From 3e4167e0c38a2f2627e2b628f6e0e3da633a509d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Thu, 14 Sep 2023 11:56:09 -0400 Subject: [PATCH 01/86] Create draft-pdf.yml --- .github/workflows/draft-pdf.yml | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 .github/workflows/draft-pdf.yml diff --git a/.github/workflows/draft-pdf.yml b/.github/workflows/draft-pdf.yml new file mode 100644 index 000000000..1953a2c2e --- /dev/null +++ b/.github/workflows/draft-pdf.yml @@ -0,0 +1,23 @@ +on: [push] + +jobs: + paper: + runs-on: ubuntu-latest + name: Paper Draft + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Build draft PDF + uses: openjournals/openjournals-draft-action@master + with: + journal: joss + # This should be the path to the paper within your repo. + paper-path: docs/joss/paper.md + - name: Upload + uses: actions/upload-artifact@v1 + with: + name: paper + # This is the output path where Pandoc will write the compiled + # PDF. Note, this should be the same directory as the input + # paper.md + path: docs/joss/paper.pdf From 10a2701cb329520a911f43d196290a49bea401ea Mon Sep 17 00:00:00 2001 From: Milan Date: Thu, 14 Sep 2023 17:35:38 -0400 Subject: [PATCH 02/86] paper template, first paragraphs, bib --- .gitignore | 5 +- docs/img/barotropic_vorticity.jpg | Bin 128869 -> 0 bytes docs/img/galewsky.jpg | Bin 101390 -> 0 bytes docs/img/galewsky_nc_12days.png | Bin 70347 -> 0 bytes docs/img/galewsky_nc_12days_mountains.png | Bin 72995 -> 0 bytes docs/img/galewsky_nc_6days.png | Bin 42804 -> 0 bytes docs/joss/paper.bib | 424 ++++++++++++++++ docs/joss/paper.jats | 572 ++++++++++++++++++++++ docs/joss/paper.md | 139 ++++++ docs/joss/paper.pdf | Bin 0 -> 1037800 bytes docs/joss/swm.png | Bin 0 -> 823588 bytes 11 files changed, 1139 insertions(+), 1 deletion(-) delete mode 100644 docs/img/barotropic_vorticity.jpg delete mode 100644 docs/img/galewsky.jpg delete mode 100644 docs/img/galewsky_nc_12days.png delete mode 100644 docs/img/galewsky_nc_12days_mountains.png delete mode 100644 docs/img/galewsky_nc_6days.png create mode 100644 docs/joss/paper.bib create mode 100644 docs/joss/paper.jats create mode 100644 docs/joss/paper.md create mode 100644 docs/joss/paper.pdf create mode 100644 docs/joss/swm.png diff --git a/.gitignore b/.gitignore index 533680177..640a6c1cb 100644 --- a/.gitignore +++ b/.gitignore @@ -35,4 +35,7 @@ Manifest.toml run_*/ # no video outputs -*.mp4 \ No newline at end of file +*.mp4 + +# JOSS paper +docs/joss/media \ No newline at end of file diff --git a/docs/img/barotropic_vorticity.jpg b/docs/img/barotropic_vorticity.jpg deleted file mode 100644 index 3a269f828be7670c5660f1669508efd446ff2c77..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 128869 zcmeFZcQjqk8!x<%-g_sA61~@Ghln0MhHq`+058A~ zaJ>QKtHGTg1AwkBzz+Zb0e}mk0Ki0_=ZatT^xH=X?ayyQegJbZ<1?L8kk2-|tOi@9kArcr-hI1ZSG(Kx98e{81-KmC-OJs<&z2qT?&jeu 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zVj6|kqhG#U7>b-a?ccyRcaWF)4{vDW9e-KyA5OIM_2.3.CO;2}, + urldate = {2022-01-07}, + langid = {english}, + file = {/Users/milan/Zotero/storage/29QHT8QP/Bourke - 1972 - An Efficient, One-Level, Primitive-Equation Spectr.pdf} +} + +@article{Burns2020, + title = {Dedalus: {{A}} Flexible Framework for Numerical Simulations with Spectral Methods}, + shorttitle = {Dedalus}, + author = {Burns, Keaton J. and Vasil, Geoffrey M. and Oishi, Jeffrey S. and Lecoanet, Daniel and Brown, Benjamin P.}, + year = {2020}, + month = apr, + journal = {Physical Review Research}, + volume = {2}, + number = {2}, + pages = {023068}, + publisher = {{American Physical Society}}, + doi = {10.1103/PhysRevResearch.2.023068}, + urldate = {2023-09-14}, + abstract = {Numerical solutions of partial differential equations enable a broad range of scientific research. The Dedalus project is a flexible, open-source, parallelized computational framework for solving general partial differential equations using spectral methods. Dedalus translates plain-text strings describing partial differential equations into efficient solvers. This paper details the numerical method that enables this translation, describes the design and implementation of the codebase, and illustrates its capabilities with a variety of example problems. The numerical method is a first-order generalized tau formulation that discretizes equations into banded matrices. This method is implemented with an object-oriented design. Classes for spectral bases and domains manage the discretization and automatic parallel distribution of variables. Discretized fields and mathematical operators are symbolically manipulated with a basic computer algebra system. Initial value, boundary value, and eigenvalue problems are efficiently solved using high-performance linear algebra, transform, and parallel communication libraries. Custom analysis outputs can also be specified in plain text and stored in self-describing portable formats. The performance of the code is evaluated with a parallel scaling benchmark and a comparison to a finite-volume code. The features and flexibility of the codebase are illustrated by solving several examples: the nonlinear Schr\"odinger equation on a graph, a supersonic magnetohydrodynamic vortex, quasigeostrophic flow, Stokes flow in a cylindrical annulus, normal modes of a radiative atmosphere, and diamagnetic levitation.}, + file = {/Users/milan/Zotero/storage/D23SMV3X/Burns et al. - 2020 - Dedalus A flexible framework for numerical simula.pdf;/Users/milan/Zotero/storage/NRZ7F4CI/PhysRevResearch.2.html} +} + +@manual{Cartopy, +author = {{Met Office}}, +title = {Cartopy: a cartographic python library with a Matplotlib interface}, +year = {2010 - 2015}, +address = {Exeter, Devon }, +url = {https://scitools.org.uk/cartopy} +} + +@article{Corby1972, + title = {A General Circulation Model of the Atmosphere Suitable for Long Period Integrations}, + author = {Corby, G. A. and Gilchrist, A. and Newson, R. L.}, + year = {1972}, + journal = {Quarterly Journal of the Royal Meteorological Society}, + volume = {98}, + number = {418}, + pages = {809--832}, + issn = {1477-870X}, + doi = {10.1002/qj.49709841808}, + urldate = {2023-03-07}, + abstract = {The design of a general circulation model using the primitive equations in spherical form is described, including a statement of the finite difference forms used to integrate the system and explanations of the motives for unusual aspects of the finite difference scheme. The model incorporates the hydrological cycle, topography, a simple scheme for the radiative exchanges and arrangements for the simulation of deep free convection (sub grid-scale) and for the representation of exchanges of momentum, sensible and latent heat with the underlying surface. An experiment performed with the model forms the subject of a separate paper.}, + langid = {english}, + file = {/Users/milan/Zotero/storage/VTBQF9B7/Corby et al. - 1972 - A general circulation model of the atmosphere suit.pdf;/Users/milan/Zotero/storage/LMC9D2VS/qj.html} +} + +@article{Gorski2005, + title = {{{HEALPix}}: {{A Framework}} for {{High-Resolution Discretization}} and {{Fast Analysis}} of {{Data Distributed}} on the {{Sphere}}}, + shorttitle = {{{HEALPix}}}, + author = {G{\'o}rski, K. M. and Hivon, E. and Banday, A. J. and Wandelt, B. D. and Hansen, F. K. and Reinecke, M. and Bartelmann, M.}, + year = {2005}, + month = apr, + journal = {The Astrophysical Journal}, + volume = {622}, + number = {2}, + pages = {759}, + publisher = {{IOP Publishing}}, + issn = {0004-637X}, + doi = {10.1086/427976}, + urldate = {2023-09-14}, + langid = {english}, + file = {/Users/milan/Zotero/storage/GGI4L9QV/Górski et al. - 2005 - HEALPix A Framework for High-Resolution Discretiz.pdf} +} + +@article{Held1994, + title = {A {{Proposal}} for the {{Intercomparison}} of the {{Dynamical Cores}} of {{Atmospheric General Circulation Models}}}, + author = {Held, Isaac M. and Suarez, Max J.}, + year = {1994}, + month = oct, + journal = {Bulletin of the American Meteorological Society}, + volume = {75}, + number = {10}, + pages = {1825--1830}, + publisher = {{American Meteorological Society}}, + issn = {0003-0007, 1520-0477}, + doi = {10.1175/1520-0477(1994)075<1825:APFTIO>2.0.CO;2}, + urldate = {2022-01-07}, + abstract = {A benchmark calculation is proposed for evaluating the dynamical cores of atmospheric general circulation models independently of the physical parameterizations. The test focuses on the long-term statistical properties of a fully developed general circulation; thus, it is particularly appropriate for intercomparing the dynamics used in climate models. To illustrate the use of this benchmark, two very different atmospheric dynamical cores\textemdash one spectral, one finite difference\textemdash are compared. It is found that the long-term statistics produced by the two models are very similar. Selected results from these calculations are presented to initiate the intercomparison.}, + chapter = {Bulletin of the American Meteorological Society}, + langid = {english}, + file = {/Users/milan/Zotero/storage/NUBBDSUA/Held and Suarez - 1994 - A Proposal for the Intercomparison of the Dynamica.pdf;/Users/milan/Zotero/storage/NXJH4Q6M/1520-0477_1994_075_1825_apftio_2_0_co_2.html} +} + +@article{Hoskins1975, + title = {A Multi-Layer Spectral Model and the Semi-Implicit Method}, + author = {Hoskins, B. J. and Simmons, A. J.}, + year = {1975}, + journal = {Quarterly Journal of the Royal Meteorological Society}, + volume = {101}, + number = {429}, + pages = {637--655}, + issn = {1477-870X}, + doi = {10.1002/qj.49710142918}, + urldate = {2023-03-03}, + abstract = {The formulaton of a multi-layer primitive equation model on the sphere is described. The horizontal representation is by means of spherical harmonics, truncated either in the triangular or rhomboidal manner. The time integration is performed using the semi-implicit method in which the linearized gravity wave terms are time averaged and thus the fast moving waves of this type are slowed. For a 5-layer hemispheric model with triangular truncation at wavenumber 21, storage of 38K words is needed and with the time scheme allowing a time-step of 90 minutes, one day's simulation requires 11 seconds of CDC 7600 time. The growth of a baroclinic wave on a simple basic state of differential solid body rotation is exhibited. The errors involved in this case in utilizing the large time-step allowed by the semi-implicit scheme are thoroughly examined by comparing wave amplitudes and phases, conservation properties and gravity wave treatment for different time-steps. These errors are found to be negligible. The conservation properties of the model are in fact extremely good. The vertical finite differencing scheme of Arakawa is studied in the same baroclinic instability simulation. The growth is similar though the conservation of angular momentum is greatly improved. The transform method used in all these integrations allows some aliasing, but this is shown to be negligible.}, + langid = {english}, + file = {/Users/milan/Zotero/storage/HFWTWI7A/Hoskins and Simmons - 1975 - A multi-layer spectral model and the semi-implicit.pdf;/Users/milan/Zotero/storage/4Y43KN5T/qj.html} +} + +@article{Hotta2018, + title = {A Nestable, Multigrid-Friendly Grid on a Sphere for Global Spectral Models Based on {{Clenshaw}}\textendash{{Curtis}} Quadrature}, + author = {Hotta, Daisuke and Ujiie, Masashi}, + year = {2018}, + journal = {Quarterly Journal of the Royal Meteorological Society}, + volume = {144}, + number = {714}, + pages = {1382--1397}, + issn = {1477-870X}, + doi = {10.1002/qj.3282}, + urldate = {2022-12-08}, + abstract = {A new grid system on a sphere is proposed which allows for straightforward implementation of both spherical-harmonics-based spectral methods and gridpoint-based multigrid methods. The latitudinal gridpoints in the new grid are equidistant and spectral transforms in the latitudinal direction are performed using Clenshaw\textendash Curtis quadrature. The spectral transforms with this new grid and quadrature are shown to be exact within machine precision provided that the grid truncation is such that there are at least 2N + 1 latitudinal gridpoints for the total truncation wavenumber of N. The new grid and quadrature is implemented and tested on a shallow-water equations model and the hydrostatic dry dynamical core of the global NWP model JMA-GSM. The integration results obtained with the new quadrature are shown to be almost identical to those obtained with the conventional Gaussian quadrature on a Gaussian grid. Only minor code changes are required to adapt any Gaussian-based spectral models to employ the proposed quadrature.}, + langid = {english}, + keywords = {Clenshaw\textendash Curtis quadrature,Fej\'er quadrature,global spectral model,Legendre transform,multigrid}, + file = {/Users/milan/Zotero/storage/5HXBNCQW/Hotta and Ujiie - 2018 - A nestable, multigrid-friendly grid on a sphere fo.pdf;/Users/milan/Zotero/storage/J5BN2ENU/qj.html} +} + +@article{Hunter2007, + title = {Matplotlib: {{A 2D Graphics Environment}}}, + shorttitle = {Matplotlib}, + author = {Hunter, John D.}, + year = {2007}, + month = may, + journal = {Computing in Science \& Engineering}, + volume = {9}, + number = {3}, + pages = {90--95}, + issn = {1558-366X}, + doi = {10.1109/MCSE.2007.55}, + abstract = {Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operating systems}, + keywords = {application development,Computer languages,Equations,Graphical user interfaces,Graphics,Image generation,Interpolation,Operating systems,Packaging,Programming profession,Python,scientific programming,scripting languages,User interfaces}, + file = {/Users/milan/Zotero/storage/6YGLJIB7/Hunter - 2007 - Matplotlib A 2D Graphics Environment.pdf} +} + +@article{Jablonowski2006, + title = {A Baroclinic Instability Test Case for Atmospheric Model Dynamical Cores}, + author = {Jablonowski, Christiane and Williamson, David L.}, + year = {2006}, + month = oct, + journal = {Quarterly Journal of the Royal Meteorological Society}, + volume = {132}, + number = {621C}, + pages = {2943--2975}, + issn = {00359009, 1477870X}, + doi = {10.1256/qj.06.12}, + urldate = {2023-03-22}, + abstract = {A deterministic initial-value test case for dry dynamical cores of atmospheric general-circulation models is presented that assesses the evolution of an idealized baroclinic wave in the northern hemisphere. The initial zonal state is quasi-realistic and completely defined by analytic expressions which are a steady-state solution of the adiabatic inviscid primitive equations with pressure-based vertical coordinates. A two-component test strategy first evaluates the ability of the discrete approximations to maintain the steady-state solution. Then an overlaid perturbation is introduced which triggers the growth of a baroclinic disturbance over the course of several days.}, + langid = {english}, + file = {/Users/milan/Zotero/storage/VH7SAZC2/Jablonowski and Williamson - 2006 - A baroclinic instability test case for atmospheric.pdf} +} + +@article{Klower2022, + title = {Fluid {{Simulations Accelerated With}} 16 {{Bits}}: {{Approaching}} 4x {{Speedup}} on {{A64FX}} by {{Squeezing ShallowWaters}}.Jl {{Into Float16}}}, + shorttitle = {Fluid {{Simulations Accelerated With}} 16 {{Bits}}}, + author = {Kl{\"o}wer, Milan and Hatfield, Sam and Croci, Matteo and D{\"u}ben, Peter D. and Palmer, Tim N.}, + year = {2022}, + journal = {Journal of Advances in Modeling Earth Systems}, + volume = {14}, + number = {2}, + pages = {e2021MS002684}, + issn = {1942-2466}, + doi = {10.1029/2021MS002684}, + urldate = {2022-06-30}, + abstract = {Most Earth-system simulations run on conventional central processing units in 64-bit double precision floating-point numbers Float64, although the need for high-precision calculations in the presence of large uncertainties has been questioned. Fugaku, currently the world's fastest supercomputer, is based on A64FX microprocessors, which also support the 16-bit low-precision format Float16. We investigate the Float16 performance on A64FX with ShallowWaters.jl, the first fluid circulation model that runs entirely with 16-bit arithmetic. The model implements techniques that address precision and dynamic range issues in 16 bits. The precision-critical time integration is augmented to include compensated summation to minimize rounding errors. Such a compensated time integration is as precise but faster than mixed precision with 16 and 32-bit floats. As subnormals are inefficiently supported on A64FX the very limited range available in Float16 is 6 \texttimes{} 10-5 to 65,504. We develop the analysis-number format Sherlogs.jl to log the arithmetic results during the simulation. The equations in ShallowWaters.jl are then systematically rescaled to fit into Float16, using 97\% of the available representable numbers. Consequently, we benchmark speedups of up to 3.8x on A64FX with Float16. Adding a compensated time integration, speedups reach up to 3.6x. Although ShallowWaters.jl is simplified compared to large Earth-system models, it shares essential algorithms and therefore shows that 16-bit calculations are indeed a competitive way to accelerate Earth-system simulations on available hardware.}, + langid = {english}, + keywords = {climate models,floating-point numbers,hardware acceleration,low precision,rounding errors}, + file = {/Users/milan/Zotero/storage/68GUS3P9/Klöwer et al. - 2022 - Fluid Simulations Accelerated With 16 Bits Approa.pdf;/Users/milan/Zotero/storage/R4EELGQV/2021MS002684.html} +} + +@article{Kucharski2013, + title = {On the {{Need}} of {{Intermediate Complexity General Circulation Models}}: {{A}} ``{{SPEEDY}}'' {{Example}}}, + shorttitle = {On the {{Need}} of {{Intermediate Complexity General Circulation Models}}}, + author = {Kucharski, Fred and Molteni, Franco and King, Martin P. and Farneti, Riccardo and Kang, In-Sik and Feudale, Laura}, + year = {2013}, + month = jan, + journal = {Bulletin of the American Meteorological Society}, + volume = {94}, + number = {1}, + pages = {25--30}, + publisher = {{American Meteorological Society}}, + doi = {10.1175/BAMS-D-11-00238.1}, + urldate = {2023-09-14}, + abstract = {"On the Need of Intermediate Complexity General Circulation Models: A ``SPEEDY'' Example" published on Jan 2013 by American Meteorological Society.}, + chapter = {Bulletin of the American Meteorological Society}, + langid = {english}, + file = {/Users/milan/Zotero/storage/N8YS452F/Kucharski et al. - 2013 - On the Need of Intermediate Complexity General Cir.pdf} +} + +@misc{Malardel2016, + title = {A New Grid for the {{IFS}}}, + author = {Malardel, Sylvie and Wedi, Nils and Deconinck, Nils and Diamantakis, Michail and Kuehnlein, Christian and Mozdzynski, George and Hamrud, Mats and Smolarkiewicz, Piotr}, + year = {2016}, + journal = {ECMWF Newsletter}, + abstract = {ECMWF will implement a resolution upgrade for high-resolution forecasts (HRES) and ensemble forecasts (ENS) in spring 2016. HRES will then be run on a grid with a grid-point distance between neighbouring points of approximately 9 km instead of 16 km in the current configuration.}, + howpublished = {https://www.ecmwf.int/node/15041}, + file = {/Users/milan/Zotero/storage/RTX8TJ4K/A-new-grid-for-the-IFS.pdf} +} + +@article{Molteni2003, + title = {Atmospheric Simulations Using a {{GCM}} with Simplified Physical Parametrizations. {{I}}: Model Climatology and Variability in Multi-Decadal Experiments}, + shorttitle = {Atmospheric Simulations Using a {{GCM}} with Simplified Physical Parametrizations. {{I}}}, + author = {Molteni, F.}, + year = {2003}, + month = jan, + journal = {Climate Dynamics}, + volume = {20}, + number = {2}, + pages = {175--191}, + issn = {1432-0894}, + doi = {10.1007/s00382-002-0268-2}, + urldate = {2023-09-14}, + abstract = {This work describes the formulation and climatology of an atmospheric general circulation model (GCM) of intermediate complexity, based on a spectral primitive-equation dynamical core and a set of simplified physical parametrization schemes. The parametrization package has been specially designed to work in models with just a few vertical levels, and is based on the same physical principles adopted in the schemes of state-of-the art GCMs. The parametrized processes include large-scale condensation, convection, clouds, short-wave and long-wave radiation, surface fluxes and vertical diffusion. In the current configuration, the model (nicknamed SPEEDY, from Simplified Parametrizations, primitivE-Equation DYnamics") has five vertical levels and a spectral truncation at total wave number 30 (T30L5). The top vertical level (crudely) represents the stratosphere, the bottom one the planetary boundary layer. Computationally, SPEEDY requires (at least) one order of magnitude less CPU time than a state-of-the-art GCM at the same horizontal resolution, and is therefore suitable for studies of inter-decadal or inter-centennial variability. Statistics of the model mean state and variability are computed from an ensemble of 41-year simulations forced by observed sea-surface temperatures in the period 1952\textendash 1992. The model mean state is closer to the observed climatology during the (boreal) winter than during summer. In winter (i.e. December to February, DJF), the model underestimates the amplitude of the Northern Hemisphere stationary wave pattern, particularly in the European-Atlantic sector. Some aspects of the systematic error of SPEEDY are in fact typical of many GCMs, although the error amplitude is stronger than in state-of-the-art models. On the other hand, the global distribution of precipitation in DJF is quite realistic, and compares well with that of more complex GCMs. In summer (June to August), a strong negative bias in the mid-tropospheric temperature generates a Northern Hemisphere circulation with some springtime characteristics. In particular, the position of the Tropical Convergence Zone in the Indian Ocean remains too far south, leading to a deficient simulation of the monsoon circulation over South Asia. The simulated variability during the northern winter is reasonably realistic as far as the spatial distribution is concerned, although some underestimation in the intensity can be found, particularly in the low-frequency range and in the Atlantic sector. The atmospheric response to ENSO events is also weaker than observed, although the spatial patterns of the rainfall and geopotential response in the Pacific sector are in phase with their observed counterparts. In the Atlantic/Eurasian region, the spatial patterns associated with the interdecadal trends in the simulated and observed large-scale circulation show a clear positive correlation, consistent with the hypothesis of a positive ocean\textendash atmosphere feedback on decadal time scales.}, + langid = {english}, + keywords = {Atmospheric General Circulation Model,ENSO Event,General Circulation Model,Planetary Boundary Layer,Vertical Level}, + file = {/Users/milan/Zotero/storage/22FVB5QT/Molteni - 2003 - Atmospheric simulations using a GCM with simplifie.pdf} +} + +@article{Nakano2018, + title = {Single {{Precision}} in the {{Dynamical Core}} of a {{Nonhydrostatic Global Atmospheric Model}}: {{Evaluation Using}} a {{Baroclinic Wave Test Case}}}, + shorttitle = {Single {{Precision}} in the {{Dynamical Core}} of a {{Nonhydrostatic Global Atmospheric Model}}}, + author = {Nakano, Masuo and Yashiro, Hisashi and Kodama, Chihiro and Tomita, Hirofumi}, + year = {2018}, + month = feb, + journal = {Monthly Weather Review}, + volume = {146}, + number = {2}, + pages = {409--416}, + publisher = {{American Meteorological Society}}, + issn = {1520-0493, 0027-0644}, + doi = {10.1175/MWR-D-17-0257.1}, + urldate = {2021-06-02}, + abstract = {{$<$}section class="abstract"{$><$}h2 class="abstractTitle text-title my-1" id="d145702010e111"{$>$}Abstract{$<$}/h2{$><$}p{$>$}Reducing the computational cost of weather and climate simulations would lower electric energy consumption. From the standpoint of reducing costs, the use of reduced precision arithmetic has become an active area of research. Here the impact of using single-precision arithmetic on simulation accuracy is examined by conducting Jablonowski and Williamson's baroclinic wave tests using the dynamical core of a global fully compressible nonhydrostatic model. The model employs a finite-volume method discretized on an icosahedral grid system and its mesh size is set to 220, 56, 14, and 3.5 km. When double-precision arithmetic is fully replaced by single-precision arithmetic, a spurious wavenumber-5 structure becomes dominant in both hemispheres, rather than the expected baroclinic wave growth only in the Northern Hemisphere. It was found that this spurious wave growth comes from errors in the calculation of gridcell geometrics. Therefore, an additional simulation was conducted using double precision for calculations that only need to be performed for model setup, including calculation of gridcell geometrics, and single precision everywhere else, meaning that all calculations performed each time step used single precision. In this case, the model successfully simulated the growth of the baroclinic wave with only small errors and a 46\% reduction in runtime. These results suggest that the use of single-precision arithmetic will allow significant reduction of computational costs in next-generation weather and climate simulations using a fully compressible nonhydrostatic global model with the finite-volume method.{$<$}/p{$><$}/section{$>$}}, + chapter = {Monthly Weather Review}, + langid = {english}, + file = {/Users/milan/Zotero/storage/XE4CRLDK/Nakano et al. - 2018 - Single Precision in the Dynamical Core of a Nonhyd.pdf;/Users/milan/Zotero/storage/A966XWT3/mwr-d-17-0257.1.html} +} + +@article{Ramadhan2020, + title = {Oceananigans.Jl: {{Fast}} and Friendly Geophysical Fluid Dynamics on {{GPUs}}}, + shorttitle = {Oceananigans.Jl}, + author = {Ramadhan, Ali and Wagner, Gregory LeClaire and Hill, Chris and Campin, Jean-Michel and Churavy, Valentin and Besard, Tim and Souza, Andre and Edelman, Alan and Ferrari, Raffaele and Marshall, John}, + year = {2020}, + month = sep, + journal = {Journal of Open Source Software}, + volume = {5}, + number = {53}, + pages = {2018}, + issn = {2475-9066}, + doi = {10.21105/joss.02018}, + urldate = {2023-09-14}, + abstract = {Ramadhan et al., (2020). Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs. Journal of Open Source Software, 5(53), 2018, https://doi.org/10.21105/joss.02018}, + langid = {english}, + file = {/Users/milan/Zotero/storage/UBSRFFJG/Ramadhan et al. - 2020 - Oceananigans.jl Fast and friendly geophysical flu.pdf} +} + +@article{Rasp2018, + title = {Deep Learning to Represent Subgrid Processes in Climate Models}, + author = {Rasp, Stephan and Pritchard, Michael S. and Gentine, Pierre}, + year = {2018}, + month = sep, + journal = {Proceedings of the National Academy of Sciences}, + volume = {115}, + number = {39}, + pages = {9684--9689}, + file = {/Users/milan/Zotero/storage/4FW52IRQ/9684.html} +} + +@article{Schneider2017, + title = {Earth {{System Modeling}} 2.0: {{A Blueprint}} for {{Models That Learn From Observations}} and {{Targeted High-Resolution Simulations}}}, + shorttitle = {Earth {{System Modeling}} 2.0}, + author = {Schneider, Tapio and Lan, Shiwei and Stuart, Andrew and Teixeira, Jo{\~a}o}, + year = {2017}, + journal = {Geophysical Research Letters}, + volume = {44}, + number = {24}, + pages = {12,396--12,417}, + issn = {1944-8007}, + doi = {10.1002/2017GL076101}, + urldate = {2022-10-21}, + abstract = {Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.}, + langid = {english}, + keywords = {data assimilation,Earth system models,Kalman inversion,machine learning,Markov chain Monte Carlo,parameterizations}, + file = {/Users/milan/Zotero/storage/79YWM78D/Schneider et al. - 2017 - Earth System Modeling 2.0 A Blueprint for Models .pdf;/Users/milan/Zotero/storage/SL4Z8NTA/2017GL076101.html} +} + +@article{Schneider2023, + title = {Harnessing {{AI}} and Computing to Advance Climate Modelling and Prediction}, + author = {Schneider, Tapio and Behera, Swadhin and Boccaletti, Giulio and Deser, Clara and Emanuel, Kerry and Ferrari, Raffaele and Leung, L. Ruby and Lin, Ning and M{\"u}ller, Thomas and Navarra, Antonio and Ndiaye, Ousmane and Stuart, Andrew and Tribbia, Joseph and Yamagata, Toshio}, + year = {2023}, + month = sep, + journal = {Nature Climate Change}, + volume = {13}, + number = {9}, + pages = {887--889}, + publisher = {{Nature Publishing Group}}, + issn = {1758-6798}, + doi = {10.1038/s41558-023-01769-3}, + urldate = {2023-09-14}, + abstract = {There are contrasting views on how to produce the accurate predictions that are needed to guide climate change adaptation. Here, we argue for harnessing artificial intelligence, building on domain-specific knowledge and generating ensembles of moderately high-resolution (10\textendash 50 km) climate simulations as anchors for detailed hazard models.}, + copyright = {2023 Springer Nature Limited}, + langid = {english}, + keywords = {Climate and Earth system modelling,Projection and prediction}, + file = {/Users/milan/Zotero/storage/Q8DTJ4NT/Schneider et al. - 2023 - Harnessing AI and computing to advance climate mod.pdf} +} + +@article{Simmons1978, + title = {Stability of the {{Semi-Implicit Method}} of {{Time Integration}}}, + author = {Simmons, A. J. and Hoskins, B. J. and Burridge, D. M.}, + year = {1978}, + month = mar, + journal = {Monthly Weather Review}, + volume = {106}, + number = {3}, + pages = {405--412}, + publisher = {{American Meteorological Society}}, + issn = {1520-0493, 0027-0644}, + doi = {10.1175/1520-0493(1978)106<0405:SOTSIM>2.0.CO;2}, + urldate = {2023-03-07}, + abstract = {Abstract The stability of the semi-implicit method of time integration of the primitive equations is examined when the actual temperature deviates from the reference profile about which the implicitly treated gravity wave terms are linearized. The stability criterion is shown in general to be much more stringent than might he assumed from a simple analytical solution. Instability may occur when there exists a region in which the static stability of the actual atmosphere differs significantly from that of the reference atmosphere, and for realistic actual profiles and commonly chosen reference profiles it is likely to arise at vertical resolutions that are little higher than those used in previous tests of the scheme. Stabilization is achieved either by an appropriate change of reference profile or by a modification of the time-averaging of gravity wave terms. Both may result in a small further reduction in gravity wave phase speeds. Alternatives are mentioned which give better phase speeds at the expense of a reduced time step.}, + chapter = {Monthly Weather Review}, + langid = {english}, + file = {/Users/milan/Zotero/storage/A2NGNVRV/Simmons et al. - 1978 - Stability of the Semi-Implicit Method of Time Inte.pdf} +} + +@article{Simmons1981, + title = {An {{Energy}} and {{Angular-Momentum Conserving Vertical Finite-Difference Scheme}} and {{Hybrid Vertical Coordinates}}}, + author = {Simmons, A. J. and Burridge, D. M.}, + year = {1981}, + month = apr, + journal = {Monthly Weather Review}, + volume = {109}, + number = {4}, + pages = {758--766}, + publisher = {{American Meteorological Society}}, + issn = {1520-0493, 0027-0644}, + doi = {10.1175/1520-0493(1981)109<0758:AEAAMC>2.0.CO;2}, + urldate = {2023-03-07}, + abstract = {Abstract An energy and angular-momentum conserving vertical finite-difference scheme is introduced for a general terrain-following vertical coordinate which is a function of pressure and its surface value. A corresponding semi-implicit time scheme is also defined. These schemes am used to compare the usual sigma coordinate with the hybrid coordinate which reduces to pressure above a fixed level and with a modified hybrid coordinate which tends uniformly to pressure at upper levels. Error in the representation of the stratospheric pressure gradient over steep orography can be significantly reduced by use of the hybrid coordinate but the semi-implicit scheme is less stable. The modified hybrid coordinate offers a useful compromise.}, + chapter = {Monthly Weather Review}, + langid = {english}, + file = {/Users/milan/Zotero/storage/WHTSRU3P/Simmons and Burridge - 1981 - An Energy and Angular-Momentum Conserving Vertical.pdf} +} + +@article{Vana2017, + title = {Single {{Precision}} in {{Weather Forecasting Models}}: {{An Evaluation}} with the {{IFS}}}, + shorttitle = {Single {{Precision}} in {{Weather Forecasting Models}}}, + author = {V{\'a}{\v n}a, Filip and D{\"u}ben, Peter and Lang, Simon and Palmer, Tim and Leutbecher, Martin and Salmond, Deborah and Carver, Glenn}, + year = {2017}, + month = feb, + journal = {Monthly Weather Review}, + volume = {145}, + number = {2}, + pages = {495--502}, + issn = {0027-0644, 1520-0493}, + doi = {10.1175/MWR-D-16-0228.1}, + urldate = {2020-02-25}, + abstract = {Earth's climate is a nonlinear dynamical system with scale-dependent Lyapunov exponents. As such, an important theoretical question for modeling weather and climate is how much real information is carried in a model's physical variables as a function of scale and variable type. Answering this question is of crucial practical importance given that the development of weather and climate models is strongly constrained by available supercomputer power. As a starting point for answering this question, the impact of limiting almost all real-number variables in the forecasting mode of ECMWF Integrated Forecast System (IFS) from 64 to 32 bits is investigated. Results for annual integrations and medium-range ensemble forecasts indicate no noticeable reduction in accuracy, and an average gain in computational efficiency by approximately 40\%. This study provides the motivation for more scale-selective reductions in numerical precision.}, + langid = {english} +} + +@article{Williams2011, + title = {The {{RAW Filter}}: {{An Improvement}} to the {{Robert}}\textendash{{Asselin Filter}} in {{Semi-Implicit Integrations}}}, + shorttitle = {The {{RAW Filter}}}, + author = {Williams, Paul D.}, + year = {2011}, + month = jun, + journal = {Monthly Weather Review}, + volume = {139}, + number = {6}, + pages = {1996--2007}, + issn = {0027-0644, 1520-0493}, + doi = {10.1175/2010MWR3601.1}, + urldate = {2021-12-17}, + abstract = {Errors caused by discrete time stepping may be an important component of total model error in contemporary atmospheric and oceanic simulations. To reduce time-stepping errors in leapfrog integrations, the Robert\textendash Asselin\textendash Williams (RAW) filter was proposed by the author as a simple improvement to the widely used Robert\textendash Asselin (RA) filter. The present paper examines the behavior of the RAW filter in semi-implicit integrations. First, in a linear theoretical analysis, the stability and accuracy are interrogated by deriving analytic expressions for the amplitude errors and phase errors. Then, power-series expansions are used to interpret the leading-order errors for small time steps and hence to identify optimal values of the filter parameters. Finally, the RAW filter is tested in a realistic nonlinear setting, by applying it to semi-implicit integrations of the elastic pendulum equations. The results suggest that replacing the RA filter with the RAW filter could reduce time-stepping errors in semi-implicit integrations.}, + langid = {english}, + file = {/Users/milan/Zotero/storage/YS2LGST8/Williams - 2011 - The RAW Filter An Improvement to the Robert–Assel.pdf} +} diff --git a/docs/joss/paper.jats b/docs/joss/paper.jats new file mode 100644 index 000000000..80f21d744 --- /dev/null +++ b/docs/joss/paper.jats @@ -0,0 +1,572 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +0 +N/A + +SpeedyWeather.jl: Reinventing atmospheric general +circulation models towards interactivity, extensibility and +composability + + + +https://orcid.org/0000-0002-3920-4356 + +Klöwer +Milan + +milank@mit.edu + + +* + + + +Gelbrecht +Maximilian + + + + + + +Hotta +Daisuke + + + + + + +Willmert +Justin + + + + + +Silvestri +Simone + + + + + +Wagner +Gregory L + + + + + +White +Alistair + + + + + + +Hatfield +Sam + + + + + +Meyer +David + + + + + +Kimpson +Tom + + + + + + +Constantinou +Navid C + + + + + +Hill +Chris + + + + + +Massachusetts Institute of Technology, Cambridge, MA, +USA + + + + +University of Oxford, UK + + + + +Technical University Munich, Germany + + + + +Potsdam Institute for Climate Impact Research, +Germany + + + + +Japan Meteorological Agency, Tsukuba, Japan + + + + +University of Reading, UK + + + + +University of Minnesota, Minneapolis, MN, USA + + + + +European Centre for Medium-Range Weather Forecasts, +Reading, UK + + + + +University of Melbourne, Melbourne, Australia + + + + +Australian National University, Canberra, +Australia + + + + +* E-mail: milank@mit.edu + + +14 +9 +2023 + +¿VOL? +¿ISSUE? +¿PAGE? + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Julia +weather +climate +general circulation model +spectral +spherical harmonic transform + + + + + + Summary +

SpeedyWeather.jl is a library to simulate and analyse the global + atmospheric circulation on the sphere. It implements several 2D and 3D + models to solve the primitive equations with and without humidity, the + shallow water equations + ([fig:swm]), or the + barotropic vorticity equations with spherical harmonics.

+

The user interface of SpeedyWeather.jl is heavily influenced by + Oceananigans.jl + (Ramadhan + et al., 2020). A monolithic interface is deliberately + avoided

+

To be extendible and composable, SpeedyWeather.jl relies on + multiple dispatch from the Julia programming language + (Bezanson + et al., 2017). Every model component is defined as a new type + SomeComponent <: AbstractComponent, + i.e. subtype of an abstract super type + AbstractComponent. Extending SpeedyWeather.jl + can therefore easily achieved by defining a new + OtherComponent <: AbstractComponent

+

The dynamical core of SpeedyWeather.jl uses established numerics + (Bourke, + 1972; + Hoskins + & Simmons, 1975; + Simmons + et al., 1978; + Simmons + & Burridge, 1981), widely adapted in numerical weather + prediction. It is based on the spherical harmonic transform with a + leapfrog-based semi-implicit time integration + (Hoskins + & Simmons, 1975) and a Robert-Asselin-Williams filter + (Amezcua + et al., 2011; + Williams, + 2011). The spherical harmonic transform is grid-flexible. Any + iso-latitude ring-based grid can be used and new grids can be + externally defined and passed on as argument. Many grids are already + implemented: The conventional Gaussian grid, a regular + longitude-latitude grid, the octahedral Gaussian grid + (Malardel + et al., 2016), the octahedral Clenshaw-Curtis grid + (Hotta + & Ujiie, 2018), and the HEALPix grid + (Górski + et al., 2005). Both SpeedyWeather.jl and its spherical harmonic + transform are also number format-flexible. 32-bit single-precision + floating-point numbers (Float32) are the default as adapted by other + modelling efforts + (Váňa + et al., 2017), but Float64 and other custom number formats can + be used with a single code basis. Julia will compile to the choice of + the number format and grid (and other model components) + just-in-time.

+
+ + Statement of need +

Most weather and climate models are written in Fortran and have + been developed over decades. From this tradition follows a specific + programming style and associated user interface. SpeedyWeather.jl is a + fresh approach to atmospheric models that have been very influential + in many areas of scientific and high-performance computing as well as + climate change mitigation and adaptation.

+ +

Shallow water simulation with SpeedyWeather.jl. Relative + vorticity with a spectral resolution of T1023 (about 20km) simulated + in Float32 on an octahedral Clenshaw-Curtis grid + (Hotta + & Ujiie, 2018). Relative vorticity is visualised with + Matplotlib + (Hunter, + 2007) and Cartopy + (Met + Office, 2010 - 2015) using a transparent-to-white colormap to + mimic the appearance of clouds. Underlain is NASA’s blue marble from + June 2004. +

+ +
+
+ + Acknowledgements +

We acknowledge contributions from Mosè Giordano, Valentin Churavy + and Pietro Monticone who have also committed to the SpeedyWeather.jl + repository, and the wider Julia community help and support. We + gratefully acknowledge funding from the National Science Foundation + (…) and the European Research Council under the European Union’s + Horizon 2020 research and innovation programme for the ITHACA grant + (no. 741112).

+
+ + + + + + + AmezcuaJavier + KalnayEugenia + WilliamsPaul D. + + The Effects of the RAW Filter on the Climatology and Forecast Skill of the SPEEDY Model + Monthly Weather Review + American Meteorological Society + 201102 + 20230606 + 139 + 2 + 1520-0493 + 10.1175/2010MWR3530.1 + 608 + 619 + + + + + + BezansonJeff. + EdelmanAlan. + KarpinskiStefan. + ShahViral B. + + Julia: A Fresh Approach to Numerical Computing + SIAM Review + Society for Industrial and Applied Mathematics + 201701 + 20200225 + 59 + 1 + 0036-1445 + 10.1137/141000671 + 65 + 98 + + + + + + BourkeWilliam + + An Efficient, One-Level, Primitive-Equation Spectral Model + Monthly Weather Review + 197209 + 20220107 + 100 + 9 + 0027-0644 + 10.1175/1520-0493(1972)100<0683:AEOPSM>2.3.CO;2 + 683 + 689 + + + + + + Met Office + + Cartopy: A cartographic python library with a matplotlib interface + Exeter, Devon + https://scitools.org.uk/cartopy + + + + + + GórskiK. M. + HivonE. + BandayA. J. + WandeltB. D. + HansenF. K. + ReineckeM. + BartelmannM. + + HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere + The Astrophysical Journal + IOP Publishing + 200504 + 20230914 + 622 + 2 + 0004-637X + 10.1086/427976 + 759 + + + + + + + HoskinsB. J. + SimmonsA. J. + + A multi-layer spectral model and the semi-implicit method + Quarterly Journal of the Royal Meteorological Society + 1975 + 20230303 + 101 + 429 + 1477-870X + 10.1002/qj.49710142918 + 637 + 655 + + + + + + HottaDaisuke + UjiieMasashi + + A nestable, multigrid-friendly grid on a sphere for global spectral models based on Clenshaw quadrature + Quarterly Journal of the Royal Meteorological Society + 2018 + 20221208 + 144 + 714 + 1477-870X + 10.1002/qj.3282 + 1382 + 1397 + + + + + + HunterJohn D. + + Matplotlib: A 2D Graphics Environment + Computing in Science & Engineering + 200705 + 9 + 3 + 1558-366X + 10.1109/MCSE.2007.55 + 90 + 95 + + + + + + MalardelSylvie + WediNils + DeconinckNils + DiamantakisMichail + KuehnleinChristian + MozdzynskiGeorge + HamrudMats + SmolarkiewiczPiotr + + A new grid for the IFS + ECMWF Newsletter + https://www.ecmwf.int/node/15041 + 2016 + + + + + + RamadhanAli + WagnerGregory LeClaire + HillChris + CampinJean-Michel + ChuravyValentin + BesardTim + SouzaAndre + EdelmanAlan + FerrariRaffaele + MarshallJohn + + Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs + Journal of Open Source Software + 202009 + 20230914 + 5 + 53 + 2475-9066 + 10.21105/joss.02018 + 2018 + + + + + + + SimmonsA. J. + HoskinsB. J. + BurridgeD. M. + + Stability of the Semi-Implicit Method of Time Integration + Monthly Weather Review + American Meteorological Society + 197803 + 20230307 + 106 + 3 + 1520-0493 + 10.1175/1520-0493(1978)106<0405:SOTSIM>2.0.CO;2 + 405 + 412 + + + + + + SimmonsA. J. + BurridgeD. M. + + An Energy and Angular-Momentum Conserving Vertical Finite-Difference Scheme and Hybrid Vertical Coordinates + Monthly Weather Review + American Meteorological Society + 198104 + 20230307 + 109 + 4 + 1520-0493 + 10.1175/1520-0493(1981)109<0758:AEAAMC>2.0.CO;2 + 758 + 766 + + + + + + VáňaFilip + DübenPeter + LangSimon + PalmerTim + LeutbecherMartin + SalmondDeborah + CarverGlenn + + Single Precision in Weather Forecasting Models: An Evaluation with the IFS + Monthly Weather Review + 201702 + 20200225 + 145 + 2 + 0027-0644 + 10.1175/MWR-D-16-0228.1 + 495 + 502 + + + + + + WilliamsPaul D. + + The RAW Filter: An Improvement to the Robert in Semi-Implicit Integrations + Monthly Weather Review + 201106 + 20211217 + 139 + 6 + 0027-0644 + 10.1175/2010MWR3601.1 + 1996 + 2007 + + + + +
diff --git a/docs/joss/paper.md b/docs/joss/paper.md new file mode 100644 index 000000000..ab95ad5e1 --- /dev/null +++ b/docs/joss/paper.md @@ -0,0 +1,139 @@ +--- +title: 'SpeedyWeather.jl: Reinventing atmospheric general circulation models towards interactivity, extensibility and composability' + +tags: + - Julia + - weather + - climate + - general circulation model + - spectral + - spherical harmonic transform + +authors: + - name: Milan Klöwer + orcid: 0000-0002-3920-4356 + email: milank@mit.edu + corresponding: true # (This is how to denote the corresponding author) + affiliation: "1, 2" # (Multiple affiliations must be quoted) + + - name: Maximilian Gelbrecht + affiliation: "3,4" + + - name: Daisuke Hotta + affiliation: "5,6" + + - name: Justin Willmert + affiliation: 7 + + - name: Simone Silvestri + affiliation: 1 + + - name: Gregory L Wagner + affiliation: 1 + + - name: Alistair White + affiliation: "3,4" + + - name: Sam Hatfield + affiliation: 8 + + - name: David Meyer + affiliation: 8 + + - name: Tom Kimpson + affiliation: "2,9" + + - name: Navid C Constantinou + affiliation: 10 + + - name: Chris Hill + affiliation: 1 + +affiliations: + - name: Massachusetts Institute of Technology, Cambridge, MA, USA + index: 1 + - name: University of Oxford, UK + index: 2 + - name: Technical University Munich, Germany + index: 3 + - name: Potsdam Institute for Climate Impact Research, Germany + index: 4 + - name: Japan Meteorological Agency, Tsukuba, Japan + index: 5 + - name: University of Reading, UK + index: 6 + - name: University of Minnesota, Minneapolis, MN, USA + index: 7 + - name: European Centre for Medium-Range Weather Forecasts, Reading, UK + index: 8 + - name: University of Melbourne, Melbourne, Australia + index: 9 + - name: Australian National University, Canberra, Australia + index: 10 + +date: 14 September 2023 +bibliography: paper.bib + +--- + +# Summary + +SpeedyWeather.jl is a library to simulate and analyse the global atmospheric +circulation on the sphere. It implements several 2D and 3D +models to solve the primitive equations with and without humidity, +the shallow water equations (\autoref{fig:swm}), or the barotropic vorticity equations +with spherical harmonics. + +The user interface of SpeedyWeather.jl is heavily influenced by +Oceananigans.jl [@Ramadhan2020]. A monolithic interface is deliberately avoided + +To be extendible and composable, SpeedyWeather.jl relies on multiple dispatch +from the Julia programming language [@Bezanson2017]. Every model component +is defined as a new type `SomeComponent <: AbstractComponent`, i.e. subtype of +an abstract super type `AbstractComponent`. +Extending SpeedyWeather.jl can therefore easily achieved by defining a new +`OtherComponent <: AbstractComponent` + +The dynamical core of SpeedyWeather.jl uses established numerics +[@Bourke1972; @Hoskins1975; @Simmons1978; @Simmons1981], +widely adapted in numerical weather prediction. It is based on the spherical +harmonic transform with a leapfrog-based semi-implicit time integration [@Hoskins1975] +and a Robert-Asselin-Williams filter [@Williams2011; @Amezcua2011]. +The spherical harmonic transform is grid-flexible. Any iso-latitude ring-based +grid can be used and new grids can be externally defined and passed on +as argument. Many grids are already implemented: The conventional +Gaussian grid, a regular longitude-latitude grid, +the octahedral Gaussian grid [@Malardel2016], the octahedral +Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. +Both SpeedyWeather.jl and its spherical harmonic transform are also +number format-flexible. 32-bit single-precision floating-point numbers +(Float32) are the default as adapted by other modelling efforts [@Vana2017], +but Float64 and other custom number formats can be used with a single +code basis. Julia will compile to the choice of the number format +and grid (and other model components) just-in-time. + +# Statement of need + +Most weather and climate models are written in Fortran and have been developed over +decades. From this tradition follows a specific programming style and +associated user interface. SpeedyWeather.jl is a fresh approach to atmospheric +models that have been very influential in many areas of scientific +and high-performance computing as well as climate change mitigation and adaptation. + +![Shallow water simulation with SpeedyWeather.jl. +Relative vorticity with a spectral resolution of T1023 (about 20km) simulated +in Float32 on an octahedral Clenshaw-Curtis grid [@Hotta2018]. Relative vorticity +is visualised with Matplotlib [@Hunter2007] and Cartopy [@Cartopy] using a +transparent-to-white colormap to mimic the appearance of clouds. Underlain is +NASA's blue marble from June 2004. \label{fig:swm}](swm.png) + +# Acknowledgements + +We acknowledge contributions from Mosè Giordano, Valentin Churavy and Pietro Monticone +who have also committed to the SpeedyWeather.jl repository, and the wider Julia community +help and support. We gratefully acknowledge funding from the +National Science Foundation (...) and the European Research Council +under the European Union’s Horizon 2020 research and innovation programme +for the ITHACA grant (no. 741112). + +# References diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf new file mode 100644 index 0000000000000000000000000000000000000000..210e5d203bbe2e01b957c2a22e2f32d8e23cb271 GIT binary patch literal 1037800 zcmaI7W0YiF5G7hx7rJa$b=kIU+qP}Hs>`-*8(p?-+s4apX4ZT2W8UPSyeo5^T<4w} zd&k}pk)-m%qBIP&EHI>#OZ|)gR%eHXVVDW%3G56lVYs;o=wu0)2@R6eTGR0+s+on7{ff3Z{yjh$xS|fpR~vl8V4e1m#zhe*ZOuhVr6| z11dHpSHF|$w%1Aa%X9Y2RQl%5+x?W^_2ZQ)`6KT#VhYe+y%bOGoZ5l-B{1wxOr?r2 zdI#BK$dDd@{1X|bk0ab+u1DOvlV)Tffg(oIGRO{$cn6dYAHY7nqrDhd5yyo=qDSaW z!(X$sf$Z5sa_Odq&kv|kd?k-jW>o9Iyv(DCQL>&xJe1PuwCR&0V(! z$7ho&OEa@&4Vw_N`SuX_nL(FTsv&^OKDSe5=CqM*I-|4I{M>o-lhRw}`{Q{)*{5y| zsr*3>^mYZ+H&@RfF()Bj-&)F;k3yHHe&z7~rT09Nl;>9slS<|L-2vYfnI$POxm~-h z=JV9x3fzY`^1NG8t2@pLw7vqI=kZZ#rikD#i3nt~rJYW46IHre0fa!#4^HooHVZl2 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17:47:47 -0400 Subject: [PATCH 03/86] paper.pdf and paper.jats removed --- .gitignore | 4 +- docs/joss/paper.jats | 572 ------------------------------------------- docs/joss/paper.pdf | Bin 1037800 -> 0 bytes 3 files changed, 3 insertions(+), 573 deletions(-) delete mode 100644 docs/joss/paper.jats delete mode 100644 docs/joss/paper.pdf diff --git a/.gitignore b/.gitignore index 640a6c1cb..7213efb96 100644 --- a/.gitignore +++ b/.gitignore @@ -38,4 +38,6 @@ run_*/ *.mp4 # JOSS paper -docs/joss/media \ No newline at end of file +docs/joss/media +docs/joss/paper.jats +docs/joss/paper.pdf \ No newline at end of file diff --git a/docs/joss/paper.jats b/docs/joss/paper.jats deleted file mode 100644 index 80f21d744..000000000 --- a/docs/joss/paper.jats +++ /dev/null @@ -1,572 +0,0 @@ - - -

- - - - -Journal of Open Source Software -JOSS - -2475-9066 - -Open Journals - - - -0 -N/A - -SpeedyWeather.jl: Reinventing atmospheric general -circulation models towards interactivity, extensibility and -composability - - - -https://orcid.org/0000-0002-3920-4356 - -Klöwer -Milan - -milank@mit.edu - - -* - - - -Gelbrecht -Maximilian - - - - - - -Hotta -Daisuke - - - - - - -Willmert -Justin - - - - - -Silvestri -Simone - - - - - -Wagner -Gregory L - - - - - -White -Alistair - - - - - - -Hatfield -Sam - - - - - -Meyer -David - - - - - -Kimpson -Tom - - - - - - -Constantinou -Navid C - - - - - -Hill -Chris - - - - - -Massachusetts Institute of Technology, Cambridge, MA, -USA - - - - -University of Oxford, UK - - - - -Technical University Munich, Germany - - - - -Potsdam Institute for Climate Impact Research, -Germany - - - - -Japan Meteorological Agency, Tsukuba, Japan - - - - -University of Reading, UK - - - - -University of Minnesota, Minneapolis, MN, USA - - - - -European Centre for Medium-Range Weather Forecasts, -Reading, UK - - - - -University of Melbourne, Melbourne, Australia - - - - -Australian National University, Canberra, -Australia - - - - -* E-mail: milank@mit.edu - - -14 -9 -2023 - -¿VOL? -¿ISSUE? -¿PAGE? - -Authors of papers retain copyright and release the -work under a Creative Commons Attribution 4.0 International License (CC -BY 4.0) -2022 -The article authors - -Authors of papers retain copyright and release the work under -a Creative Commons Attribution 4.0 International License (CC BY -4.0) - - - -Julia -weather -climate -general circulation model -spectral -spherical harmonic transform - - - - - - Summary -

SpeedyWeather.jl is a library to simulate and analyse the global - atmospheric circulation on the sphere. It implements several 2D and 3D - models to solve the primitive equations with and without humidity, the - shallow water equations - ([fig:swm]), or the - barotropic vorticity equations with spherical harmonics.

-

The user interface of SpeedyWeather.jl is heavily influenced by - Oceananigans.jl - (Ramadhan - et al., 2020). A monolithic interface is deliberately - avoided

-

To be extendible and composable, SpeedyWeather.jl relies on - multiple dispatch from the Julia programming language - (Bezanson - et al., 2017). Every model component is defined as a new type - SomeComponent <: AbstractComponent, - i.e. subtype of an abstract super type - AbstractComponent. Extending SpeedyWeather.jl - can therefore easily achieved by defining a new - OtherComponent <: AbstractComponent

-

The dynamical core of SpeedyWeather.jl uses established numerics - (Bourke, - 1972; - Hoskins - & Simmons, 1975; - Simmons - et al., 1978; - Simmons - & Burridge, 1981), widely adapted in numerical weather - prediction. It is based on the spherical harmonic transform with a - leapfrog-based semi-implicit time integration - (Hoskins - & Simmons, 1975) and a Robert-Asselin-Williams filter - (Amezcua - et al., 2011; - Williams, - 2011). The spherical harmonic transform is grid-flexible. Any - iso-latitude ring-based grid can be used and new grids can be - externally defined and passed on as argument. Many grids are already - implemented: The conventional Gaussian grid, a regular - longitude-latitude grid, the octahedral Gaussian grid - (Malardel - et al., 2016), the octahedral Clenshaw-Curtis grid - (Hotta - & Ujiie, 2018), and the HEALPix grid - (Górski - et al., 2005). Both SpeedyWeather.jl and its spherical harmonic - transform are also number format-flexible. 32-bit single-precision - floating-point numbers (Float32) are the default as adapted by other - modelling efforts - (Váňa - et al., 2017), but Float64 and other custom number formats can - be used with a single code basis. Julia will compile to the choice of - the number format and grid (and other model components) - just-in-time.

-
- - Statement of need -

Most weather and climate models are written in Fortran and have - been developed over decades. From this tradition follows a specific - programming style and associated user interface. SpeedyWeather.jl is a - fresh approach to atmospheric models that have been very influential - in many areas of scientific and high-performance computing as well as - climate change mitigation and adaptation.

- -

Shallow water simulation with SpeedyWeather.jl. Relative - vorticity with a spectral resolution of T1023 (about 20km) simulated - in Float32 on an octahedral Clenshaw-Curtis grid - (Hotta - & Ujiie, 2018). Relative vorticity is visualised with - Matplotlib - (Hunter, - 2007) and Cartopy - (Met - Office, 2010 - 2015) using a transparent-to-white colormap to - mimic the appearance of clouds. Underlain is NASA’s blue marble from - June 2004. -

- -
-
- - Acknowledgements -

We acknowledge contributions from Mosè Giordano, Valentin Churavy - and Pietro Monticone who have also committed to the SpeedyWeather.jl - repository, and the wider Julia community help and support. We - gratefully acknowledge funding from the National Science Foundation - (…) and the European Research Council under the European Union’s - Horizon 2020 research and innovation programme for the ITHACA grant - (no. 741112).

-
- - - - - - - AmezcuaJavier - KalnayEugenia - WilliamsPaul D. - - The Effects of the RAW Filter on the Climatology and Forecast Skill of the SPEEDY Model - Monthly Weather Review - American Meteorological Society - 201102 - 20230606 - 139 - 2 - 1520-0493 - 10.1175/2010MWR3530.1 - 608 - 619 - - - - - - BezansonJeff. - EdelmanAlan. - KarpinskiStefan. - ShahViral B. - - Julia: A Fresh Approach to Numerical Computing - SIAM Review - Society for Industrial and Applied Mathematics - 201701 - 20200225 - 59 - 1 - 0036-1445 - 10.1137/141000671 - 65 - 98 - - - - - - BourkeWilliam - - An Efficient, One-Level, Primitive-Equation Spectral Model - Monthly Weather Review - 197209 - 20220107 - 100 - 9 - 0027-0644 - 10.1175/1520-0493(1972)100<0683:AEOPSM>2.3.CO;2 - 683 - 689 - - - - - - Met Office - - Cartopy: A cartographic python library with a matplotlib interface - Exeter, Devon - https://scitools.org.uk/cartopy - - - - - - GórskiK. M. - HivonE. - BandayA. J. - WandeltB. D. - HansenF. K. - ReineckeM. - BartelmannM. - - HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere - The Astrophysical Journal - IOP Publishing - 200504 - 20230914 - 622 - 2 - 0004-637X - 10.1086/427976 - 759 - - - - - - - HoskinsB. J. - SimmonsA. J. - - A multi-layer spectral model and the semi-implicit method - Quarterly Journal of the Royal Meteorological Society - 1975 - 20230303 - 101 - 429 - 1477-870X - 10.1002/qj.49710142918 - 637 - 655 - - - - - - HottaDaisuke - UjiieMasashi - - A nestable, multigrid-friendly grid on a sphere for global spectral models based on Clenshaw quadrature - Quarterly Journal of the Royal Meteorological Society - 2018 - 20221208 - 144 - 714 - 1477-870X - 10.1002/qj.3282 - 1382 - 1397 - - - - - - HunterJohn D. - - Matplotlib: A 2D Graphics Environment - Computing in Science & Engineering - 200705 - 9 - 3 - 1558-366X - 10.1109/MCSE.2007.55 - 90 - 95 - - - - - - MalardelSylvie - WediNils - DeconinckNils - DiamantakisMichail - KuehnleinChristian - MozdzynskiGeorge - HamrudMats - SmolarkiewiczPiotr - - A new grid for the IFS - ECMWF Newsletter - https://www.ecmwf.int/node/15041 - 2016 - - - - - - RamadhanAli - WagnerGregory LeClaire - HillChris - CampinJean-Michel - ChuravyValentin - BesardTim - SouzaAndre - EdelmanAlan - FerrariRaffaele - MarshallJohn - - Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs - Journal of Open Source Software - 202009 - 20230914 - 5 - 53 - 2475-9066 - 10.21105/joss.02018 - 2018 - - - - - - - SimmonsA. J. - HoskinsB. J. - BurridgeD. M. - - Stability of the Semi-Implicit Method of Time Integration - Monthly Weather Review - American Meteorological Society - 197803 - 20230307 - 106 - 3 - 1520-0493 - 10.1175/1520-0493(1978)106<0405:SOTSIM>2.0.CO;2 - 405 - 412 - - - - - - SimmonsA. J. - BurridgeD. M. - - An Energy and Angular-Momentum Conserving Vertical Finite-Difference Scheme and Hybrid Vertical Coordinates - Monthly Weather Review - American Meteorological Society - 198104 - 20230307 - 109 - 4 - 1520-0493 - 10.1175/1520-0493(1981)109<0758:AEAAMC>2.0.CO;2 - 758 - 766 - - - - - - VáňaFilip - DübenPeter - LangSimon - PalmerTim - LeutbecherMartin - SalmondDeborah - CarverGlenn - - Single Precision in Weather Forecasting Models: An Evaluation with the IFS - Monthly Weather Review - 201702 - 20200225 - 145 - 2 - 0027-0644 - 10.1175/MWR-D-16-0228.1 - 495 - 502 - - - - - - WilliamsPaul D. - - The RAW Filter: An Improvement to the Robert in Semi-Implicit Integrations - Monthly Weather Review - 201106 - 20211217 - 139 - 6 - 0027-0644 - 10.1175/2010MWR3601.1 - 1996 - 2007 - - - - -
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Note, this should be the same directory as the input # paper.md path: docs/joss/paper.pdf + # These lines have been added following + # https://github.com/openjournals/openjournals-draft-action/issues/15 + - name: save pdf to repo + uses: stefanzweifel/git-auto-commit-action@v4 + with: + commit_message: Saved new PDF of paper From 9bfea3da2a45818334219283af0ac0a580f3ccad Mon Sep 17 00:00:00 2001 From: Milan Date: Fri, 15 Sep 2023 16:13:36 -0400 Subject: [PATCH 05/86] first paper draft finished --- .gitignore | 3 +- docs/joss/paper.bib | 48 +++++++++++-------- docs/joss/paper.md | 100 +++++++++++++++++++++++++++++++--------- docs/joss/primitive.jpg | Bin 0 -> 288095 bytes 4 files changed, 108 insertions(+), 43 deletions(-) create mode 100644 docs/joss/primitive.jpg diff --git a/.gitignore b/.gitignore index 7213efb96..94406f4f6 100644 --- a/.gitignore +++ b/.gitignore @@ -39,5 +39,4 @@ run_*/ # JOSS paper docs/joss/media -docs/joss/paper.jats -docs/joss/paper.pdf \ No newline at end of file +docs/joss/paper.jats \ No newline at end of file diff --git a/docs/joss/paper.bib b/docs/joss/paper.bib index a12ec1638..2e185a6aa 100644 --- a/docs/joss/paper.bib +++ b/docs/joss/paper.bib @@ -312,24 +312,6 @@ @article{Rasp2018 file = {/Users/milan/Zotero/storage/4FW52IRQ/9684.html} } -@article{Schneider2017, - title = {Earth {{System Modeling}} 2.0: {{A Blueprint}} for {{Models That Learn From Observations}} and {{Targeted High-Resolution Simulations}}}, - shorttitle = {Earth {{System Modeling}} 2.0}, - author = {Schneider, Tapio and Lan, Shiwei and Stuart, Andrew and Teixeira, Jo{\~a}o}, - year = {2017}, - journal = {Geophysical Research Letters}, - volume = {44}, - number = {24}, - pages = {12,396--12,417}, - issn = {1944-8007}, - doi = {10.1002/2017GL076101}, - urldate = {2022-10-21}, - abstract = {Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.}, - langid = {english}, - keywords = {data assimilation,Earth system models,Kalman inversion,machine learning,Markov chain Monte Carlo,parameterizations}, - file = {/Users/milan/Zotero/storage/79YWM78D/Schneider et al. - 2017 - Earth System Modeling 2.0 A Blueprint for Models .pdf;/Users/milan/Zotero/storage/SL4Z8NTA/2017GL076101.html} -} - @article{Schneider2023, title = {Harnessing {{AI}} and Computing to Advance Climate Modelling and Prediction}, author = {Schneider, Tapio and Behera, Swadhin and Boccaletti, Giulio and Deser, Clara and Emanuel, Kerry and Ferrari, Raffaele and Leung, L. Ruby and Lin, Ning and M{\"u}ller, Thomas and Navarra, Antonio and Ndiaye, Ousmane and Stuart, Andrew and Tribbia, Joseph and Yamagata, Toshio}, @@ -422,3 +404,33 @@ @article{Williams2011 langid = {english}, file = {/Users/milan/Zotero/storage/YS2LGST8/Williams - 2011 - The RAW Filter An Improvement to the Robert–Assel.pdf} } + +@misc{Innes2019, + title = {A {{Differentiable Programming System}} to {{Bridge Machine Learning}} and {{Scientific Computing}}}, + author = {Innes, Mike and Edelman, Alan and Fischer, Keno and Rackauckas, Chris and Saba, Elliot and Shah, Viral B. and Tebbutt, Will}, + year = {2019}, + month = jul, + number = {arXiv:1907.07587}, + eprint = {1907.07587}, + primaryclass = {cs}, + publisher = {{arXiv}}, + doi = {10.48550/arXiv.1907.07587}, + urldate = {2023-09-15}, + abstract = {Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large amounts of data. At the same time, machine learning models are becoming increasingly sophisticated and exhibit many features often seen in scientific computing, stressing the capabilities of machine learning frameworks. Just as the disciplines of scientific computing and machine learning have shared common underlying infrastructure in the form of numerical linear algebra, we now have the opportunity to further share new computational infrastructure, and thus ideas, in the form of Differentiable Programming. We describe Zygote, a Differentiable Programming system that is able to take gradients of general program structures. We implement this system in the Julia programming language. Our system supports almost all language constructs (control flow, recursion, mutation, etc.) and compiles high-performance code without requiring any user intervention or refactoring to stage computations. This enables an expressive programming model for deep learning, but more importantly, it enables us to incorporate a large ecosystem of libraries in our models in a straightforward way. We discuss our approach to automatic differentiation, including its support for advanced techniques such as mixed-mode, complex and checkpointed differentiation, and present several examples of differentiating programs.}, + archiveprefix = {arxiv}, + keywords = {Computer Science - Machine Learning,Computer Science - Programming Languages}, + file = {/Users/milan/Zotero/storage/VY5339JF/Innes et al. - 2019 - A Differentiable Programming System to Bridge Mach.pdf;/Users/milan/Zotero/storage/CZ4BXQCY/1907.html} +} + +@inproceedings{Moses2020, + title = {Instead of {{Rewriting Foreign Code}} for {{Machine Learning}}, {{Automatically Synthesize Fast Gradients}}}, + booktitle = {Advances in {{Neural Information Processing Systems}}}, + author = {Moses, William and Churavy, Valentin}, + year = {2020}, + volume = {33}, + pages = {12472--12485}, + publisher = {{Curran Associates, Inc.}}, + urldate = {2023-09-15}, + abstract = {Applying differentiable programming techniques and machine learning algorithms to foreign programs requires developers to either rewrite their code in a machine learning framework, or otherwise provide derivatives of the foreign code. This paper presents Enzyme, a high-performance automatic differentiation (AD) compiler plugin for the LLVM compiler framework capable of synthesizing gradients of statically analyzable programs expressed in the LLVM intermediate representation (IR). Enzyme synthesizes gradients for programs written in any language whose compiler targets LLVM IR including C, C++, Fortran, Julia, Rust, Swift, MLIR, etc., thereby providing native AD capabilities in these languages. Unlike traditional source-to-source and operator-overloading tools, Enzyme performs AD on optimized IR. On a machine-learning focused benchmark suite including Microsoft's ADBench, AD on optimized IR achieves a geometric mean speedup of 4.2 times over AD on IR before optimization allowing Enzyme to achieve state-of-the-art performance. Packaging Enzyme for PyTorch and TensorFlow provides convenient access to gradients of foreign code with state-of-the-art performance, enabling foreign code to be directly incorporated into existing machine learning workflows.}, + file = {/Users/milan/Zotero/storage/Y9ZTEWXC/Moses and Churavy - 2020 - Instead of Rewriting Foreign Code for Machine Lear.pdf} +} diff --git a/docs/joss/paper.md b/docs/joss/paper.md index ab95ad5e1..92c0c846a 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -66,7 +66,7 @@ affiliations: index: 7 - name: European Centre for Medium-Range Weather Forecasts, Reading, UK index: 8 - - name: University of Melbourne, Melbourne, Australia + - name: University of Melbourne, Australia index: 9 - name: Australian National University, Canberra, Australia index: 10 @@ -76,23 +76,60 @@ bibliography: paper.bib --- + # Summary SpeedyWeather.jl is a library to simulate and analyse the global atmospheric circulation on the sphere. It implements several 2D and 3D -models to solve the primitive equations with and without humidity, +models to solve the primitive equations with and without humidity (\autoref{fig:primitive}), the shallow water equations (\autoref{fig:swm}), or the barotropic vorticity equations -with spherical harmonics. +with spherical harmonics. Several simple parameterizations for unresolved physical processes +such as precipitation or the boundary layer are implemented, and new ones can +be externally defined and passed as an argument to the model constructor. +SpeedyWeather.jl is an intermediate-complexity general circulation model [@Kucharski2013] +and research playground with an (almost) everything-flexible attitude. +It can be thought of as a conceptual reinvention of the Fortran SPEEDY model [@Molteni2003] +in the Julia programming language [@Bezanson2017]. + +SpeedyWeather.jl internally uses three sub-modules `SpeedyTransforms`, `RingGrids`, and +`LowerTriangularMatrices` to perform spherical harmonic transforms and interpolations +between various grids and the spectral space. `RingGrids` discretize the sphere +on iso-latitude rings and the spectral space is defined by the `LowerTriangularMatrices` +of the spherical harmonic coefficients. These three modules are independently usable +and therefore make SpeedyWeather.jl, beyond its main purpose of simulating the weather, +also a library for the analysis of gridded data on the sphere. +Running and analysing simulations can interactively combined, enhancing user +experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by -Oceananigans.jl [@Ramadhan2020]. A monolithic interface is deliberately avoided - -To be extendible and composable, SpeedyWeather.jl relies on multiple dispatch -from the Julia programming language [@Bezanson2017]. Every model component -is defined as a new type `SomeComponent <: AbstractComponent`, i.e. subtype of -an abstract super type `AbstractComponent`. -Extending SpeedyWeather.jl can therefore easily achieved by defining a new -`OtherComponent <: AbstractComponent` +the Julia ocean model Oceananigans.jl [@Ramadhan2020]. +A monolithic interface is deliberately avoided, +instead, a model is created bottom-up by first defining the discretization +and any non-default model components with its respective parameters. +All components are then collected into a single model object, which, once +initialized, returns a simulation object that contains the entire model state, +work arrays and parameters, that can be run, analysed or changed. +While these steps can be written into a script for reproducibility, +the same steps can be executed and interacted with one-by-one in +Julia's read-evaluate-print loop (REPL). We thereby reach an interactivity +far beyond a monolithic interface that is limited to the options provided. + +To be extendible and composable with new +model components, SpeedyWeather.jl relies on Julia's multiple dispatch +programming paradigm [@Bezanson2017]. Every model component +is defined as a new type. For example, to define a new way how to calculate +the precipitation due to the physical process of large-scale condensation, +one would define `MyCondensation` as a new subtype of `AbstractCondensation`. +One then only needs to extend the `initialize!` and `condensation!` +functions for this new type. Passing on `condensation = MyCondensation()` +to the model constructor then implements this new model component without +the need to branch off or overwrite existing model components. +Conceptually similar scientific modelling paradigms have been very successful +in the Python-based generic partial differential equation solver Dedalus [@Burns2020] +and the Julia ocean model Oceananigans.jl [@Ramadhan2020]. + +![Surface temperature simulated with the primitive equation model in SpeedyWeather.jl. +(Figure will be updated) \label{fig:primitive}](primitive.jpg) The dynamical core of SpeedyWeather.jl uses established numerics [@Bourke1972; @Hoskins1975; @Simmons1978; @Simmons1981], @@ -107,22 +144,39 @@ the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. Both SpeedyWeather.jl and its spherical harmonic transform are also number format-flexible. 32-bit single-precision floating-point numbers -(Float32) are the default as adapted by other modelling efforts [@Vana2017], +(Float32) are the default as adapted by other modelling efforts [@Vana2017, @Nakano2018], but Float64 and other custom number formats can be used with a single -code basis. Julia will compile to the choice of the number format -and grid (and other model components) just-in-time. +code basis. Julia will compile to the choice of the number format, the grid, +and and other model components just-in-time. A simple parallelisation +across vertical layers is supported with Julia's multi threading. # Statement of need -Most weather and climate models are written in Fortran and have been developed over -decades. From this tradition follows a specific programming style and -associated user interface. SpeedyWeather.jl is a fresh approach to atmospheric +SpeedyWeather.jl is a fresh approach to atmospheric models that have been very influential in many areas of scientific and high-performance computing as well as climate change mitigation and adaptation. - -![Shallow water simulation with SpeedyWeather.jl. -Relative vorticity with a spectral resolution of T1023 (about 20km) simulated -in Float32 on an octahedral Clenshaw-Curtis grid [@Hotta2018]. Relative vorticity +Most weather, ocean and climate models are written in Fortran and have been developed over +decades. From this tradition follows a specific programming style and +associated user interface. Running a simulation in Fortran and analysing the +data in Python makes it virtually impossible to interact with various model +components interactively. Furthermore, data-driven climate modelling +[@Rasp2018,Schneider2023], which replaces existing model components with machine learning +is difficult due to the lack of established deep learning frameworks in Fortran [@Innes2019]. +Let alone online learning, which trains a neural network-based component together +with the rest of the model, accounting for interactions between components. +Gradients, necessary to optimize training, can be computed +with automatic differentiation [@Moses2020], but only if differentiable functions +in a coherent language framework are provided. + +We hope to provide with SpeedyWeather.jl a first test platform for data-driven +atmospheric modelling and in general an interactive model that makes difficult +problems easy to simulate. Climate models that are user-friendly, trainable, +but also easily extensible will suddenly make many complex +research ideas possible. + +![Relative vorticity simulated with the shallow water model in SpeedyWeather.jl. +The simulation used a spectral resolution of T1023 (about 20km) and Float32 +arithmetic on an octahedral Clenshaw-Curtis grid [@Hotta2018]. Relative vorticity is visualised with Matplotlib [@Hunter2007] and Cartopy [@Cartopy] using a transparent-to-white colormap to mimic the appearance of clouds. Underlain is NASA's blue marble from June 2004. \label{fig:swm}](swm.png) @@ -131,8 +185,8 @@ NASA's blue marble from June 2004. \label{fig:swm}](swm.png) We acknowledge contributions from Mosè Giordano, Valentin Churavy and Pietro Monticone who have also committed to the SpeedyWeather.jl repository, and the wider Julia community -help and support. We gratefully acknowledge funding from the -National Science Foundation (...) and the European Research Council +for help and support. We gratefully acknowledge funding from the +National Science Foundation (Chris please add) and the European Research Council under the European Union’s Horizon 2020 research and innovation programme for the ITHACA grant (no. 741112). diff --git a/docs/joss/primitive.jpg b/docs/joss/primitive.jpg new file mode 100644 index 0000000000000000000000000000000000000000..0d68a1365d802356a3978bf85ade76a273f4ab5e GIT binary patch literal 288095 zcmeFZby!tjyDq!{0Ric5>6Y$TBHhBGL6L405Tp_5?iA_n?vU>8mPSfinr|-s)%)&i zU*Gw@>-@3zIeRIK>6&AVC-3`t)|hkpF#GTggdr;_BME|m0fAtEKcI&NkQfLK7W#s| z!vU{H2#=tz#|Q}U2uP2Sk&zxFAt66Oe}asHhJu8IiiwJbj)8%Rf&2su8w&#)IL3f3 z0t1~1_vkS&5d#GY1^D#;r3?>K`69x_w=Ajcr4(JIF^Xmor;{^i? z_Xr*V@i7uI3NWA=0|X1mhJ6GF5C7;9FxnkB4|;?Nk43>Qih!-Gk4R~Y!{HT~{+Q}T zc^j_E*bz0Sf!!x0WITKVLLwSkI(i01E^Z!PK7Ii)aS2H&X&G6Fs+zinrk1v$k+F%X znYo4idk4o4PR=ggKE8hb0f9kL(J`@c@d=4Z8JStxIk|cH1r?Q5)it$s^$qPEon75M zy?y=T6O&WZGqZE^t842Un_JsE-*=BsPS4ISeqLT(L+yeA!TmN1c>itKzu5&i0S5LF 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z)3~~rcao~*H9N{SMqFBYQFF${!F|R3a(CH0pI_1B=bF;8NhkRJggF0%#O*GZPUe@@ z%!_Ipvu8iI$s<{G=by4N>B>RNgKwRxOf6CT9%E^;iA)=?`lNKqg3`3Br|!5OQoQs% z&rMqxYd$5!^;FB~7ojWk@^qN;!f)o;>l&o3v|lwaWK}vV^CE-AajNmnEdE|Gyj6NL z);IP$ryb61R+mbG6{Qmk4A|!iSN&*v=@na+IDE#|=gzH$X-7<=OwPUS`@S}% Date: Sat, 16 Sep 2023 09:23:18 -0400 Subject: [PATCH 07/86] joss paper: affiliations updated Co-authored-by: Daisuke Hotta <88590419+hottad@users.noreply.github.com> Co-authored-by: Navid C. Constantinou --- docs/joss/paper.md | 25 +++++++++++++------------ 1 file changed, 13 insertions(+), 12 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 92c0c846a..d83444fe6 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -20,31 +20,34 @@ authors: affiliation: "3,4" - name: Daisuke Hotta - affiliation: "5,6" + orcid: 0000-0003-2287-0608 + affiliation: "5,7" - name: Justin Willmert - affiliation: 7 + affiliation: 6 - name: Simone Silvestri affiliation: 1 - name: Gregory L Wagner + orcid: 0000-0001-5317-2445 affiliation: 1 - name: Alistair White affiliation: "3,4" - name: Sam Hatfield - affiliation: 8 + affiliation: 7 - name: David Meyer - affiliation: 8 + affiliation: 7 - name: Tom Kimpson - affiliation: "2,9" + affiliation: "2,8" - name: Navid C Constantinou - affiliation: 10 + orcid: 0000-0002-8149-4094 + affiliation: 9 - name: Chris Hill affiliation: 1 @@ -60,16 +63,14 @@ affiliations: index: 4 - name: Japan Meteorological Agency, Tsukuba, Japan 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z$GgqEHxBB19}PzXOTqIcfS_i-V=faF$$5<=$q5lHUI*p5xX?ip~9A4ZCU zt7^Prr3_>@(*?(w?pic5;lvJ@D4l_cb(OwWAG4Q29&2qvb#YP}G#qBd#wD=YY?Lb8 zGdA&faHR0yXmT52qAs+2mV#0^D&OX&54JOD%zg8{c{l#0{Ls_qqM-O&#~J@zDQ1Nv z;bhmIk3grA^}<=*>r-5SwYl?Ao^Vzihm(&`T9nAZ=Q!}(POWLL^-I%k#~wOD*H@iN z&*19)(GvIGJ-Mf>{dY1+oISP(N82Tn-D^fkvXbJdm7%8>jvucLH=bZI#a2R<&}pUc zTk%fyB^Yli@f7fUof{qZIi*^C8y&}`fi|05b!ts~YK#l23$!y-p+$r?n-jU*bLyPS z?`!Asj)uS>&Cqh@yb39otI~?dKBS|M1^Hzhm@HCDWRJXx+PStyrEwX&^J2t zdk7kvC1Z#FL&Yi%4z5t~pO+MijJ>%7wDf0Bv&j68zzT?qNpN# zbFguUaX{ai5@I|Ol43&te^n5E*U|rLeZq0_LSxqEKzuN-yqYNS;02*6L=M3{XC#`A zEP!Ij*)xE4jc$ks-UhXWPkt-2Vi1gycvy_PEa=!(D#jiC@ML5d2va4_Pri> z-6>M>=`ttFi~Z~wJdpY&6@7h@J0JB`H0J=j(*S%ly1uQma`iP|sJSBcnj^Q!F4=i3#QS ziVvQ+S1xN_%3j(M#gf;Y)0HNkjg Date: Sat, 16 Sep 2023 09:41:28 -0400 Subject: [PATCH 09/86] JOSS paper: further comments accepted Co-authored-by: Daisuke Hotta <88590419+hottad@users.noreply.github.com> Co-authored-by: Navid C. Constantinou --- docs/joss/paper.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index d83444fe6..337e6ecb8 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -99,7 +99,7 @@ on iso-latitude rings and the spectral space is defined by the `LowerTriangularM of the spherical harmonic coefficients. These three modules are independently usable and therefore make SpeedyWeather.jl, beyond its main purpose of simulating the weather, also a library for the analysis of gridded data on the sphere. -Running and analysing simulations can interactively combined, enhancing user +Running and analysing simulations can be interactively combined, enhancing user experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by @@ -115,7 +115,7 @@ the same steps can be executed and interacted with one-by-one in Julia's read-evaluate-print loop (REPL). We thereby reach an interactivity far beyond a monolithic interface that is limited to the options provided. -To be extendible and composable with new +To be extensible and composable with new model components, SpeedyWeather.jl relies on Julia's multiple dispatch programming paradigm [@Bezanson2017]. Every model component is defined as a new type. For example, to define a new way how to calculate @@ -139,7 +139,7 @@ harmonic transform with a leapfrog-based semi-implicit time integration [@Hoskin and a Robert-Asselin-Williams filter [@Williams2011; @Amezcua2011]. The spherical harmonic transform is grid-flexible. Any iso-latitude ring-based grid can be used and new grids can be externally defined and passed on -as argument. Many grids are already implemented: The conventional +as argument. Many grids are already implemented: the conventional Gaussian grid, a regular longitude-latitude grid, the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. @@ -184,7 +184,7 @@ NASA's blue marble from June 2004. \label{fig:swm}](swm.png) # Acknowledgements -We acknowledge contributions from Mosè Giordano, Valentin Churavy and Pietro Monticone +We acknowledge contributions from Mosè Giordano, Valentin Churavy, and Pietro Monticone who have also committed to the SpeedyWeather.jl repository, and the wider Julia community for help and support. 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authors: - name: Daisuke Hotta orcid: 0000-0003-2287-0608 - affiliation: "5,7" + affiliation: "5,6" - name: Justin Willmert - affiliation: 6 + affiliation: 7 - name: Simone Silvestri affiliation: 1 @@ -37,10 +37,10 @@ authors: affiliation: "3,4" - name: Sam Hatfield - affiliation: 7 + affiliation: 6 - name: David Meyer - affiliation: 7 + affiliation: 6 - name: Tom Kimpson affiliation: "2,8" @@ -63,9 +63,9 @@ affiliations: index: 4 - name: Japan Meteorological Agency, Tsukuba, Japan index: 5 - - name: University of Minnesota, Minneapolis, MN, USA - index: 6 - name: European Centre for Medium-Range Weather Forecasts, Reading, UK + index: 6 + - name: University of Minnesota, Minneapolis, MN, USA index: 7 - name: University of Melbourne, Australia index: 8 @@ -104,8 +104,10 @@ experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by the Julia ocean model Oceananigans.jl [@Ramadhan2020]. -A monolithic interface is deliberately avoided, -instead, a model is created bottom-up by first defining the discretization +A monolithic interface based on parameter files is avoided in favor of a +library-style interface in which users write code to run models rather than +merely supplying parameters and input arrays. +A model is created bottom-up by first defining the discretization and any non-default model components with its respective parameters. All components are then collected into a single model object, which, once initialized, returns a simulation object that contains the entire model state, @@ -143,7 +145,7 @@ as argument. Many grids are already implemented: the conventional Gaussian grid, a regular longitude-latitude grid, the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. -Both SpeedyWeather.jl and its spherical harmonic transform are also +Both SpeedyWeather.jl and its spherical harmonic transform SpeedyTransforms are also number format-flexible. 32-bit single-precision floating-point numbers (Float32) are the default as adapted by other modelling efforts [@Vana2017, @Nakano2018], but Float64 and other custom number formats can be used with a single From 0ebc3aa843c63ad6e49831514d7c650d50520c38 Mon Sep 17 00:00:00 2001 From: milankl Date: Sat, 16 Sep 2023 13:49:47 +0000 Subject: [PATCH 12/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1337560 -> 1337732 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index 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=?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Mon, 18 Sep 2023 11:27:18 -0400 Subject: [PATCH 13/86] joss paper: Sam's suggestions accepted Co-authored-by: Sam Hatfield --- docs/joss/paper.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 29ee95617..6d49f2914 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -136,18 +136,18 @@ and the Julia ocean model Oceananigans.jl [@Ramadhan2020]. The dynamical core of SpeedyWeather.jl uses established numerics [@Bourke1972; @Hoskins1975; @Simmons1978; @Simmons1981], -widely adapted in numerical weather prediction. It is based on the spherical +widely adopted in numerical weather prediction. It is based on the spherical harmonic transform with a leapfrog-based semi-implicit time integration [@Hoskins1975] and a Robert-Asselin-Williams filter [@Williams2011; @Amezcua2011]. The spherical harmonic transform is grid-flexible. Any iso-latitude ring-based -grid can be used and new grids can be externally defined and passed on -as argument. Many grids are already implemented: the conventional +grid can be used and new grids can be externally defined and passed in +as an argument. Many grids are already implemented: the conventional Gaussian grid, a regular longitude-latitude grid, the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. Both SpeedyWeather.jl and its spherical harmonic transform SpeedyTransforms are also number format-flexible. 32-bit single-precision floating-point numbers -(Float32) are the default as adapted by other modelling efforts [@Vana2017, @Nakano2018], +(Float32) are the default as adopted by other modelling efforts [@Vana2017, @Nakano2018], but Float64 and other custom number formats can be used with a single code basis. Julia will compile to the choice of the number format, the grid, and and other model components just-in-time. A simple parallelisation From 7ef34cef08e29c3eced518d76d3410bc831295e0 Mon Sep 17 00:00:00 2001 From: milankl Date: Mon, 18 Sep 2023 15:28:18 +0000 Subject: [PATCH 14/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1337732 -> 1337731 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index 7ad4d05f5a8ce1a5115468c66e098f6268b5e54a..3a8c5be351be84528628f952b8e31dbbb394f88d 100644 GIT binary patch delta 8241 zcmajjRZJW}w*X+QIFv<;7I!Gn-Nk*eV#S@J#hpU2F7ECWFV5nN7bxy7OL2E=aV1fM^V-|-hd z_Y2)V{yRy7LHSzTC}lKxvpb&6JtfwlS>K>(>cVU>L%BlFVZJ9~|8D;s_4jhGIgOn( z#jspwTohLT76+2t)V@+vda8dwND+BpiL>o(L@CmLZF?HYg_h3Tt+kx3IbM^5)c?CA z4J7v7)*u|RbHd3ilusz$3z_*x98D@IxUIRXba^*31dZc&u4HC6?{a)e3$xe^i~ag(i(skq9AZKDG$f~X zif{qtKvPmvi?MsUoP@*=z8Y}(wTz!M(LIiU?vhB@2I;jLfmy?>KzOItsmjTWJ}N6O zQlBrsHCv#f{A+=wew-{;DGj5nezfFK^#$Bt^lSDcP7W!0_*qt7vgKIQDMLlO-5DQnr$U~V|;-8f{XS9{2L$!TGZRJ$S`^yGh z?3F}ydk5D@y@=?TIzFPF6KJcUPH5JH>bLY4K)mthbNgcQOlt`_kFjnmu>;B)e|Ngs 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We gratefully acknowledge funding from the -National Science Foundation (Chris please add) and the European Research Council -under the European Union’s Horizon 2020 research and innovation programme -for the ITHACA grant (no. 741112). +for help and support. MK acknowledges funding from the +National Science Foundation (Chris please add). 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17/86] joss paper: max easy running Co-authored-by: Maximilian Gelbrecht --- docs/joss/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index a667e30f1..862a81665 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -115,7 +115,7 @@ work arrays and parameters, that can be run, analysed or changed. While these steps can be written into a script for reproducibility, the same steps can be executed and interacted with one-by-one in Julia's read-evaluate-print loop (REPL). We thereby reach an interactivity -far beyond a monolithic interface that is limited to the options provided. +far beyond a monolithic interface that is limited to the options provided. At the same time, sensible default arguments enable even inexperienced users, to run simulations in just a few lines of code. 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zqZp4xly8yLqLAJy5@Dv`k@Z9SV{VmO$08-}P+iY!VIn2Om$okr4wP*CBH0n4ehDB= z-;u~nd#!Pxn~atbaDY7O--qeR8y)+Upgj^qsPL02W&PqE5Vs%k+H=^uYu3oMr>AU7 XwjuI}YzG=3KnMf^aB?a`Q~>`4D@ywX From e9ac229ee7d7df69fc74967ec9f2c0b4b32cbdeb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Tue, 19 Sep 2023 15:41:34 -0400 Subject: [PATCH 19/86] joss paper: fix some citations --- docs/joss/paper.bib | 16 ++++++++++++++++ docs/joss/paper.md | 13 +++++++++---- 2 files changed, 25 insertions(+), 4 deletions(-) diff --git a/docs/joss/paper.bib b/docs/joss/paper.bib index 2e185a6aa..e4f44df1e 100644 --- a/docs/joss/paper.bib +++ b/docs/joss/paper.bib @@ -196,6 +196,22 @@ @article{Jablonowski2006 file = {/Users/milan/Zotero/storage/VH7SAZC2/Jablonowski and Williamson - 2006 - A baroclinic instability test case for atmospheric.pdf} } +@article{Klower2020, +author = {Klöwer, M. and Düben, P. D. and Palmer, T. N.}, +title = {Number Formats, Error Mitigation, and Scope for 16-Bit Arithmetics in Weather and Climate Modeling Analyzed With a Shallow Water Model}, +journal = {Journal of Advances in Modeling Earth Systems}, +volume = {12}, +number = {10}, +pages = {e2020MS002246}, +keywords = {Reduced precision, 16-bit arithmetic, climate models, rounding error, floating-point numbers, posit numbers}, +doi = {https://doi.org/10.1029/2020MS002246}, +url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020MS002246}, +eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2020MS002246}, +note = {e2020MS002246 10.1029/2020MS002246}, +abstract = {Abstract The need for high-precision calculations with 64-bit or 32-bit floating-point arithmetic for weather and climate models is questioned. Lower-precision numbers can accelerate simulations and are increasingly supported by modern computing hardware. This paper investigates the potential of 16-bit arithmetic when applied within a shallow water model that serves as a medium complexity weather or climate application. There are several 16-bit number formats that can potentially be used (IEEE half precision, BFloat16, posits, integer, and fixed-point). It is evident that a simple change to 16-bit arithmetic will not be possible for complex weather and climate applications as it will degrade model results by intolerable rounding errors that cause a stalling of model dynamics or model instabilities. However, if the posit number format is used as an alternative to the standard floating-point numbers, the model degradation can be significantly reduced. Furthermore, mitigation methods, such as rescaling, reordering, and mixed precision, are available to make model simulations resilient against a precision reduction. If mitigation methods are applied, 16-bit floating-point arithmetic can be used successfully within the shallow water model. The results show the potential of 16-bit formats for at least parts of complex weather and climate models where rounding errors would be entirely masked by initial condition, model, or discretization error.}, +year = {2020} +} + @article{Klower2022, title = {Fluid {{Simulations Accelerated With}} 16 {{Bits}}: {{Approaching}} 4x {{Speedup}} on {{A64FX}} by {{Squeezing ShallowWaters}}.Jl {{Into Float16}}}, shorttitle = {Fluid {{Simulations Accelerated With}} 16 {{Bits}}}, diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 862a81665..6366ccb4d 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -115,7 +115,9 @@ work arrays and parameters, that can be run, analysed or changed. While these steps can be written into a script for reproducibility, the same steps can be executed and interacted with one-by-one in Julia's read-evaluate-print loop (REPL). We thereby reach an interactivity -far beyond a monolithic interface that is limited to the options provided. At the same time, sensible default arguments enable even inexperienced users, to run simulations in just a few lines of code. +far beyond a monolithic interface that is limited to the options provided. +At the same time, sensible default arguments enable even inexperienced users +to run simulations in just a few lines of code. To be extensible and composable with new model components, SpeedyWeather.jl relies on Julia's multiple dispatch @@ -147,11 +149,14 @@ the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. Both SpeedyWeather.jl and its spherical harmonic transform SpeedyTransforms are also number format-flexible. 32-bit single-precision floating-point numbers -(Float32) are the default as adopted by other modelling efforts [@Vana2017, @Nakano2018], +(Float32) are the default as adopted by other modelling efforts [@Vana2017; @Nakano2018], but Float64 and other custom number formats can be used with a single -code basis. Julia will compile to the choice of the number format, the grid, +code basis [@Klower2022; @Klower2020]. +Julia will compile to the choice of the number format, the grid, and and other model components just-in-time. A simple parallelisation across vertical layers is supported with Julia's multi threading. +Output is stored as NetCDF files using +[NCDatasets.jl](https://github.com/Alexander-Barth/NCDatasets.jl). # Statement of need @@ -163,7 +168,7 @@ decades. From this tradition follows a specific programming style and associated user interface. Running a simulation in Fortran and analysing the data in Python makes it virtually impossible to interact with various model components interactively. Furthermore, data-driven climate modelling -[@Rasp2018,Schneider2023], which replaces existing model components with machine learning +[@Rasp2018; @Schneider2023], which replaces existing model components with machine learning is difficult due to the lack of established deep learning frameworks in Fortran [@Innes2019]. Let alone online learning, which trains a neural network-based component together with the rest of the model, accounting for interactions between components. 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b/docs/joss/paper.md index 12082cd96..b3385ac2f 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -25,6 +25,7 @@ authors: affiliation: "5,6" - name: Justin Willmert + orcid: 0000-0002-6452-4693 affiliation: 7 - name: Simone Silvestri From 1e636df1bf10b2d8469b1d05d001f9049d2b5c93 Mon Sep 17 00:00:00 2001 From: milankl Date: Mon, 25 Sep 2023 19:03:37 +0000 Subject: [PATCH 24/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1341105 -> 1341192 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index 1ef22c35966e5701fc6b15c3191032c19ed7f87d..34c3083e8f2ddc2ebe383e758d94933b4079b8af 100644 GIT binary patch delta 14278 zcmaiabzD^4w>Lv~%nTjUokOQ|cZq~_r*tTTbW0z)5fG)3R1gvA25FHH=|(`%cMzX@ zpZojV`+5IZ=bXLQT6?YU+H38z_nfKQ(}~{KsXfOAi2#L6P*xOSei4Ak7Yv2(N%ki) zwATIjg?$s^*}@Z|E&WmzmhWyYyb|_RkMa${Qt)B>#Se22ESR$03tioS74+~e3Kezk z_ZGaqu(@aN;lF?UxOk5bzgQxr={!Ucev)EJjk=k7zIwR#34lM%;%peYcl@dDhJ0Rz 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z-i{aMo?ASG*?*{V&MU&nx7vw;0P3h;Wz?u zh*TV`J>f-ToO4B9TaEu9$-xe9$>|EN)%XrZGZ$eBdd6Yg4RTk)Bx#bUe*J>d zZcm4vBJtbo`#`AxAKzt5!&^vO*Q}0501vr0#o>6f=>moLT;Y@kbmC_F`6|TK%pvG$ zgYLSClK|GIX`_U!D_$!(6F*^Ue2gz?2iHX=BcFKG8K!pWYknUpz zUitAg^x-I4WPGnWSm|QvMKU;O!Z?WxXw){QqnKp(X_;5c{Ai{qdzBSCKjsO8-c;d8 z9|r~(ggp?kT}dDR2qTL-Rb~yv+h^&C`s|2DMRd%@ z_C`b+)Z?3YFL18bOB-^AJ1$)dnD$x%&}~1JNkV^K8>l3uLgk;ypbPjO^H2Up#-|bs z^OGXKillh0=IZy=P=1XuXe&j}#8Z5hniy8(7PK|^HfzI#(lPQT&3#PkkVe5SWqa{^ zq;ZUY<15J;Yio<&jj|}ZQ?HU)I|xr03amm^iMGkjZ+?Fl4- z!k0FDx259{U;|%f!XWsT3chm&@xlc@tnKOwUl=?OC4ox`V(SX;{oU#)-S3aZWaN2- zp1><97+yK01q68cc!h;zgoWkdMTSp+U-*f{{|^Kij)8%_fOJSae^(vD+^WX3JLTxv zG*f=^^=;oSLEMzETwIlxE>Jl7z4Y5LuNQYHp52XyB~97bAF*GwB<+mYcD=1IStecY zL>eKwu^W!UP=mmAMt!IEE+!4NIrXhX85g02dr`qYH*7WQ^={B+B_HBNa zTbI34OMj0&1s_J??a$9|lbZ)##E-1B$k(gj?G73lp!+vc3rI;oogGqSpN?;1N|oe From dc0f903e20528ce51013b2c34d7d23d19ad3d81d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Tue, 26 Sep 2023 18:31:32 -0400 Subject: [PATCH 25/86] JOSS paper: Alistair's suggestions Co-authored-by: Alistair White <59571934+white-alistair@users.noreply.github.com> Co-authored-by: dmey --- docs/joss/paper.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index b3385ac2f..1e202f3c4 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -36,13 +36,15 @@ authors: affiliation: 1 - name: Alistair White + - orcid: 0000-0003-3377-6852 affiliation: "3,4" - name: Sam Hatfield affiliation: 6 - name: David Meyer - affiliation: 6 + orcid: 0000-0002-7071-7547 + affiliation: "8,9" - name: Tom Kimpson affiliation: "2,8" @@ -82,7 +84,7 @@ bibliography: paper.bib # Summary -SpeedyWeather.jl is a library to simulate and analyse the global atmospheric +SpeedyWeather.jl is a library to simulate and analyze the global atmospheric circulation on the sphere. It implements several 2D and 3D models to solve the primitive equations with and without humidity (\autoref{fig:primitive}), the shallow water equations (\autoref{fig:swm}), or the barotropic vorticity equations @@ -110,8 +112,8 @@ A monolithic interface based on parameter files is avoided in favor of a library-style interface in which users write code to run models rather than merely supplying parameters and input arrays. A model is created bottom-up by first defining the discretization -and any non-default model components with its respective parameters. -All components are then collected into a single model object, which, once +and any non-default model components with their respective parameters. +All components are then collected into a single model object which, once initialized, returns a simulation object that contains the entire model state, work arrays and parameters, that can be run, analysed or changed. While these steps can be written into a script for reproducibility, @@ -185,7 +187,7 @@ but also easily extensible will suddenly make many complex research ideas possible. ![Relative vorticity simulated with the shallow water model in SpeedyWeather.jl. -The simulation used a spectral resolution of T1023 (about 20km) and Float32 +The simulation used a spectral resolution of T1023 (about 20 km) and Float32 arithmetic on an octahedral Clenshaw-Curtis grid [@Hotta2018]. Relative vorticity is visualised with Matplotlib [@Hunter2007] and Cartopy [@Cartopy] using a transparent-to-white colormap to mimic the appearance of clouds. 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27/86] JOSS paper: affils updated --- docs/joss/paper.md | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 1e202f3c4..39ba3f586 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -40,6 +40,7 @@ authors: affiliation: "3,4" - name: Sam Hatfield + orcid: 0000-0001-7235-6450 affiliation: 6 - name: David Meyer @@ -47,11 +48,12 @@ authors: affiliation: "8,9" - name: Tom Kimpson - affiliation: "2,8" + orcid: 0000-0002-6542-6032 + affiliation: "2,10" - name: Navid C Constantinou orcid: 0000-0002-8149-4094 - affiliation: 9 + affiliation: 11 - name: Chris Hill affiliation: 1 @@ -71,10 +73,14 @@ affiliations: index: 6 - name: University of Minnesota, Minneapolis, MN, USA index: 7 - - name: University of Melbourne, Australia + - name: Imperial College London, UK index: 8 - - name: Australian National University, Canberra, Australia + - name: European Centre for Medium-Range Weather Forecasts, Bonn, Germany index: 9 + - name: University of Melbourne, Australia + index: 10 + - name: Australian National University, Canberra, Australia + index: 11 date: 14 September 2023 bibliography: paper.bib From 78d3a46d1c34c9f45650b88b59f10c2dc38a45f2 Mon Sep 17 00:00:00 2001 From: milankl Date: Tue, 26 Sep 2023 22:45:04 +0000 Subject: [PATCH 28/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1341417 -> 1342376 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index d71808606a96c69e64679ae5428dbaf343cca41a..b39f1ffe77d6f04ccf6f062f934c7548200c8b53 100644 GIT binary patch delta 37639 zcmZsiQ*dBGyR|2p*tRC-#OB1B*tTu#WMbRS#I|kQwr%I1@B7cWJ6-jx+81wiRbTYp z{jRn97>ILsulu?`Y+h^FT z-(q4h`?Oh3YujpwYZT;g@3jReMR+Rs(qxcaSfCL>UmG%ITV_W6mpz{Asz__8oy#j z)vw#0NFpkrZf1&%?77lT9FOi7p~_ISmr!bug!ov)WP_}mn-~vAc2>W_YoTs~2UTAL zgYmPtCH5~rZ&=UYdEa_`$hTdxnPlNsp$U;$?1UiVR}Obd76)5DxLy1=PO;8+2!oYM zKH_`Tu?^!GXZQB{!B|nGeQsV!!AWYQ(FlS~Nq-Ol%J@D69;v8$`Tk(ud~>L!>oA>! 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Subject: [PATCH 29/86] Update docs/joss/paper.md Co-authored-by: Alistair White <59571934+white-alistair@users.noreply.github.com> --- docs/joss/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 39ba3f586..1683e60d8 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -162,7 +162,7 @@ number format-flexible. 32-bit single-precision floating-point numbers (Float32) are the default as adopted by other modelling efforts [@Vana2017; @Nakano2018], but Float64 and other custom number formats can be used with a single code basis [@Klower2022; @Klower2020]. -Julia will compile to the choice of the number format, the grid, +Julia will compile to the choice of number format, the grid, and and other model components just-in-time. A simple parallelisation across vertical layers is supported with Julia's multi threading. 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This paper presents Enzyme, a high-performance automatic differentiation (AD) compiler plugin for the LLVM compiler framework capable of synthesizing gradients of statically analyzable programs expressed in the LLVM intermediate representation (IR). Enzyme synthesizes gradients for programs written in any language whose compiler targets LLVM IR including C, C++, Fortran, Julia, Rust, Swift, MLIR, etc., thereby providing native AD capabilities in these languages. Unlike traditional source-to-source and operator-overloading tools, Enzyme performs AD on optimized IR. On a machine-learning focused benchmark suite including Microsoft's ADBench, AD on optimized IR achieves a geometric mean speedup of 4.2 times over AD on IR before optimization allowing Enzyme to achieve state-of-the-art performance. Packaging Enzyme for PyTorch and TensorFlow provides convenient access to gradients of foreign code with state-of-the-art performance, enabling foreign code to be directly incorporated into existing machine learning workflows.}, file = {/Users/milan/Zotero/storage/Y9ZTEWXC/Moses and Churavy - 2020 - Instead of Rewriting Foreign Code for Machine Lear.pdf} } + +@phdthesis{Meyer_2022, + title = {Machine Learning Emulators for Numerical Weather Prediction—Applications to Parametrization Schemes}, + author = {David Meyer}, + year = {2022}, + school = {University of Reading}, + type = {PhD thesis}, + note = {Available at \url{https://www.doi.org/10.48683/1926.00109229}} +} + +@article{Meyer_et_al_2022, + doi = {10.1029/2021ms002744}, + year = {2022}, + volume = {14}, + number = {3}, + author = {David Meyer and Sue Grimmond and Peter Dueben and Robin Hogan and Maarten van Reeuwijk}, + title = {Machine Learning Emulation of Urban Land Surface Processes}, + journal = {Journal of Advances in Modeling Earth Systems} +} + +@article{Rose2018, + title = {{{CLIMLAB}}: A {{Python}} Toolkit for Interactive, Process-Oriented Climate Modeling}, + shorttitle = {{{CLIMLAB}}}, + author = {j Rose, Brian E.}, + year = {2018}, + month = apr, + journal = {Journal of Open Source Software}, + volume = {3}, + number = {24}, + pages = {659}, + issn = {2475-9066}, + doi = {10.21105/joss.00659}, + urldate = {2023-09-29}, + abstract = {Rose, (2018). CLIMLAB: a Python toolkit for interactive, process-oriented climate modeling. Journal of Open Source Software, 3(24), 659, https://doi.org/10.21105/joss.00659}, + langid = {english}, + file = {/Users/milan/Zotero/storage/25RBWXLV/Rose - 2018 - CLIMLAB a Python toolkit for interactive, process.pdf} +} + diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 1683e60d8..1173cdcfa 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -92,9 +92,11 @@ bibliography: paper.bib SpeedyWeather.jl is a library to simulate and analyze the global atmospheric circulation on the sphere. It implements several 2D and 3D -models to solve the primitive equations with and without humidity (\autoref{fig:primitive}), -the shallow water equations (\autoref{fig:swm}), or the barotropic vorticity equations -with spherical harmonics. Several simple parameterizations for unresolved physical processes +models solved with spherical harmonics: +- the primitive equations with and without humidity (\autoref{fig:primitive}), +- the shallow water equations (\autoref{fig:swm}), and +- the barotropic vorticity equations. +Several simple parameterizations for unresolved physical processes such as precipitation or the boundary layer are implemented, and new ones can be externally defined and passed as an argument to the model constructor. SpeedyWeather.jl is an intermediate-complexity general circulation model [@Kucharski2013] @@ -102,45 +104,53 @@ and research playground with an (almost) everything-flexible attitude. It can be thought of as a conceptual reinvention of the Fortran SPEEDY model [@Molteni2003] in the Julia programming language [@Bezanson2017]. -SpeedyWeather.jl internally uses three sub-modules `SpeedyTransforms`, `RingGrids`, and -`LowerTriangularMatrices` to perform spherical harmonic transforms and interpolations -between various grids and the spectral space. `RingGrids` discretize the sphere -on iso-latitude rings and the spectral space is defined by the `LowerTriangularMatrices` -of the spherical harmonic coefficients. These three modules are independently usable -and therefore make SpeedyWeather.jl, beyond its main purpose of simulating the weather, -also a library for the analysis of gridded data on the sphere. +SpeedyWeather.jl internally uses three sub-modules `RingGrids`, +`LowerTriangularMatrices`, and `SpeedyTransforms`. `RingGrids` is a module that discretizes +the sphere on iso-latitude rings and implements interpolations between various grids. +`LowerTriangularMatrices` is a module used to define the spectral space of the spherical +harmonic coefficients. `SpeedyTransforms` implements the spectral transform between +the grid-point space as defined by `RingGrids` and the spectral space defined in +`LowerTriangularMatrices`. These three modules are independently usable +and therefore make SpeedyWeather.jl, beyond its main purpose of simulating +atmospheric motion also a library for the analysis of gridded data on the sphere. Running and analysing simulations can be interactively combined, enhancing user experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by the Julia ocean model Oceananigans.jl [@Ramadhan2020]. A monolithic interface based on parameter files is avoided in favor of a -library-style interface in which users write code to run models rather than -merely supplying parameters and input arrays. +library-style interface in which users write short scripts to run models +rather than merely supplying parameters and input arrays. A model is created bottom-up by first defining the discretization and any non-default model components with their respective parameters. All components are then collected into a single model object which, once -initialized, returns a simulation object that contains the entire model state, -work arrays and parameters, that can be run, analysed or changed. +initialized, returns a simulation object. A simulation contains everything, +the model with all parameters as created before but also all prognostic and diagnostic variables. +Such a simulation can then be run, but also accessed to analyze the current variables, +or individual terms of the equations. One can also adjust parameters before resuming the +simulation. + While these steps can be written into a script for reproducibility, the same steps can be executed and interacted with one-by-one in -Julia's read-evaluate-print loop (REPL). We thereby reach an interactivity -far beyond a monolithic interface that is limited to the options provided. -At the same time, sensible default arguments enable even inexperienced users -to run simulations in just a few lines of code. +Julia's read-evaluate-print loop (REPL). We thereby achieve an interactivity +of a simulation and its various model components far beyond +the options provided in a monolithic interface. +At the same time, defaults, set to well-established test cases, +enable even inexperienced users to run simulations in just a few lines of code. To be extensible and composable with new model components, SpeedyWeather.jl relies on Julia's multiple dispatch programming paradigm [@Bezanson2017]. Every model component -is defined as a new type. For example, to define a new way how to calculate -the precipitation due to the physical process of large-scale condensation, +is defined as a new type. For example, to define precipitation due to the +physical process of large-scale condensation, one would define `MyCondensation` as a new subtype of `AbstractCondensation`. One then only needs to extend the `initialize!` and `condensation!` functions for this new type. Passing on `condensation = MyCondensation()` to the model constructor then implements this new model component without the need to branch off or overwrite existing model components. Conceptually similar scientific modelling paradigms have been very successful -in the Python-based generic partial differential equation solver Dedalus [@Burns2020] +in the Python-based generic partial differential equation solver Dedalus [@Burns2020], +the process-oriented climate model CLIMLAB [@Rose2018], and the Julia ocean model Oceananigans.jl [@Ramadhan2020]. ![Surface temperature simulated with the primitive equation model in SpeedyWeather.jl. @@ -158,13 +168,19 @@ Gaussian grid, a regular longitude-latitude grid, the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. Both SpeedyWeather.jl and its spherical harmonic transform SpeedyTransforms are also -number format-flexible. 32-bit single-precision floating-point numbers +number format-flexible. Single precision floating-point numbers (Float32) are the default as adopted by other modelling efforts [@Vana2017; @Nakano2018], but Float64 and other custom number formats can be used with a single code basis [@Klower2022; @Klower2020]. +<<<<<<< HEAD +Julia will compile to the choice of the number format, the grid, +and and other model components just-in-time. A simple parallelization +across vertical layers is supported by Julia's multithreading. +======= Julia will compile to the choice of number format, the grid, and and other model components just-in-time. A simple parallelisation across vertical layers is supported with Julia's multi threading. +>>>>>>> 8c99caf7620a833b1c3563a0cc77e59466da2fd4 Output is stored as NetCDF files using [NCDatasets.jl](https://github.com/Alexander-Barth/NCDatasets.jl). @@ -175,18 +191,20 @@ models that have been very influential in many areas of scientific and high-performance computing as well as climate change mitigation and adaptation. Most weather, ocean and climate models are written in Fortran and have been developed over decades. From this tradition follows a specific programming style and -associated user interface. Running a simulation in Fortran and analysing the +associated user interface. +SpeedyWeather.jl aims to overcome the constraints of traditional Fortran-based models. +Running a simulation in Fortran and analyzing the data in Python makes it virtually impossible to interact with various model -components interactively. Furthermore, data-driven climate modelling -[@Rasp2018; @Schneider2023], which replaces existing model components with machine learning -is difficult due to the lack of established deep learning frameworks in Fortran [@Innes2019]. -Let alone online learning, which trains a neural network-based component together -with the rest of the model, accounting for interactions between components. -Gradients, necessary to optimize training, can be computed -with automatic differentiation [@Moses2020], but only if differentiable functions -in a coherent language framework are provided. - -We hope to provide with SpeedyWeather.jl a first test platform for data-driven +components directly. In SpeedyWeather.jl, interfaces to the model components are +exposed to the user. Furthermore, data-driven climate modelling +[@Rasp2018; @Schneider2023], which replaces existing model components with machine learning, +is difficult due to the lack of established machine learning frameworks in Fortran. +In Julia, Flux.jl is available for machine learning [@Innes2019] as well as automatic +differentiation with Enzyme [@Moses2020], which calculates gradients, +necessary to optimize network weights or parameters during training. + + +With SpeedyWeather.jl we hope to provide a first test platform for data-driven atmospheric modelling and in general an interactive model that makes difficult problems easy to simulate. Climate models that are user-friendly, trainable, but also easily extensible will suddenly make many complex @@ -195,8 +213,8 @@ research ideas possible. ![Relative vorticity simulated with the shallow water model in SpeedyWeather.jl. The simulation used a spectral resolution of T1023 (about 20 km) and Float32 arithmetic on an octahedral Clenshaw-Curtis grid [@Hotta2018]. Relative vorticity -is visualised with Matplotlib [@Hunter2007] and Cartopy [@Cartopy] using a -transparent-to-white colormap to mimic the appearance of clouds. Underlain is +is visualized with Matplotlib [@Hunter2007] and Cartopy [@Cartopy] using a +transparent-to-white colormap to mimic the appearance of clouds. Underlaid is NASA's blue marble from June 2004. \label{fig:swm}](swm.png) # Acknowledgements @@ -204,7 +222,8 @@ NASA's blue marble from June 2004. \label{fig:swm}](swm.png) We acknowledge contributions from Mosè Giordano, Valentin Churavy, and Pietro Monticone who have also committed to the SpeedyWeather.jl repository, and the wider Julia community for help and support. MK acknowledges funding from the -National Science Foundation (Chris please add). MK and TK acknowledge funding from the European Research Council +National Science Foundation (Chris please add). +MK and TK acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme for the ITHACA grant (no. 741112). NCC acknowledges support by the Australian Research Council DECRA Fellowship DE210100749. 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zMo{jU?`ny>TG19=^9l8ved24lEnlEBt|92nY<1t!>tuE!iZ3@SGl`L*vOFKE3c@I! zZd%2!lx@D&ImqCD3x2}iU1%_zlH-sen+O`c-+YyNmYn90ibHX5U8c(r*AN}58yim# zAR%GydGV`MBxzwS&N(s1dMGvCCVs<4+M=Vd_e@H=HZzvhU#8k_*77p{Ce5sB+0v(2 k!ZrG`t0rYua)zBLkbECA5e%@Aii%4~lW=pZ!qiCq1)KqfNdN!< From 794ae95beb68c2d20f634663c3f19db91e4f3969 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Mon, 16 Oct 2023 16:53:17 -0400 Subject: [PATCH 33/86] joss paper: spaces for list --- docs/joss/paper.md | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 1173cdcfa..27257294b 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -93,9 +93,11 @@ bibliography: paper.bib SpeedyWeather.jl is a library to simulate and analyze the global atmospheric circulation on the sphere. It implements several 2D and 3D models solved with spherical harmonics: + - the primitive equations with and without humidity (\autoref{fig:primitive}), - the shallow water equations (\autoref{fig:swm}), and - the barotropic vorticity equations. + Several simple parameterizations for unresolved physical processes such as precipitation or the boundary layer are implemented, and new ones can be externally defined and passed as an argument to the model constructor. @@ -172,15 +174,9 @@ number format-flexible. Single precision floating-point numbers (Float32) are the default as adopted by other modelling efforts [@Vana2017; @Nakano2018], but Float64 and other custom number formats can be used with a single code basis [@Klower2022; @Klower2020]. -<<<<<<< HEAD Julia will compile to the choice of the number format, the grid, and and other model components just-in-time. A simple parallelization across vertical layers is supported by Julia's multithreading. -======= -Julia will compile to the choice of number format, the grid, -and and other model components just-in-time. A simple parallelisation -across vertical layers is supported with Julia's multi threading. ->>>>>>> 8c99caf7620a833b1c3563a0cc77e59466da2fd4 Output is stored as NetCDF files using [NCDatasets.jl](https://github.com/Alexander-Barth/NCDatasets.jl). @@ -203,7 +199,6 @@ In Julia, Flux.jl is available for machine learning [@Innes2019] as well as auto differentiation with Enzyme [@Moses2020], which calculates gradients, necessary to optimize network weights or parameters during training. - With SpeedyWeather.jl we hope to provide a first test platform for data-driven atmospheric modelling and in general an interactive model that makes difficult problems easy to simulate. 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zJJ@8+Pn4uEywOhm7~Ic8UO$1n(;Uu2(h@Id6M-5PQ3F;`cP@w3@FltvVu~L3_W?`s zA%OjQ+wZqH3tBH}UnGPZioNC^Nr5xYJ8djiwG*$!o4W6DN%&;$sQNbk5Nn)R&KyG> Z1Qc|kH9`Tb#9*)}jEIv{Nk^IJe*q&t_;dgO From 61f4850c6434abf570c3e2977046244cc89fd682 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Mon, 16 Oct 2023 17:10:21 -0400 Subject: [PATCH 35/86] JOSS paper: slight tweaks --- docs/joss/paper.md | 43 +++++++++++++++++++++---------------------- 1 file changed, 21 insertions(+), 22 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 27257294b..a47c0b593 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -108,7 +108,7 @@ in the Julia programming language [@Bezanson2017]. SpeedyWeather.jl internally uses three sub-modules `RingGrids`, `LowerTriangularMatrices`, and `SpeedyTransforms`. `RingGrids` is a module that discretizes -the sphere on iso-latitude rings and implements interpolations between various grids. +the sphere on iso-latitude rings and implements interpolations between various such grids. `LowerTriangularMatrices` is a module used to define the spectral space of the spherical harmonic coefficients. `SpeedyTransforms` implements the spectral transform between the grid-point space as defined by `RingGrids` and the spectral space defined in @@ -128,15 +128,14 @@ and any non-default model components with their respective parameters. All components are then collected into a single model object which, once initialized, returns a simulation object. A simulation contains everything, the model with all parameters as created before but also all prognostic and diagnostic variables. -Such a simulation can then be run, but also accessed to analyze the current variables, -or individual terms of the equations. One can also adjust parameters before resuming the -simulation. - +Such a simulation can then be run, but also accessed before and after to analyze or +visualize the current variables, or individual terms of the equations. +One can also adjust parameters or define new model components before resuming the simulation. While these steps can be written into a script for reproducibility, the same steps can be executed and interacted with one-by-one in -Julia's read-evaluate-print loop (REPL). We thereby achieve an interactivity -of a simulation and its various model components far beyond -the options provided in a monolithic interface. +Julia's read-evaluate-print loop (REPL) or in a single Jupyter or Pluto notebook. +We thereby achieve an interactivity of a simulation and its various model components +far beyond the options provided in a monolithic interface. At the same time, defaults, set to well-established test cases, enable even inexperienced users to run simulations in just a few lines of code. @@ -169,8 +168,8 @@ as an argument. Many grids are already implemented: the conventional Gaussian grid, a regular longitude-latitude grid, the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. -Both SpeedyWeather.jl and its spherical harmonic transform SpeedyTransforms are also -number format-flexible. Single precision floating-point numbers +Both SpeedyWeather.jl and its spherical harmonic transform `SpeedyTransforms` are also +number format-flexible. Single-precision floating-point numbers (Float32) are the default as adopted by other modelling efforts [@Vana2017; @Nakano2018], but Float64 and other custom number formats can be used with a single code basis [@Klower2022; @Klower2020]. @@ -182,24 +181,24 @@ Output is stored as NetCDF files using # Statement of need -SpeedyWeather.jl is a fresh approach to atmospheric -models that have been very influential in many areas of scientific -and high-performance computing as well as climate change mitigation and adaptation. -Most weather, ocean and climate models are written in Fortran and have been developed over -decades. From this tradition follows a specific programming style and -associated user interface. +SpeedyWeather.jl is a fresh approach to atmospheric models that have been +very influential in many areas of scientific and high-performance computing +as well as climate change mitigation and adaptation. +Most weather, ocean and climate models are written in Fortran and have been +developed over decades. From this tradition follows a specific programming +style and associated user interface. SpeedyWeather.jl aims to overcome the constraints of traditional Fortran-based models. -Running a simulation in Fortran and analyzing the -data in Python makes it virtually impossible to interact with various model -components directly. In SpeedyWeather.jl, interfaces to the model components are -exposed to the user. Furthermore, data-driven climate modelling -[@Rasp2018; @Schneider2023], which replaces existing model components with machine learning, +Running a simulation in Fortran and analyzing the data in Python makes it +virtually impossible to interact with various model components directly. +In SpeedyWeather.jl, interfaces to the model components are exposed to the user. +Furthermore, data-driven climate modelling [@Rasp2018; @Schneider2023], +which replaces existing model components with machine learning, is difficult due to the lack of established machine learning frameworks in Fortran. In Julia, Flux.jl is available for machine learning [@Innes2019] as well as automatic differentiation with Enzyme [@Moses2020], which calculates gradients, necessary to optimize network weights or parameters during training. -With SpeedyWeather.jl we hope to provide a first test platform for data-driven +With SpeedyWeather.jl we hope to provide a platform for data-driven atmospheric modelling and in general an interactive model that makes difficult problems easy to simulate. Climate models that are user-friendly, trainable, but also easily extensible will suddenly make many complex From fc757896417f610278d58c4279d47c0b781f9968 Mon Sep 17 00:00:00 2001 From: milankl Date: Mon, 16 Oct 2023 21:11:14 +0000 Subject: [PATCH 36/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1343605 -> 1343772 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index 9380b549c4d061ebeaacea258c65f6388e33ec4c..e747219b4cca9d9867091d8aa84665f47b6c7b63 100644 GIT binary patch delta 29345 zcmV)VK(D{`fKr@-Qm`Kj12#D`mk~}B6o2hK%Z?;DZuk0%{DIO))Eh_?kX4nr@ZQEd zfDem3wXyc0+s68`zi;YIDIOUaSv%{71JgB`5vd17Q6xoD6hCqN?|=Rye(=-3{^3Q$ zFXAMOU{a_P2*I?6)3+Zle|uq;TkcQ!M&`TGwNhKPKp%;lYdfiuEpCcIDAkh{~>zy1%GsJ?LDGe<9p@Pvqtpu z8-9PszfaD^``fEh>YOGf*1#4Nme4jo-*OB2y>f4_Qpz)F`--2~td2nSeZ^X;)^M%O zS^@$j3xx2?&6|^A-g2Qkv}lF1D@U{lSZwDmf{kNdtJ0EE3HAtK7?(--s()j?q%o^o z9b3dgnG&4``WettiiC<-B$m)+k|00JJb?{a7lM3>EJZ-D`BUdsE^jW><)5{cP}8?o 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paper added --- docs/joss/paper.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index a47c0b593..14be58e3f 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -188,12 +188,13 @@ Most weather, ocean and climate models are written in Fortran and have been developed over decades. From this tradition follows a specific programming style and associated user interface. SpeedyWeather.jl aims to overcome the constraints of traditional Fortran-based models. -Running a simulation in Fortran and analyzing the data in Python makes it -virtually impossible to interact with various model components directly. +The modern trend sees simulations in Fortran and data analysis in Python, +making virtually impossible to interact with various model components directly. In SpeedyWeather.jl, interfaces to the model components are exposed to the user. Furthermore, data-driven climate modelling [@Rasp2018; @Schneider2023], which replaces existing model components with machine learning, -is difficult due to the lack of established machine learning frameworks in Fortran. +is more difficult in Fortran due to the lack of +established machine learning frameworks [@Meyer2022]. In Julia, Flux.jl is available for machine learning [@Innes2019] as well as automatic differentiation with Enzyme [@Moses2020], which calculates gradients, necessary to optimize network weights or parameters during training. From 8615235c4325776d2e0338834386542b62f1a416 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Mon, 16 Oct 2023 17:28:36 -0400 Subject: [PATCH 38/86] JOSS paper: citation typo --- docs/joss/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 14be58e3f..ec045efa3 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -194,7 +194,7 @@ In SpeedyWeather.jl, interfaces to the model components are exposed to the user. Furthermore, data-driven climate modelling [@Rasp2018; @Schneider2023], which replaces existing model components with machine learning, is more difficult in Fortran due to the lack of -established machine learning frameworks [@Meyer2022]. +established machine learning frameworks [@Meyer_2022]. In Julia, Flux.jl is available for machine learning [@Innes2019] as well as automatic differentiation with Enzyme [@Moses2020], which calculates gradients, necessary to optimize network weights or parameters during training. From f2b6f7d79bf02b126b5850e9b073ae0b9f05d27c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Mon, 16 Oct 2023 17:29:48 -0400 Subject: [PATCH 39/86] JOSS paper: David's paper key changed --- docs/joss/paper.bib | 19 ++++++++++--------- docs/joss/paper.md | 2 +- 2 files changed, 11 insertions(+), 10 deletions(-) diff --git a/docs/joss/paper.bib b/docs/joss/paper.bib index 27971ebc3..8002c9f9e 100644 --- a/docs/joss/paper.bib +++ b/docs/joss/paper.bib @@ -451,16 +451,8 @@ @inproceedings{Moses2020 file = {/Users/milan/Zotero/storage/Y9ZTEWXC/Moses and Churavy - 2020 - Instead of Rewriting Foreign Code for Machine Lear.pdf} } -@phdthesis{Meyer_2022, - title = {Machine Learning Emulators for Numerical Weather Prediction—Applications to Parametrization Schemes}, - author = {David Meyer}, - year = {2022}, - school = {University of Reading}, - type = {PhD thesis}, - note = {Available at \url{https://www.doi.org/10.48683/1926.00109229}} -} -@article{Meyer_et_al_2022, +@article{Meyer2022a, doi = {10.1029/2021ms002744}, year = {2022}, volume = {14}, @@ -470,6 +462,15 @@ @article{Meyer_et_al_2022 journal = {Journal of Advances in Modeling Earth Systems} } +@phdthesis{Meyer2022b, + title = {Machine Learning Emulators for Numerical Weather Prediction—Applications to Parametrization Schemes}, + author = {David Meyer}, + year = {2022}, + school = {University of Reading}, + type = {PhD thesis}, + note = {Available at \url{https://www.doi.org/10.48683/1926.00109229}} +} + @article{Rose2018, title = {{{CLIMLAB}}: A {{Python}} Toolkit for Interactive, Process-Oriented Climate Modeling}, shorttitle = {{{CLIMLAB}}}, diff --git a/docs/joss/paper.md b/docs/joss/paper.md index ec045efa3..8a4965709 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -194,7 +194,7 @@ In SpeedyWeather.jl, interfaces to the model components are exposed to the user. Furthermore, data-driven climate modelling [@Rasp2018; @Schneider2023], which replaces existing model components with machine learning, is more difficult in Fortran due to the lack of -established machine learning frameworks [@Meyer_2022]. +established machine learning frameworks [@Meyer2022a]. In Julia, Flux.jl is available for machine learning [@Innes2019] as well as automatic differentiation with Enzyme [@Moses2020], which calculates gradients, necessary to optimize network weights or parameters during training. 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zKjb!eRYs%vKI4b2NVaYc%M~Oh^WRp3@Z939c%?tDDX#@%uDGR2#GfoKpv9l|I0>dD zaD_ih{4ASe!^4t$7M+xp7V-Ou3{OK%e8se$$fTxqEhR+dP!ZMMb-uN*(a{{%e83(<_$hiqb>#*JeW=e(+y|jOlY4hd1y(g_%_WB{9}{!nHR0W7zdybXP3d!_8rQB( z=5iDoSKmuUR%YB!!tlA*`G0q)Om^d&)MDs%4zGCTsVBBXSnuti|M3-1rpHL;#WgmC za3EuSTi!~^ndG2n9<6YnUPOq=u|+LxpY`YrbE~-nvy6dOktU{)SNE|A-zQZI4+-2k z_AZ+W?V?>(JZ*DvfdsRo{hiMk?Q7~@0D`E_o9^h zf^XKER9zz8O}||A!p-br#x6ZhXQG>dwtUiheT&(e(uZd#L+{bfhb@wo!y^w|?dmEwHg2d@H{M%w zLBCoS(v&!J#Sn(2c>F=?kZODNoHBiMkQU|3bKji|a1=$Qk^QSVpNN)M2o-7?b&hBK sSeL~}UFdtd$ Date: Mon, 16 Oct 2023 17:46:54 -0400 Subject: [PATCH 41/86] JOSS paper: Add Justin's citations --- docs/joss/paper.bib | 37 +++++++++++++++++++++++++++++++++++++ docs/joss/paper.md | 17 ++++++++--------- 2 files changed, 45 insertions(+), 9 deletions(-) diff --git a/docs/joss/paper.bib b/docs/joss/paper.bib index 8002c9f9e..e54aabf40 100644 --- a/docs/joss/paper.bib +++ b/docs/joss/paper.bib @@ -489,3 +489,40 @@ @article{Rose2018 file = {/Users/milan/Zotero/storage/25RBWXLV/Rose - 2018 - CLIMLAB a Python toolkit for interactive, process.pdf} } +@article{reinecke2013, + author = {{Reinecke}, M. and {Seljebotn}, D.~S.}, + title = "{Libsharp - spherical harmonic transforms revisited}", + journal = {Astronomy and Astrophysics}, + year = 2013, + month = jun, + volume = {554}, + eid = {A112}, + pages = {A112}, + doi = {10.1051/0004-6361/201321494}, + eprinttype = {arXiv}, + eprint = {1303.4945}, + eprintclass = {physics.comp-ph}, + adsurl = {https://ui.adsabs.harvard.edu/abs/2013A&A...554A.112R}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@misc{stompor2011, + author = {{Stompor}, Radek}, + title = "{S2HAT: Scalable Spherical Harmonic Transform Library}", + keywords = {Software}, +howpublished = {Astrophysics Source Code Library, record ascl:1110.013}, + year = 2011, + month = oct, + eprintclass = {ascl}, + eprint = {1110.013}, + adsurl = {https://ui.adsabs.harvard.edu/abs/2011ascl.soft10013S}, + adsnote = {Provided by the SAO/NASA Astrophysics Data System} +} + +@misc{Willmert2020, + author = {Willmert, Justin}, + title = {Blog Series: Notes on Calculating the Spherical Harmonics}, + howpublished = {\url{https://justinwillmert.com/articles/2020/notes-on-calculating-the-spherical-harmonics/}}, + year = 2020, + note = {Accessed: 2023-10-16} +} diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 8a4965709..8d72f852e 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -1,5 +1,5 @@ --- -title: 'SpeedyWeather.jl: Reinventing atmospheric general circulation models towards interactivity, extensibility and composability' +title: 'SpeedyWeather.jl: Reinventing atmospheric general circulation models towards interactivity and extensibility' tags: - Julia @@ -139,11 +139,10 @@ far beyond the options provided in a monolithic interface. At the same time, defaults, set to well-established test cases, enable even inexperienced users to run simulations in just a few lines of code. -To be extensible and composable with new -model components, SpeedyWeather.jl relies on Julia's multiple dispatch -programming paradigm [@Bezanson2017]. Every model component -is defined as a new type. For example, to define precipitation due to the -physical process of large-scale condensation, +To be extensible with new model components, SpeedyWeather.jl relies on Julia's +multiple dispatch programming paradigm [@Bezanson2017]. +Every model component is defined as a new type. +For example, to define precipitation due to the physical process of large-scale condensation, one would define `MyCondensation` as a new subtype of `AbstractCondensation`. One then only needs to extend the `initialize!` and `condensation!` functions for this new type. Passing on `condensation = MyCondensation()` @@ -160,9 +159,9 @@ and the Julia ocean model Oceananigans.jl [@Ramadhan2020]. The dynamical core of SpeedyWeather.jl uses established numerics [@Bourke1972; @Hoskins1975; @Simmons1978; @Simmons1981], widely adopted in numerical weather prediction. It is based on the spherical -harmonic transform with a leapfrog-based semi-implicit time integration [@Hoskins1975] -and a Robert-Asselin-Williams filter [@Williams2011; @Amezcua2011]. -The spherical harmonic transform is grid-flexible. Any iso-latitude ring-based +harmonic transform [@reinecke2013; @stompor2011] with a leapfrog-based semi-implicit +time integration [@Hoskins1975] and a Robert-Asselin-Williams filter [@Williams2011; @Amezcua2011]. +The spherical harmonic transform is grid-flexible [@Willmert2020]. Any iso-latitude ring-based grid can be used and new grids can be externally defined and passed in as an argument. 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It implements several 2D and 3D -models solved with spherical harmonics: +models solving different sets of equations: - the primitive equations with and without humidity (\autoref{fig:primitive}), - the shallow water equations (\autoref{fig:swm}), and -- the barotropic vorticity equations. +- the barotropic vorticity equation. Several simple parameterizations for unresolved physical processes -such as precipitation or the boundary layer are implemented, and new ones can +including precipitation or boundary layer mixing are implemented, and new ones can be externally defined and passed as an argument to the model constructor. SpeedyWeather.jl is an intermediate-complexity general circulation model [@Kucharski2013] and research playground with an (almost) everything-flexible attitude. @@ -116,14 +116,14 @@ A monolithic interface based on parameter files is avoided in favor of a library-style interface. Users write notebooks, directly into Julia's read-evaluate-print loop (REPL) or short scripts to run models rather than merely supplying parameters and input arrays. -A model is created bottom-up by first defining the discretization +A model is constructed bottom-up by first defining the discretization and any non-default model components with their respective parameters. All components are then collected into a single model object which, once initialized, returns a simulation object. A simulation contains everything, the model with all parameters as created before but also all prognostic and diagnostic variables. Such a simulation can then be run, but also accessed before and after to analyze or visualize the current variables, or individual terms of the equations. -One can also adjust parameters or define new model components before resuming the simulation. +One can also adjust some parameters before resuming the simulation. While these steps can be written into a script for reproducibility, the same steps can be executed and interacted with one-by-one in the REPL or in a single Jupyter or Pluto notebook. @@ -132,10 +132,12 @@ far beyond the options provided in a monolithic interface. At the same time, defaults, set to well-established test cases, enable even inexperienced users to run simulations in just a few lines of code. -To be extensible with new model components, SpeedyWeather.jl relies on Julia's -multiple dispatch programming paradigm [@Bezanson2017]. -Every model component is defined as a new type. -For example, to define precipitation due to the physical process of large-scale condensation, +SpeedyWeather.jl relies on Julia's multiple dispatch programming paradigm [@Bezanson2017] +to be extensible with new components including parameterizations, forcings, drag, +or even the grid. +All such supported model components define an abstract type that can be +subtyped to introduce, for example, a new parameterization. +To define precipitation due to the physical process of large-scale condensation, one would define `MyCondensation` as a new subtype of `AbstractCondensation`. One then only needs to extend the `initialize!` and `condensation!` functions for this new type. 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zy?e26LH680YtYPi8R*A5B{JnVl2hP`@Vd_b4!8e24RLidc5(B1*#M!iv2%bpctI%C K)RJ$dQ2rm|(fQ^8 From 71a93552d28563b060198204bded29dc8b34d93f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Wed, 25 Oct 2023 14:31:40 -0400 Subject: [PATCH 49/86] JOSS paper: Alistair not MIT --- docs/joss/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index e40a7069b..030d9526b 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -36,7 +36,7 @@ authors: affiliation: 1 - name: Alistair White - - orcid: 0000-0003-3377-6852 + orcid: 0000-0003-3377-6852 affiliation: "3,4" - name: Sam Hatfield From 4ede4da9d373b3be804cb4dba05ee3849bce673a Mon Sep 17 00:00:00 2001 From: milankl Date: Wed, 25 Oct 2023 18:32:36 +0000 Subject: [PATCH 50/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1343549 -> 1343486 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index 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JOSS paper: Simone's restructure suggestions --- docs/joss/paper.md | 40 +++++++++++++++++++++------------------- 1 file changed, 21 insertions(+), 19 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 030d9526b..c47599304 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -84,7 +84,7 @@ bibliography: paper.bib SpeedyWeather.jl is a library to simulate and analyze the global atmospheric circulation on the sphere. It implements several 2D and 3D -models solving different sets of equations: +models which solve different sets of equations: - the primitive equations with and without humidity (\autoref{fig:primitive}), - the shallow water equations (\autoref{fig:swm}), and @@ -93,19 +93,13 @@ models solving different sets of equations: Several simple parameterizations for unresolved physical processes including precipitation or boundary layer mixing are implemented, and new ones can be externally defined and passed as an argument to the model constructor. -SpeedyWeather.jl is an intermediate-complexity general circulation model [@Kucharski2013] -and research playground with an (almost) everything-flexible attitude. -It can be thought of as a conceptual reinvention of the Fortran SPEEDY model [@Molteni2003] -in the Julia programming language [@Bezanson2017]. - -SpeedyWeather.jl internally uses three sub-modules `RingGrids`, -`LowerTriangularMatrices`, and `SpeedyTransforms`. `RingGrids` is a module that discretizes -the sphere on iso-latitude rings and implements interpolations between various such grids. -`LowerTriangularMatrices` is a module used to define the spectral space of the spherical -harmonic coefficients. `SpeedyTransforms` implements the spectral transform between -the grid-point space as defined by `RingGrids` and the spectral space defined in -`LowerTriangularMatrices`. These three modules are independently usable -and therefore make SpeedyWeather.jl, beyond its main purpose of simulating +The primitive equation model in SpeedyWeather.jl is an intermediate-complexity +atmospheric general circulation model [@Kucharski2013] and can be thought of as a +conceptual reinvention of the Fortran SPEEDY model [@Molteni2003] in the Julia +programming language [@Bezanson2017]. However, all models are written in a modular +way to make its components easily extensible. Furthermore, operators used inside +SpeedyWeather.jl are exposed to the user, facilitating analysis of the simulation +data. SpeedyWeather.jl is therefore, beyond its main purpose of simulating atmospheric motion, also a library for the analysis of gridded data on the sphere. Running and analyzing simulations can be interactively combined, enhancing user experience and productivity. @@ -113,20 +107,18 @@ experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by the Julia ocean model Oceananigans.jl [@Ramadhan2020]. A monolithic interface based on parameter files is avoided in favor of a -library-style interface. Users write notebooks, directly into -Julia's read-evaluate-print loop (REPL) or short scripts to run models -rather than merely supplying parameters and input arrays. +library-style interface. A model is constructed bottom-up by first defining the discretization and any non-default model components with their respective parameters. All components are then collected into a single model object which, once initialized, returns a simulation object. A simulation contains everything, -the model with all parameters as created before but also all prognostic and diagnostic variables. +the model with all parameters as constructed before but also all prognostic and diagnostic variables. Such a simulation can then be run, but also accessed before and after to analyze or visualize the current variables, or individual terms of the equations. One can also adjust some parameters before resuming the simulation. While these steps can be written into a script for reproducibility, the same steps can be executed and interacted with one-by-one in -the REPL or in a single Jupyter or Pluto notebook. +Julia's read-evaluate-print loop (REPL) or in a Jupyter or Pluto notebook. We thereby achieve an interactivity of a simulation and its various model components far beyond the options provided in a monolithic interface. At the same time, defaults, set to well-established test cases, @@ -170,6 +162,16 @@ code basis [@Klower2022; @Klower2020]. Julia will compile to the choice of number format, the grid, and and other model components just-in-time. A simple parallelization across vertical layers is supported by Julia's multithreading. + +SpeedyWeather.jl internally uses three sub-modules `RingGrids`, +`LowerTriangularMatrices`, and `SpeedyTransforms`. `RingGrids` is a module that discretizes +the sphere on iso-latitude rings and implements interpolations between various such grids. +`LowerTriangularMatrices` facilitates the implementation of the spherical harmonics by organizing +their coefficients in a lower triangular matrix representation. +`SpeedyTransforms` implements the spectral transform between +the grid-point space as defined by `RingGrids` and the spectral space defined in +`LowerTriangularMatrices`. These three modules are independently usable +and therefore support SpeedyWeather's library-like user interface. Output is stored as NetCDF files using [NCDatasets.jl](https://github.com/Alexander-Barth/NCDatasets.jl). 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zsq>bR3}sMHK%>+)hc`vwP}|Su2uSPk!M7vZI#>7HnrD6PFr}#PIeS^r(!#IQ+FQ-q z(wj5$4m&;N>rrrN#ykg(OKLNZBd)~+dZpAY-U20752GG`J6k~i!^I1>dJ>2WmhLDx zX!4Z_4@EG9g3dD>Ne;l<#2;S{z zN9y~~whZ<8&;o)lL=^#N^E>ICTAdZpQ!1tpV1c-3DC2%wAU-NP7eU5KV;_wzB=xc9v9IEVa+S zP-aCFjj~moBb+p4rM-c`Djya1(kVS}XlCBBj^oGK^Zqmk;#MQ1OZZA_D2=&@=^15F zUJ41lkHgc@k?D&1M-NJ+96Djp>7}h=M*+1>}ZRvNe}1|2EJ(`@USIM89wP zA*e3W4Wo(P^`&|TBk=Yvf-j*u{W`IXclMg}H4N|YlcQEkslcO%LUf!|68*D6> z57gqFv!=ZC-FD}wawgVC%HcXfB!+u From 66cf01ca50ba41f4ea834f4332053558dd635cbb Mon Sep 17 00:00:00 2001 From: Milan Date: Thu, 30 Nov 2023 10:54:16 -0500 Subject: [PATCH 57/86] joss paper: figures moved upwards --- docs/joss/paper.md | 31 +++++++++++++++---------------- 1 file changed, 15 insertions(+), 16 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 2f0e8fb1f..3842435c9 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -124,6 +124,13 @@ far beyond the options provided in a monolithic interface. At the same time, defaults, set to well-established test cases, enable even inexperienced users to run simulations in just a few lines of code. +![Surface humidity, air temperature, wind speed and precipitation simulated +with the primitive equation model in SpeedyWeather.jl. Spectral resolution is +T127 (about 100km) on an octahedral Gaussian grid [@Malardel2016] with simple +physics to represent unresolved processes such as surface fluxes including +evaporation, and precipitation due to large-scale condensation and convection. +\label{fig:primitive}](primitive.png) + SpeedyWeather.jl relies on Julia's multiple dispatch programming paradigm [@Bezanson2017] to be extensible with new components including parameterizations, forcings, drag, or even the grid. @@ -140,13 +147,6 @@ in the Python-based generic partial differential equation solver Dedalus [@Burns the process-oriented climate model CLIMLAB [@Rose2018], and the Julia ocean model Oceananigans.jl [@Ramadhan2020]. -![Surface humidity, air temperature, wind speed and precipitation simulated -with the primitive equation model in SpeedyWeather.jl. Spectral resolution is -T127 (about 100km) on an octahedral Gaussian grid [@Malardel2016] with simple -physics to represent unresolved processes such as surface fluxes including -evaporation, and precipitation due to large-scale condensation and convection. -\label{fig:primitive}](primitive.png) - The dynamical core of SpeedyWeather.jl uses established numerics [@Bourke1972; @Hoskins1975; @Simmons1978; @Simmons1981], widely adopted in numerical weather prediction. It is based on the spherical @@ -179,6 +179,13 @@ and therefore support SpeedyWeather's library-like user interface. Output is stored as NetCDF files using [NCDatasets.jl](https://github.com/Alexander-Barth/NCDatasets.jl). +![Relative vorticity simulated with the shallow water model in SpeedyWeather.jl. +The simulation used a spectral resolution of T1023 (about 20 km) and Float32 +arithmetic on an octahedral Clenshaw-Curtis grid [@Hotta2018]. Relative vorticity +is visualized with Matplotlib [@Hunter2007] and Cartopy [@Cartopy] using a +transparent-to-white colormap to mimic the appearance of clouds. Underlaid is +NASA's blue marble from June 2004. \label{fig:swm}](swm.png) + # Statement of need SpeedyWeather.jl is a fresh approach to atmospheric models that have been @@ -196,8 +203,7 @@ which replaces existing model components with machine learning, is more difficult in Fortran due to the lack of established machine learning frameworks [@Meyer2022a]. In Julia, Flux.jl is available for machine learning [@Innes2019] as well as automatic -differentiation with Enzyme [@Moses2020], which calculates gradients, -necessary to optimize network weights or parameters during training. +differentiation with Enzyme [@Moses2020] for gradients-based optimization. With SpeedyWeather.jl we hope to provide a platform for data-driven atmospheric modelling and in general an interactive model that makes difficult @@ -205,13 +211,6 @@ problems easy to simulate. Climate models that are user-friendly, trainable, but also easily extensible will suddenly make many complex research ideas possible. -![Relative vorticity simulated with the shallow water model in SpeedyWeather.jl. -The simulation used a spectral resolution of T1023 (about 20 km) and Float32 -arithmetic on an octahedral Clenshaw-Curtis grid [@Hotta2018]. Relative vorticity -is visualized with Matplotlib [@Hunter2007] and Cartopy [@Cartopy] using a -transparent-to-white colormap to mimic the appearance of clouds. Underlaid is -NASA's blue marble from June 2004. \label{fig:swm}](swm.png) - # Acknowledgements We acknowledge contributions from David Meyer, Mosè Giordano, Valentin Churavy, and Pietro Monticone From 465edc71bb6f800b752d152fcc973f98638eee6d Mon Sep 17 00:00:00 2001 From: milankl Date: Thu, 30 Nov 2023 15:55:08 +0000 Subject: [PATCH 58/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1463548 -> 1461146 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index 5d13000570369688caeb26fc8c3d9c1c1b8a35ee..a4ea1dfbab981771c36a2584bd4c2eb054fe1d1c 100644 GIT binary patch delta 27818 zcmY(~LvSuk10~=jH@0otwr$(CoxHJa=f<{e+qUiG#`FENn5tPkRlVryRd-dNQ{7(` zT3P8@0nNZLy1-1yL@;Q87Tu}1qfVrqIgNi1S?PBWhOB?>w}ftQ$(vvrr4wwKA??}U zzwgyXh{Za{yn@0OT168_Du;}FDE$u}?gW0PfB&5*0RD|?Xo&t0(+@(IhV)7jWk5YX zwh`?4|Bm8%@akUnwf$Il)3+W@8|)`@lM6__In4j!VC^4$wi)09ghxI%Sr~lVeSgQu zh4uitKh7t**t4lozh+Asbw4b)%$BTKy3_HZep%B# z+qLTy@nOfk`}DY|YZ=pdzvnjhW?xDyS9$qS{)BzWtlfJ>Ro1ZxcXeGp!N(thOxtCH z*FIP&;ZMF5r;hOiBm-wvZ31zxrpW4Og$|cL`vo&qHoi0f0=EtD2lQEC;wZF|(2PVu z^RY*0jqijVUfK4=V=@wRxKOyKRb2zFS<-2&5Bqq(nYluBhYSc}k;K&BD~BCYuaNK@ zPuLyteP&I#Y|CI!V9KdU|5@R`F3s|8FOnLZrwvNnxa!svSc4bIQeNfx&a@r&zlW@h+EkJykFr{-F(gi-;v?Y^iJj1cs;uPVRpXY~^VFhWw3!%S zeEfxD)B^7G9Y*Fm9gAqd(5z6jX`~ayDvQu_>zx`Ce_E%zT%~TOx)efER&w$aT0(

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zl;Tr^@f3;&zI0_(E-}|PAI1uiAyf=8L4GsRf=t^A_4l5(( zHG5Bz+OSGn%hYFvCD=E5!Eh0%U)LY(BtO|ET;DN!%1vo@chgAp1X)t{sDJhXr>Bym zFOFM;b?xZg1^4InQ?2q3*R@zq4R9-*YFA_TD6H>3XV&nMohHA!!ScbKN|Zp5eQ?SX zUfEN@uSN|Vm9Vtwf^|$7FTz#r^r#2h=-mG z4fpxK{~$B;0q)C=8&RJZcC?~bMquuK4S9y_3@(uzBAw;R?v2e;HLrd?y`Qo6&Q6uW zm$$RYdgX`S*UeJDGR4Lq!3A*a#L&t-o`LA*C5x)&C!()kV@{r{Y~`G!^1pW?Gu5AH z_8A?@%oz4ow#0AO9rY}X?5E_(X0OsX%qOEXkZlHozBVRn_J4T~AS99-1%NoNt*Hyx gz@t8R9k6CCHC#ix-J@Y80>j`iLQYOOHF?7S1rM0aMgRZ+ From fd03c799346b618cc8b401ef964499dcc4582ec0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Wed, 6 Dec 2023 11:30:18 +0000 Subject: [PATCH 59/86] josspaper: doi corrected --- docs/joss/paper.bib | 29 ++--------------------------- 1 file changed, 2 insertions(+), 27 deletions(-) diff --git a/docs/joss/paper.bib b/docs/joss/paper.bib index e54aabf40..9b1115859 100644 --- a/docs/joss/paper.bib +++ b/docs/joss/paper.bib @@ -14,7 +14,6 @@ @article{Amezcua2011 abstract = {Abstract In a recent study, Williams introduced a simple modification to the widely used Robert\textendash Asselin (RA) filter for numerical integration. The main purpose of the Robert\textendash Asselin\textendash Williams (RAW) filter is to avoid the undesired numerical damping of the RA filter and to increase the accuracy. In the present paper, the effects of the modification are comprehensively evaluated in the Simplified Parameterizations, Primitive Equation Dynamics (SPEEDY) atmospheric general circulation model. First, the authors search for significant changes in the monthly climatology due to the introduction of the new filter. After testing both at the local level and at the field level, no significant changes are found, which is advantageous in the sense that the new scheme does not require a retuning of the parameterized model physics. Second, the authors examine whether the new filter improves the skill of short- and medium-term forecasts. January 1982 data from the NCEP\textendash NCAR reanalysis are used to evaluate the forecast skill. Improvements are found in all the model variables (except the relative humidity, which is hardly changed). The improvements increase with lead time and are especially evident in medium-range forecasts (96\textendash 144 h). For example, in tropical surface pressure predictions, 5-day forecasts made using the RAW filter have approximately the same skill as 4-day forecasts made using the RA filter. The results of this work are encouraging for the implementation of the RAW filter in other models currently using the RA filter.}, chapter = {Monthly Weather Review}, langid = {english}, - file = {/Users/milan/Zotero/storage/KWWGE38V/Amezcua et al. - 2011 - The Effects of the RAW Filter on the Climatology a.pdf} } @article{Bezanson2017, @@ -32,7 +31,6 @@ @article{Bezanson2017 doi = {10.1137/141000671}, urldate = {2020-02-25}, abstract = {Bridging cultures that have often been distant, Julia combines expertise from the diverse fields of computer science and computational science to create a new approach to numerical computing. Julia is designed to be easy and fast and questions notions generally held to be ``laws of nature" by practitioners of numerical computing: \textbackslash beginlist \textbackslash item High-level dynamic programs have to be slow. \textbackslash item One must prototype in one language and then rewrite in another language for speed or deployment. \textbackslash item There are parts of a system appropriate for the programmer, and other parts that are best left untouched as they have been built by the experts. \textbackslash endlist We introduce the Julia programming language and its design---a dance between specialization and abstraction. Specialization allows for custom treatment. Multiple dispatch, a technique from computer science, picks the right algorithm for the right circumstance. Abstraction, which is what good computation is really about, recognizes what remains the same after differences are stripped away. Abstractions in mathematics are captured as code through another technique from computer science, generic programming. Julia shows that one can achieve machine performance without sacrificing human convenience.}, - file = {/Users/milan/Zotero/storage/SZM3ENMR/Bezanson et al. - 2017 - Julia A Fresh Approach to Numerical Computing.pdf;/Users/milan/Zotero/storage/UG5NFZ28/141000671.html} } @article{Bourke1972, @@ -48,7 +46,6 @@ @article{Bourke1972 doi = {10.1175/1520-0493(1972)100<0683:AEOPSM>2.3.CO;2}, urldate = {2022-01-07}, langid = {english}, - file = {/Users/milan/Zotero/storage/29QHT8QP/Bourke - 1972 - An Efficient, One-Level, Primitive-Equation Spectr.pdf} } @article{Burns2020, @@ -65,7 +62,6 @@ @article{Burns2020 doi = {10.1103/PhysRevResearch.2.023068}, urldate = {2023-09-14}, abstract = {Numerical solutions of partial differential equations enable a broad range of scientific research. The Dedalus project is a flexible, open-source, parallelized computational framework for solving general partial differential equations using spectral methods. Dedalus translates plain-text strings describing partial differential equations into efficient solvers. This paper details the numerical method that enables this translation, describes the design and implementation of the codebase, and illustrates its capabilities with a variety of example problems. The numerical method is a first-order generalized tau formulation that discretizes equations into banded matrices. This method is implemented with an object-oriented design. Classes for spectral bases and domains manage the discretization and automatic parallel distribution of variables. Discretized fields and mathematical operators are symbolically manipulated with a basic computer algebra system. Initial value, boundary value, and eigenvalue problems are efficiently solved using high-performance linear algebra, transform, and parallel communication libraries. Custom analysis outputs can also be specified in plain text and stored in self-describing portable formats. The performance of the code is evaluated with a parallel scaling benchmark and a comparison to a finite-volume code. The features and flexibility of the codebase are illustrated by solving several examples: the nonlinear Schr\"odinger equation on a graph, a supersonic magnetohydrodynamic vortex, quasigeostrophic flow, Stokes flow in a cylindrical annulus, normal modes of a radiative atmosphere, and diamagnetic levitation.}, - file = {/Users/milan/Zotero/storage/D23SMV3X/Burns et al. - 2020 - Dedalus A flexible framework for numerical simula.pdf;/Users/milan/Zotero/storage/NRZ7F4CI/PhysRevResearch.2.html} } @manual{Cartopy, @@ -89,7 +85,6 @@ @article{Corby1972 urldate = {2023-03-07}, abstract = {The design of a general circulation model using the primitive equations in spherical form is described, including a statement of the finite difference forms used to integrate the system and explanations of the motives for unusual aspects of the finite difference scheme. The model incorporates the hydrological cycle, topography, a simple scheme for the radiative exchanges and arrangements for the simulation of deep free convection (sub grid-scale) and for the representation of exchanges of momentum, sensible and latent heat with the underlying surface. An experiment performed with the model forms the subject of a separate paper.}, langid = {english}, - file = {/Users/milan/Zotero/storage/VTBQF9B7/Corby et al. - 1972 - A general circulation model of the atmosphere suit.pdf;/Users/milan/Zotero/storage/LMC9D2VS/qj.html} } @article{Gorski2005, @@ -107,7 +102,6 @@ @article{Gorski2005 doi = {10.1086/427976}, urldate = {2023-09-14}, langid = {english}, - file = {/Users/milan/Zotero/storage/GGI4L9QV/Górski et al. - 2005 - HEALPix A Framework for High-Resolution Discretiz.pdf} } @article{Held1994, @@ -126,7 +120,6 @@ @article{Held1994 abstract = {A benchmark calculation is proposed for evaluating the dynamical cores of atmospheric general circulation models independently of the physical parameterizations. The test focuses on the long-term statistical properties of a fully developed general circulation; thus, it is particularly appropriate for intercomparing the dynamics used in climate models. To illustrate the use of this benchmark, two very different atmospheric dynamical cores\textemdash one spectral, one finite difference\textemdash are compared. It is found that the long-term statistics produced by the two models are very similar. Selected results from these calculations are presented to initiate the intercomparison.}, chapter = {Bulletin of the American Meteorological Society}, langid = {english}, - file = {/Users/milan/Zotero/storage/NUBBDSUA/Held and Suarez - 1994 - A Proposal for the Intercomparison of the Dynamica.pdf;/Users/milan/Zotero/storage/NXJH4Q6M/1520-0477_1994_075_1825_apftio_2_0_co_2.html} } @article{Hoskins1975, @@ -142,7 +135,6 @@ @article{Hoskins1975 urldate = {2023-03-03}, abstract = {The formulaton of a multi-layer primitive equation model on the sphere is described. The horizontal representation is by means of spherical harmonics, truncated either in the triangular or rhomboidal manner. The time integration is performed using the semi-implicit method in which the linearized gravity wave terms are time averaged and thus the fast moving waves of this type are slowed. For a 5-layer hemispheric model with triangular truncation at wavenumber 21, storage of 38K words is needed and with the time scheme allowing a time-step of 90 minutes, one day's simulation requires 11 seconds of CDC 7600 time. The growth of a baroclinic wave on a simple basic state of differential solid body rotation is exhibited. The errors involved in this case in utilizing the large time-step allowed by the semi-implicit scheme are thoroughly examined by comparing wave amplitudes and phases, conservation properties and gravity wave treatment for different time-steps. These errors are found to be negligible. The conservation properties of the model are in fact extremely good. The vertical finite differencing scheme of Arakawa is studied in the same baroclinic instability simulation. The growth is similar though the conservation of angular momentum is greatly improved. The transform method used in all these integrations allows some aliasing, but this is shown to be negligible.}, langid = {english}, - file = {/Users/milan/Zotero/storage/HFWTWI7A/Hoskins and Simmons - 1975 - A multi-layer spectral model and the semi-implicit.pdf;/Users/milan/Zotero/storage/4Y43KN5T/qj.html} } @article{Hotta2018, @@ -159,7 +151,6 @@ @article{Hotta2018 abstract = {A new grid system on a sphere is proposed which allows for straightforward implementation of both spherical-harmonics-based spectral methods and gridpoint-based multigrid methods. The latitudinal gridpoints in the new grid are equidistant and spectral transforms in the latitudinal direction are performed using Clenshaw\textendash Curtis quadrature. The spectral transforms with this new grid and quadrature are shown to be exact within machine precision provided that the grid truncation is such that there are at least 2N + 1 latitudinal gridpoints for the total truncation wavenumber of N. The new grid and quadrature is implemented and tested on a shallow-water equations model and the hydrostatic dry dynamical core of the global NWP model JMA-GSM. The integration results obtained with the new quadrature are shown to be almost identical to those obtained with the conventional Gaussian quadrature on a Gaussian grid. Only minor code changes are required to adapt any Gaussian-based spectral models to employ the proposed quadrature.}, langid = {english}, keywords = {Clenshaw\textendash Curtis quadrature,Fej\'er quadrature,global spectral model,Legendre transform,multigrid}, - file = {/Users/milan/Zotero/storage/5HXBNCQW/Hotta and Ujiie - 2018 - A nestable, multigrid-friendly grid on a sphere fo.pdf;/Users/milan/Zotero/storage/J5BN2ENU/qj.html} } @article{Hunter2007, @@ -176,7 +167,6 @@ @article{Hunter2007 doi = {10.1109/MCSE.2007.55}, abstract = {Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operating systems}, keywords = {application development,Computer languages,Equations,Graphical user interfaces,Graphics,Image generation,Interpolation,Operating systems,Packaging,Programming profession,Python,scientific programming,scripting languages,User interfaces}, - file = {/Users/milan/Zotero/storage/6YGLJIB7/Hunter - 2007 - Matplotlib A 2D Graphics Environment.pdf} } @article{Jablonowski2006, @@ -193,7 +183,6 @@ @article{Jablonowski2006 urldate = {2023-03-22}, abstract = {A deterministic initial-value test case for dry dynamical cores of atmospheric general-circulation models is presented that assesses the evolution of an idealized baroclinic wave in the northern hemisphere. The initial zonal state is quasi-realistic and completely defined by analytic expressions which are a steady-state solution of the adiabatic inviscid primitive equations with pressure-based vertical coordinates. A two-component test strategy first evaluates the ability of the discrete approximations to maintain the steady-state solution. Then an overlaid perturbation is introduced which triggers the growth of a baroclinic disturbance over the course of several days.}, langid = {english}, - file = {/Users/milan/Zotero/storage/VH7SAZC2/Jablonowski and Williamson - 2006 - A baroclinic instability test case for atmospheric.pdf} } @article{Klower2020, @@ -204,7 +193,7 @@ @article{Klower2020 number = {10}, pages = {e2020MS002246}, keywords = {Reduced precision, 16-bit arithmetic, climate models, rounding error, floating-point numbers, posit numbers}, -doi = {https://doi.org/10.1029/2020MS002246}, +doi = {10.1029/2020MS002246}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020MS002246}, eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2020MS002246}, note = {e2020MS002246 10.1029/2020MS002246}, @@ -227,7 +216,6 @@ @article{Klower2022 abstract = {Most Earth-system simulations run on conventional central processing units in 64-bit double precision floating-point numbers Float64, although the need for high-precision calculations in the presence of large uncertainties has been questioned. Fugaku, currently the world's fastest supercomputer, is based on A64FX microprocessors, which also support the 16-bit low-precision format Float16. We investigate the Float16 performance on A64FX with ShallowWaters.jl, the first fluid circulation model that runs entirely with 16-bit arithmetic. The model implements techniques that address precision and dynamic range issues in 16 bits. The precision-critical time integration is augmented to include compensated summation to minimize rounding errors. Such a compensated time integration is as precise but faster than mixed precision with 16 and 32-bit floats. As subnormals are inefficiently supported on A64FX the very limited range available in Float16 is 6 \texttimes{} 10-5 to 65,504. We develop the analysis-number format Sherlogs.jl to log the arithmetic results during the simulation. The equations in ShallowWaters.jl are then systematically rescaled to fit into Float16, using 97\% of the available representable numbers. Consequently, we benchmark speedups of up to 3.8x on A64FX with Float16. Adding a compensated time integration, speedups reach up to 3.6x. Although ShallowWaters.jl is simplified compared to large Earth-system models, it shares essential algorithms and therefore shows that 16-bit calculations are indeed a competitive way to accelerate Earth-system simulations on available hardware.}, langid = {english}, keywords = {climate models,floating-point numbers,hardware acceleration,low precision,rounding errors}, - file = {/Users/milan/Zotero/storage/68GUS3P9/Klöwer et al. - 2022 - Fluid Simulations Accelerated With 16 Bits Approa.pdf;/Users/milan/Zotero/storage/R4EELGQV/2021MS002684.html} } @article{Kucharski2013, @@ -246,7 +234,6 @@ @article{Kucharski2013 abstract = {"On the Need of Intermediate Complexity General Circulation Models: A ``SPEEDY'' Example" published on Jan 2013 by American Meteorological Society.}, chapter = {Bulletin of the American Meteorological Society}, langid = {english}, - file = {/Users/milan/Zotero/storage/N8YS452F/Kucharski et al. - 2013 - On the Need of Intermediate Complexity General Cir.pdf} } @misc{Malardel2016, @@ -256,7 +243,6 @@ @misc{Malardel2016 journal = {ECMWF Newsletter}, abstract = {ECMWF will implement a resolution upgrade for high-resolution forecasts (HRES) and ensemble forecasts (ENS) in spring 2016. HRES will then be run on a grid with a grid-point distance between neighbouring points of approximately 9 km instead of 16 km in the current configuration.}, howpublished = {https://www.ecmwf.int/node/15041}, - file = {/Users/milan/Zotero/storage/RTX8TJ4K/A-new-grid-for-the-IFS.pdf} } @article{Molteni2003, @@ -275,7 +261,6 @@ @article{Molteni2003 abstract = {This work describes the formulation and climatology of an atmospheric general circulation model (GCM) of intermediate complexity, based on a spectral primitive-equation dynamical core and a set of simplified physical parametrization schemes. The parametrization package has been specially designed to work in models with just a few vertical levels, and is based on the same physical principles adopted in the schemes of state-of-the art GCMs. The parametrized processes include large-scale condensation, convection, clouds, short-wave and long-wave radiation, surface fluxes and vertical diffusion. In the current configuration, the model (nicknamed SPEEDY, from Simplified Parametrizations, primitivE-Equation DYnamics") has five vertical levels and a spectral truncation at total wave number 30 (T30L5). The top vertical level (crudely) represents the stratosphere, the bottom one the planetary boundary layer. Computationally, SPEEDY requires (at least) one order of magnitude less CPU time than a state-of-the-art GCM at the same horizontal resolution, and is therefore suitable for studies of inter-decadal or inter-centennial variability. Statistics of the model mean state and variability are computed from an ensemble of 41-year simulations forced by observed sea-surface temperatures in the period 1952\textendash 1992. The model mean state is closer to the observed climatology during the (boreal) winter than during summer. In winter (i.e. December to February, DJF), the model underestimates the amplitude of the Northern Hemisphere stationary wave pattern, particularly in the European-Atlantic sector. Some aspects of the systematic error of SPEEDY are in fact typical of many GCMs, although the error amplitude is stronger than in state-of-the-art models. On the other hand, the global distribution of precipitation in DJF is quite realistic, and compares well with that of more complex GCMs. In summer (June to August), a strong negative bias in the mid-tropospheric temperature generates a Northern Hemisphere circulation with some springtime characteristics. In particular, the position of the Tropical Convergence Zone in the Indian Ocean remains too far south, leading to a deficient simulation of the monsoon circulation over South Asia. The simulated variability during the northern winter is reasonably realistic as far as the spatial distribution is concerned, although some underestimation in the intensity can be found, particularly in the low-frequency range and in the Atlantic sector. The atmospheric response to ENSO events is also weaker than observed, although the spatial patterns of the rainfall and geopotential response in the Pacific sector are in phase with their observed counterparts. In the Atlantic/Eurasian region, the spatial patterns associated with the interdecadal trends in the simulated and observed large-scale circulation show a clear positive correlation, consistent with the hypothesis of a positive ocean\textendash atmosphere feedback on decadal time scales.}, langid = {english}, keywords = {Atmospheric General Circulation Model,ENSO Event,General Circulation Model,Planetary Boundary Layer,Vertical Level}, - file = {/Users/milan/Zotero/storage/22FVB5QT/Molteni - 2003 - Atmospheric simulations using a GCM with simplifie.pdf} } @article{Nakano2018, @@ -295,7 +280,6 @@ @article{Nakano2018 abstract = {{$<$}section class="abstract"{$><$}h2 class="abstractTitle text-title my-1" id="d145702010e111"{$>$}Abstract{$<$}/h2{$><$}p{$>$}Reducing the computational cost of weather and climate simulations would lower electric energy consumption. From the standpoint of reducing costs, the use of reduced precision arithmetic has become an active area of research. Here the impact of using single-precision arithmetic on simulation accuracy is examined by conducting Jablonowski and Williamson's baroclinic wave tests using the dynamical core of a global fully compressible nonhydrostatic model. The model employs a finite-volume method discretized on an icosahedral grid system and its mesh size is set to 220, 56, 14, and 3.5 km. When double-precision arithmetic is fully replaced by single-precision arithmetic, a spurious wavenumber-5 structure becomes dominant in both hemispheres, rather than the expected baroclinic wave growth only in the Northern Hemisphere. It was found that this spurious wave growth comes from errors in the calculation of gridcell geometrics. Therefore, an additional simulation was conducted using double precision for calculations that only need to be performed for model setup, including calculation of gridcell geometrics, and single precision everywhere else, meaning that all calculations performed each time step used single precision. In this case, the model successfully simulated the growth of the baroclinic wave with only small errors and a 46\% reduction in runtime. These results suggest that the use of single-precision arithmetic will allow significant reduction of computational costs in next-generation weather and climate simulations using a fully compressible nonhydrostatic global model with the finite-volume method.{$<$}/p{$><$}/section{$>$}}, chapter = {Monthly Weather Review}, langid = {english}, - file = {/Users/milan/Zotero/storage/XE4CRLDK/Nakano et al. - 2018 - Single Precision in the Dynamical Core of a Nonhyd.pdf;/Users/milan/Zotero/storage/A966XWT3/mwr-d-17-0257.1.html} } @article{Ramadhan2020, @@ -313,7 +297,6 @@ @article{Ramadhan2020 urldate = {2023-09-14}, abstract = {Ramadhan et al., (2020). Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs. Journal of Open Source Software, 5(53), 2018, https://doi.org/10.21105/joss.02018}, langid = {english}, - file = {/Users/milan/Zotero/storage/UBSRFFJG/Ramadhan et al. - 2020 - Oceananigans.jl Fast and friendly geophysical flu.pdf} } @article{Rasp2018, @@ -325,7 +308,6 @@ @article{Rasp2018 volume = {115}, number = {39}, pages = {9684--9689}, - file = {/Users/milan/Zotero/storage/4FW52IRQ/9684.html} } @article{Schneider2023, @@ -345,7 +327,6 @@ @article{Schneider2023 copyright = {2023 Springer Nature Limited}, langid = {english}, keywords = {Climate and Earth system modelling,Projection and prediction}, - file = {/Users/milan/Zotero/storage/Q8DTJ4NT/Schneider et al. - 2023 - Harnessing AI and computing to advance climate mod.pdf} } @article{Simmons1978, @@ -364,7 +345,6 @@ @article{Simmons1978 abstract = {Abstract The stability of the semi-implicit method of time integration of the primitive equations is examined when the actual temperature deviates from the reference profile about which the implicitly treated gravity wave terms are linearized. The stability criterion is shown in general to be much more stringent than might he assumed from a simple analytical solution. Instability may occur when there exists a region in which the static stability of the actual atmosphere differs significantly from that of the reference atmosphere, and for realistic actual profiles and commonly chosen reference profiles it is likely to arise at vertical resolutions that are little higher than those used in previous tests of the scheme. Stabilization is achieved either by an appropriate change of reference profile or by a modification of the time-averaging of gravity wave terms. Both may result in a small further reduction in gravity wave phase speeds. Alternatives are mentioned which give better phase speeds at the expense of a reduced time step.}, chapter = {Monthly Weather Review}, langid = {english}, - file = {/Users/milan/Zotero/storage/A2NGNVRV/Simmons et al. - 1978 - Stability of the Semi-Implicit Method of Time Inte.pdf} } @article{Simmons1981, @@ -383,7 +363,6 @@ @article{Simmons1981 abstract = {Abstract An energy and angular-momentum conserving vertical finite-difference scheme is introduced for a general terrain-following vertical coordinate which is a function of pressure and its surface value. A corresponding semi-implicit time scheme is also defined. These schemes am used to compare the usual sigma coordinate with the hybrid coordinate which reduces to pressure above a fixed level and with a modified hybrid coordinate which tends uniformly to pressure at upper levels. Error in the representation of the stratospheric pressure gradient over steep orography can be significantly reduced by use of the hybrid coordinate but the semi-implicit scheme is less stable. The modified hybrid coordinate offers a useful compromise.}, chapter = {Monthly Weather Review}, langid = {english}, - file = {/Users/milan/Zotero/storage/WHTSRU3P/Simmons and Burridge - 1981 - An Energy and Angular-Momentum Conserving Vertical.pdf} } @article{Vana2017, @@ -418,7 +397,6 @@ @article{Williams2011 urldate = {2021-12-17}, abstract = {Errors caused by discrete time stepping may be an important component of total model error in contemporary atmospheric and oceanic simulations. To reduce time-stepping errors in leapfrog integrations, the Robert\textendash Asselin\textendash Williams (RAW) filter was proposed by the author as a simple improvement to the widely used Robert\textendash Asselin (RA) filter. The present paper examines the behavior of the RAW filter in semi-implicit integrations. First, in a linear theoretical analysis, the stability and accuracy are interrogated by deriving analytic expressions for the amplitude errors and phase errors. Then, power-series expansions are used to interpret the leading-order errors for small time steps and hence to identify optimal values of the filter parameters. Finally, the RAW filter is tested in a realistic nonlinear setting, by applying it to semi-implicit integrations of the elastic pendulum equations. The results suggest that replacing the RA filter with the RAW filter could reduce time-stepping errors in semi-implicit integrations.}, langid = {english}, - file = {/Users/milan/Zotero/storage/YS2LGST8/Williams - 2011 - The RAW Filter An Improvement to the Robert–Assel.pdf} } @misc{Innes2019, @@ -435,7 +413,6 @@ @misc{Innes2019 abstract = {Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large amounts of data. At the same time, machine learning models are becoming increasingly sophisticated and exhibit many features often seen in scientific computing, stressing the capabilities of machine learning frameworks. Just as the disciplines of scientific computing and machine learning have shared common underlying infrastructure in the form of numerical linear algebra, we now have the opportunity to further share new computational infrastructure, and thus ideas, in the form of Differentiable Programming. We describe Zygote, a Differentiable Programming system that is able to take gradients of general program structures. We implement this system in the Julia programming language. Our system supports almost all language constructs (control flow, recursion, mutation, etc.) and compiles high-performance code without requiring any user intervention or refactoring to stage computations. This enables an expressive programming model for deep learning, but more importantly, it enables us to incorporate a large ecosystem of libraries in our models in a straightforward way. We discuss our approach to automatic differentiation, including its support for advanced techniques such as mixed-mode, complex and checkpointed differentiation, and present several examples of differentiating programs.}, archiveprefix = {arxiv}, keywords = {Computer Science - Machine Learning,Computer Science - Programming Languages}, - file = {/Users/milan/Zotero/storage/VY5339JF/Innes et al. - 2019 - A Differentiable Programming System to Bridge Mach.pdf;/Users/milan/Zotero/storage/CZ4BXQCY/1907.html} } @inproceedings{Moses2020, @@ -448,7 +425,6 @@ @inproceedings{Moses2020 publisher = {{Curran Associates, Inc.}}, urldate = {2023-09-15}, abstract = {Applying differentiable programming techniques and machine learning algorithms to foreign programs requires developers to either rewrite their code in a machine learning framework, or otherwise provide derivatives of the foreign code. This paper presents Enzyme, a high-performance automatic differentiation (AD) compiler plugin for the LLVM compiler framework capable of synthesizing gradients of statically analyzable programs expressed in the LLVM intermediate representation (IR). Enzyme synthesizes gradients for programs written in any language whose compiler targets LLVM IR including C, C++, Fortran, Julia, Rust, Swift, MLIR, etc., thereby providing native AD capabilities in these languages. Unlike traditional source-to-source and operator-overloading tools, Enzyme performs AD on optimized IR. On a machine-learning focused benchmark suite including Microsoft's ADBench, AD on optimized IR achieves a geometric mean speedup of 4.2 times over AD on IR before optimization allowing Enzyme to achieve state-of-the-art performance. Packaging Enzyme for PyTorch and TensorFlow provides convenient access to gradients of foreign code with state-of-the-art performance, enabling foreign code to be directly incorporated into existing machine learning workflows.}, - file = {/Users/milan/Zotero/storage/Y9ZTEWXC/Moses and Churavy - 2020 - Instead of Rewriting Foreign Code for Machine Lear.pdf} } @@ -485,8 +461,7 @@ @article{Rose2018 doi = {10.21105/joss.00659}, urldate = {2023-09-29}, abstract = {Rose, (2018). CLIMLAB: a Python toolkit for interactive, process-oriented climate modeling. Journal of Open Source Software, 3(24), 659, https://doi.org/10.21105/joss.00659}, - langid = {english}, - file = {/Users/milan/Zotero/storage/25RBWXLV/Rose - 2018 - CLIMLAB a Python toolkit for interactive, process.pdf} + langid = {english} } @article{reinecke2013, From a8235e12be6e312b087cd059cc6dfbe743ab4deb Mon Sep 17 00:00:00 2001 From: milankl Date: Wed, 6 Dec 2023 11:31:07 +0000 Subject: [PATCH 60/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1461146 -> 1461131 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index a4ea1dfbab981771c36a2584bd4c2eb054fe1d1c..40fc863b0e24f239f09630bef4e136faadcff069 100644 GIT binary patch delta 2462 zcmaizX*kr20>&+4H$(1_r9$?77=zJ}eaSKm!pJ(d9P5xGHR7+SRMt!-O2-z4WEl(w znJmXvNC*kpvQ0FZEcbl4&wZYAzuZsn`@Fy3*Y_#OGo9p_46p+n04D$fxBzZ|2jB(x z0DeFK5Cp&g1P}s*ffIlT@UMF4gb9b9E~%3$3Z-nAK>rjbAp3WdGoS)ITXw3-lNL!Imr=KS(r|7R{A!rA?$rUq7q5C;5{e3~w%hV* zf<_!88?sUe&{%?eliFTuQL(7cjvV#s$^9G)C5D6*K|eSz@kBv@{>!-es$PrvNVS&%ERa{7zw{=dK*a7w@!Cf(u2F>%R`*? 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D.}, year = {2011}, month = feb, journal = {Monthly Weather Review}, @@ -19,7 +19,7 @@ @article{Amezcua2011 @article{Bezanson2017, title = {Julia: {{A Fresh Approach}} to {{Numerical Computing}}}, shorttitle = {Julia}, - author = {Bezanson, {\relax Jeff}. and Edelman, {\relax Alan}. and Karpinski, {\relax Stefan}. and Shah, Viral B.}, + author = {Bezanson, J. and Edelman, A. and Karpinski, S. and Shah, V. B.}, year = {2017}, month = jan, journal = {SIAM Review}, @@ -35,7 +35,7 @@ @article{Bezanson2017 @article{Bourke1972, title = {An {{Efficient}}, {{One-Level}}, {{Primitive-Equation Spectral Model}}}, - author = {Bourke, William}, + author = {Bourke, W.}, year = {1972}, month = sep, journal = {Monthly Weather Review}, @@ -51,7 +51,7 @@ @article{Bourke1972 @article{Burns2020, title = {Dedalus: {{A}} Flexible Framework for Numerical Simulations with Spectral Methods}, shorttitle = {Dedalus}, - author = {Burns, Keaton J. and Vasil, Geoffrey M. and Oishi, Jeffrey S. and Lecoanet, Daniel and Brown, Benjamin P.}, + author = {Burns, K. J. and Vasil, G. M. and Oishi, J. S. and Lecoanet, D. and Brown, B. P.}, year = {2020}, month = apr, journal = {Physical Review Research}, @@ -106,7 +106,7 @@ @article{Gorski2005 @article{Held1994, title = {A {{Proposal}} for the {{Intercomparison}} of the {{Dynamical Cores}} of {{Atmospheric General Circulation Models}}}, - author = {Held, Isaac M. and Suarez, Max J.}, + author = {Held, I. M. and Suarez, M. J.}, year = {1994}, month = oct, journal = {Bulletin of the American Meteorological Society}, @@ -139,7 +139,7 @@ @article{Hoskins1975 @article{Hotta2018, title = {A Nestable, Multigrid-Friendly Grid on a Sphere for Global Spectral Models Based on {{Clenshaw}}\textendash{{Curtis}} Quadrature}, - author = {Hotta, Daisuke and Ujiie, Masashi}, + author = {Hotta, D. and Ujiie, M.}, year = {2018}, journal = {Quarterly Journal of the Royal Meteorological Society}, volume = {144}, @@ -156,7 +156,7 @@ @article{Hotta2018 @article{Hunter2007, title = {Matplotlib: {{A 2D Graphics Environment}}}, shorttitle = {Matplotlib}, - author = {Hunter, John D.}, + author = {Hunter, J. D.}, year = {2007}, month = may, journal = {Computing in Science \& Engineering}, @@ -171,7 +171,7 @@ @article{Hunter2007 @article{Jablonowski2006, title = {A Baroclinic Instability Test Case for Atmospheric Model Dynamical Cores}, - author = {Jablonowski, Christiane and Williamson, David L.}, + author = {Jablonowski, C. and Williamson, D. L.}, year = {2006}, month = oct, journal = {Quarterly Journal of the Royal Meteorological Society}, @@ -204,7 +204,7 @@ @article{Klower2020 @article{Klower2022, title = {Fluid {{Simulations Accelerated With}} 16 {{Bits}}: {{Approaching}} 4x {{Speedup}} on {{A64FX}} by {{Squeezing ShallowWaters}}.Jl {{Into Float16}}}, shorttitle = {Fluid {{Simulations Accelerated With}} 16 {{Bits}}}, - author = {Kl{\"o}wer, Milan and Hatfield, Sam and Croci, Matteo and D{\"u}ben, Peter D. and Palmer, Tim N.}, + author = {Kl{\"o}wer, M. and Hatfield, S. and Croci, M. and D{\"u}ben, P. D. and Palmer, T. N.}, year = {2022}, journal = {Journal of Advances in Modeling Earth Systems}, volume = {14}, @@ -221,7 +221,7 @@ @article{Klower2022 @article{Kucharski2013, title = {On the {{Need}} of {{Intermediate Complexity General Circulation Models}}: {{A}} ``{{SPEEDY}}'' {{Example}}}, shorttitle = {On the {{Need}} of {{Intermediate Complexity General Circulation Models}}}, - author = {Kucharski, Fred and Molteni, Franco and King, Martin P. and Farneti, Riccardo and Kang, In-Sik and Feudale, Laura}, + author = {Kucharski, F. and Molteni, F. and King, M. P. and Farneti, R. and Kang, I.-S. and Feudale, L.}, year = {2013}, month = jan, journal = {Bulletin of the American Meteorological Society}, @@ -238,7 +238,7 @@ @article{Kucharski2013 @misc{Malardel2016, title = {A New Grid for the {{IFS}}}, - author = {Malardel, Sylvie and Wedi, Nils and Deconinck, Nils and Diamantakis, Michail and Kuehnlein, Christian and Mozdzynski, George and Hamrud, Mats and Smolarkiewicz, Piotr}, + author = {Malardel, S. and Wedi, N. and Deconinck, N. and Diamantakis, M. and Kuehnlein, C. and Mozdzynski, G. and Hamrud, M. and Smolarkiewicz, P.}, year = {2016}, journal = {ECMWF Newsletter}, abstract = {ECMWF will implement a resolution upgrade for high-resolution forecasts (HRES) and ensemble forecasts (ENS) in spring 2016. HRES will then be run on a grid with a grid-point distance between neighbouring points of approximately 9 km instead of 16 km in the current configuration.}, @@ -266,7 +266,7 @@ @article{Molteni2003 @article{Nakano2018, title = {Single {{Precision}} in the {{Dynamical Core}} of a {{Nonhydrostatic Global Atmospheric Model}}: {{Evaluation Using}} a {{Baroclinic Wave Test Case}}}, shorttitle = {Single {{Precision}} in the {{Dynamical Core}} of a {{Nonhydrostatic Global Atmospheric Model}}}, - author = {Nakano, Masuo and Yashiro, Hisashi and Kodama, Chihiro and Tomita, Hirofumi}, + author = {Nakano, M. and Yashiro, H. and Kodama, C. and Tomita, H.}, year = {2018}, month = feb, journal = {Monthly Weather Review}, @@ -285,7 +285,7 @@ @article{Nakano2018 @article{Ramadhan2020, title = {Oceananigans.Jl: {{Fast}} and Friendly Geophysical Fluid Dynamics on {{GPUs}}}, shorttitle = {Oceananigans.Jl}, - author = {Ramadhan, Ali and Wagner, Gregory LeClaire and Hill, Chris and Campin, Jean-Michel and Churavy, Valentin and Besard, Tim and Souza, Andre and Edelman, Alan and Ferrari, Raffaele and Marshall, John}, + author = {Ramadhan, A. and Wagner, G. L. and Hill, C. and Campin, J.-M. and Churavy, V. and Besard, T. and Souza, A. and Edelman, A. and Ferrari, R. and Marshall, J.}, year = {2020}, month = sep, journal = {Journal of Open Source Software}, @@ -301,7 +301,7 @@ @article{Ramadhan2020 @article{Rasp2018, title = {Deep Learning to Represent Subgrid Processes in Climate Models}, - author = {Rasp, Stephan and Pritchard, Michael S. and Gentine, Pierre}, + author = {Rasp, S. and Pritchard, M. S. and Gentine, P.}, year = {2018}, month = sep, journal = {Proceedings of the National Academy of Sciences}, @@ -312,7 +312,7 @@ @article{Rasp2018 @article{Schneider2023, title = {Harnessing {{AI}} and Computing to Advance Climate Modelling and Prediction}, - author = {Schneider, Tapio and Behera, Swadhin and Boccaletti, Giulio and Deser, Clara and Emanuel, Kerry and Ferrari, Raffaele and Leung, L. Ruby and Lin, Ning and M{\"u}ller, Thomas and Navarra, Antonio and Ndiaye, Ousmane and Stuart, Andrew and Tribbia, Joseph and Yamagata, Toshio}, + author = {Schneider, T. and Behera, S. and Boccaletti, G. and Deser, C. and Emanuel, K. and Ferrari, R. and Leung, L. R. and Lin, N. and M{\"u}ller, T. and Navarra, A. and Ndiaye, O. and Stuart, A. and Tribbia, J. and Yamagata, T.}, year = {2023}, month = sep, journal = {Nature Climate Change}, @@ -368,7 +368,7 @@ @article{Simmons1981 @article{Vana2017, title = {Single {{Precision}} in {{Weather Forecasting Models}}: {{An Evaluation}} with the {{IFS}}}, shorttitle = {Single {{Precision}} in {{Weather Forecasting Models}}}, - author = {V{\'a}{\v n}a, Filip and D{\"u}ben, Peter and Lang, Simon and Palmer, Tim and Leutbecher, Martin and Salmond, Deborah and Carver, Glenn}, + author = {V{\'a}{\v n}a, F. and D{\"u}ben, P. and Lang, S. and Palmer, T. and Leutbecher, M. and Salmond, D. and Carver, G.}, year = {2017}, month = feb, journal = {Monthly Weather Review}, @@ -385,7 +385,7 @@ @article{Vana2017 @article{Williams2011, title = {The {{RAW Filter}}: {{An Improvement}} to the {{Robert}}\textendash{{Asselin Filter}} in {{Semi-Implicit Integrations}}}, shorttitle = {The {{RAW Filter}}}, - author = {Williams, Paul D.}, + author = {Williams, P. D.}, year = {2011}, month = jun, journal = {Monthly Weather Review}, @@ -401,7 +401,7 @@ @article{Williams2011 @misc{Innes2019, title = {A {{Differentiable Programming System}} to {{Bridge Machine Learning}} and {{Scientific Computing}}}, - author = {Innes, Mike and Edelman, Alan and Fischer, Keno and Rackauckas, Chris and Saba, Elliot and Shah, Viral B. and Tebbutt, Will}, + author = {Innes, M. and Edelman, A. and Fischer, K. and Rackauckas, C. and Saba, E. and Shah, V. B. and Tebbutt, W.}, year = {2019}, month = jul, number = {arXiv:1907.07587}, @@ -418,7 +418,7 @@ @misc{Innes2019 @inproceedings{Moses2020, title = {Instead of {{Rewriting Foreign Code}} for {{Machine Learning}}, {{Automatically Synthesize Fast Gradients}}}, booktitle = {Advances in {{Neural Information Processing Systems}}}, - author = {Moses, William and Churavy, Valentin}, + author = {Moses, W. and Churavy, V.}, year = {2020}, volume = {33}, pages = {12472--12485}, @@ -433,14 +433,14 @@ @article{Meyer2022a year = {2022}, volume = {14}, number = {3}, - author = {David Meyer and Sue Grimmond and Peter Dueben and Robin Hogan and Maarten van Reeuwijk}, + author = {Meyer, D. and Grimmond, S. and Dueben, P. and Hogan, R. and van Reeuwijk, M.}, title = {Machine Learning Emulation of Urban Land Surface Processes}, journal = {Journal of Advances in Modeling Earth Systems} } @phdthesis{Meyer2022b, title = {Machine Learning Emulators for Numerical Weather Prediction—Applications to Parametrization Schemes}, - author = {David Meyer}, + author = {David M.}, year = {2022}, school = {University of Reading}, type = {PhD thesis}, @@ -450,7 +450,7 @@ @phdthesis{Meyer2022b @article{Rose2018, title = {{{CLIMLAB}}: A {{Python}} Toolkit for Interactive, Process-Oriented Climate Modeling}, shorttitle = {{{CLIMLAB}}}, - author = {j Rose, Brian E.}, + author = {Rose, B. E. J.}, year = {2018}, month = apr, journal = {Journal of Open Source Software}, @@ -465,7 +465,7 @@ @article{Rose2018 } @article{reinecke2013, - author = {{Reinecke}, M. and {Seljebotn}, D.~S.}, + author = {Reinecke, M. and Seljebotn, D. S.}, title = "{Libsharp - spherical harmonic transforms revisited}", journal = {Astronomy and Astrophysics}, year = 2013, @@ -482,7 +482,7 @@ @article{reinecke2013 } @misc{stompor2011, - author = {{Stompor}, Radek}, + author = {{Stompor}, R.}, title = "{S2HAT: Scalable Spherical Harmonic Transform Library}", keywords = {Software}, howpublished = {Astrophysics Source Code Library, record ascl:1110.013}, @@ -495,7 +495,7 @@ @misc{stompor2011 } @misc{Willmert2020, - author = {Willmert, Justin}, + author = {Willmert, J.}, title = {Blog Series: Notes on Calculating the Spherical Harmonics}, howpublished = {\url{https://justinwillmert.com/articles/2020/notes-on-calculating-the-spherical-harmonics/}}, year = 2020, From 5d9c3041b6d6077d158e10148d099f0883a1f4ad Mon Sep 17 00:00:00 2001 From: navidcy Date: Thu, 22 Feb 2024 16:04:12 +0000 Subject: [PATCH 62/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1461131 -> 1460961 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git 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zzN2aK(-w86CKWi9P~w$$^g16s8I?t2p3n8GL~}? zKIW#qTN0 zAhBXv?bD>IwCF@h4|B^6?}e6^CR|hhU?# zYt^%!V)hKqcFl!ihKT`|sdKHo(gJz5p8@3G@|GpE$qnOMm~tzkKKU7Om1!!e-& Date: Thu, 22 Feb 2024 11:05:01 -0500 Subject: [PATCH 63/86] Navid's affiliation Co-authored-by: Navid C. 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Constantinou" Date: Thu, 22 Feb 2024 18:08:05 +0200 Subject: [PATCH 65/86] combine affiliations --- docs/joss/paper.md | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 5086548b4..bcf7db804 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -49,7 +49,7 @@ authors: - name: Navid C Constantinou orcid: 0000-0002-8149-4094 - affiliation: 9 + affiliation: 8 - name: Chris Hill affiliation: 1 @@ -69,10 +69,8 @@ affiliations: index: 6 - name: University of Minnesota, Minneapolis, MN, USA index: 7 - - name: University of Melbourne, Australia - index: 8 - name: The University of Melbourne, Parkville, VIC, Australia - index: 9 + index: 8 date: 14 September 2023 bibliography: paper.bib From 5672dd89cd7fe84b468b269f6f2fc9b80f0a2884 Mon Sep 17 00:00:00 2001 From: navidcy Date: Thu, 22 Feb 2024 16:08:57 +0000 Subject: [PATCH 66/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1460969 -> 1460812 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index e24b68efa722724163d2c5a72a495becfcc47ecd..401ccd537817cd1aff3cab9b645dd463141963e2 100644 GIT binary patch delta 12323 zcmajlQ*fnEA2#aP=EOE9wrx#p+tx}lE11|Twrx9^*iI(4lZl-@?|<+8oqh+`{kyBH zPrB+kc&e*UQ*J}Ku}|*^UqL_Car>~9B=uhucsqxGK!9!L z@xE)W$TCwt|F<`4k?la@Pv1l}e!7@oWn=(&PiHOQ?eUn!^?Uu3)5_5!f758nSJS*} zpMA`%5OG%2!1?MjWwE(KxmZtXZt~q>KNY$F&ex-p@Y3#OF6&E;k3KkI9sPQD3v9G zEsmucSqy(0#5F?|`PKKYLAlcJ&TILH z%$x>vP#7>MeRMtw4b9%9e(FfLSGgWM+)Gs%xNg4jEj!O`_otR^MZa0@ppgY6-v1Xy zu|*Ug>$39>A!oL-^8pm6yL_@<^HET}4oQG}?J;k%;||&D+PJf#XWFyKu&b~hS%}oq znhmyCeTM1F43iAUM|Bn?T?;}rR?I#w%$$wGF@ygikf>U%&`4UWuf`??K`ZzYqf|I}$*?@U!xpMLB!` zH6`N*gXdsbwC)PZj<*NY|3z>7mwNGk=YJIz^;i`FfkFQ$?P^PdY1+KFIU`@Dh}*uz`03h^eSPp5@z2de(YN2x9rq>6w&el>%zy zwJz5YaHi-zoYAisJH>>Z6n=@%N52xNM-D*xG2O_l@^R0M^MY%~7?`Zepu|U$`#9|t zSOlq8m4v-^LuafHm+389p;S$Mr!1aq^`0kYw~bm07*c=yrn;hw-H5zwPYiW)P>~>{ zi-hM$krHTbcGm!N-Ep^)c0R!!%??Pxw_tG2>kxy9c~C6MTRxukaN6 zcVG-<)@uNiT<6`{r#rSR)R3D?SSvJ^lae~5!-@_WyP|r)5_qKQnKh$r?T6x zN6V9uY0Idh;qqJ0R|O7k!IrK<2YL9Q`>@{?faL+cVo_#}s8Ej;T&_$Vv01l947chr zAamT_6V&vJ2^2SJpU;$aCk;UL186_xVC2WzpD7FBFxPA-7f}U~A4th$!FU%q~ za#8Q$z8GeNPk8hY43@g)Z+#dEDVzv zjkmDG6Y{*R*+oIQkY;|p);(rgFWZ&Fn1rZOHUzbtN0#eK0zYr8V;ey)8jW3of$^MTTqGNcD5h(QcXJX9m27FOIHbW7 z%@@oFROyR)inO8nugf1qKO)2%y(MSkb+Xx!bx)lYi#1%=ssQhYxlF%7DoR_-VAuNb zWjks`<+YNcN_u;NXIm{u>_=jl2pfKTRTzAQ5QJS9RoWwWjuWy62>~Y)jzCXKd|R0! z@6>>?qWjSdjApk*a!P~Y+XQdI)X4BT&wLl5RET2Kj|pWp>(H^y&r!bJWMf24xwF!7 z$p`69O?O5MNr2ZAiKOh0`;DN)aZBSfeGB5Q!0O&6X*ALTB}r^;lAlq$(E6Hz^2jqP zI^|mkxs@1AO+y6*3RTth*8bCn%{D(|8^8l+$${V|_&Z#`xm(8LEMS_UmC}V*Dz;Tw zCP;xx&xjQ-&$l*hqn1J;xj)VcLsVhk--Bb0Q|FF(FaT98TNu5jmn2Y$CC(d~bX*$( z7zY>d`!!iAJVMhz;R9ep{xE!Tmo*$Q<{cm4{-mUey7mrvSUB$L?&R}}w*#3w4vP1Q z&;YRwHSJZJ(11%Lp{UH(N}oh%(wIr6uRa=dSu>;lDo_l#p!>l6JM$=J1)Og%M*!1* zKi}Q~0lt8}!XyZm{eA6MGe5_{vzVA6ZmV_A9%KD(UbH=mxbojbvK25t=j z4E?SE4#i1&e95>-&LP=xq--7KvV7w22pq&tfQBWlKn;Q1Hs0%|)prp7L+b0x)k2^h zICxkx(vnDW&7q8Egip;ZSpM|NgAv&ik5`rlv)oK7VpKaeXQytHuB4XR^w|&7#9ko+ zJ0M4DhW)F(jC;|8*CY&=;c&ZElLih8|3%D6#@vbVCUadgZYu3Cei_bByA1x^O%s(c z05Ll>r*lRX5v^o%zJyPj^VH>hXPy9Efx0qHMZ6Thua;Q>`h7Igc#Hi8GN^LxULgy~ z6tbvhu8VqJ?E`%*GA6@G+ z)uB$+Wr}Z*a|buH#^85mk@*-ILs1Dxd_aVFQ~N5@T?vIbPD>$PE4fnBC$! zL$^u`Ughoew-R0V{^wyDVwL1lNrvJr>1rFTw2VEGT7v$%u7!d~Sl|UyR`jbU@p3!P z1rB_dYE+C}pJjD;2CAs#*U+rfX!(iYRbZ`{gUiex1bT&!F&8)z38J1QXparUMV+0F zF~fW!RISqMi8-6vnpvx}W>dh7I)_^03;TBPUnLlMMuhhiEL!0M?$oxFC;FZ1)Q_Hh zPBfPjt%{mZh=pts2sfv)&a?prBOqV?Z}VrYbeGnWIH_P8*?c#WvqM#Z9X+j^zUvk! zM>8oI@;6pJ(uB2dUh=*Fln$;-z}%?zX;4b8AI`2e=Z>wK>crx7%Q7c$}WlsaDSD z_lTRdT6zH4nB+c1glcIWi~5_qRo*MctZ{X$#-}LA4$V&ec&h<~6=l8;Hya;2a_|j% ziYa2_GbO@IrxIr%uH@pYf~F8v_&1@3E6O?^2g}& zY;S`W#1SlUJ-TY_Z&JAC#yVSKf+5Ow4O7MatJzS3X`2xf4ScyF*&>WVX@axAT^*0z{fo4_;> zn`fisx@ga*1tLsqRz!R=sgHO3?_3i%yB2?492JAolmzOnaa?|VqS)QP$$@}+`?+J@*lhPAdFd6q%q`9k|)0+#{(Q~|Ke#V>$V`{B7rmqAzetbo~qx~Y%6Ni7dXg~ zZ^x&8jhN%er(E51^E&fb8vOfYZOr$)se~!GIss zhu&`hL=UYm3HRF#T?}50ttuQ{lUaLfeTrC;ov#2Kc!twu(g9fLTFw@&_yqB4OtcQM zDipP0-4CDh+!eXWF<-7Ma>+CbMGDu~J#TFy*I0DQD?EiVeQq2kH0?5i{-nbvx4J7=*idZSZc0 zOj@cRYp(aeq~QKAt08C-^%+fKFSU3aqZtT*SGbBfS21Wz`cBuOC&B^W#h?ZIP~MS3 z-542{UJnZmzd+09Y6Fvq-b~dMu=Yp zxZuoMe$862A~Erpdi@cToinu2xdlU_RCH98>z@g|K;IXekY*h)v8-puJn-{_-g6ru zM3GRf&XZsVh9NA?tEHV4BK#}KC3gL?${j`mzpL+<>f2hFiMy)EUM5=spHI>W z;ZB~9AFH(((-PkOJx|Gl0XT+i@u@dZNqdlZzCVWEQGdtcg`pO|mm$lugq+g8)`U{>0Sh5bZy#;RKR2jN& zhXtF8Nak?hdz=QGLbf>f#6wd79*AgpjVziI2Qp&!2FdY9ry#56!4K&s4x|ZGl`6L* zvT!1@xS}yQspPx+$+JnQtGOPhrmAV7geef#+Ab5909Tr8b$4Q$e~VkJ@YrUTG-D;$ zYeEMf&!)oLk#*u>s$(48`OlTgIL!C0Rw+xenbXXKf_UjAO-2-l(4{>A{O#UG3sNZ? 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zCaVAvX%LkMZuA%Cx>5eqHlYjiDipP0?~{a}2Tqwif>cWzg}bJ~R+|sV59}Z&Q{AyP$GD-~B2_M>jjL-}XlFVI z)dmvmpn9b8Uxz;mo($~W7se72V1UvsJ#qfrfZ~u#89WrTanK|h3T3In1aVR@Q3A^0 zcOSH7Qw^QeFR)J#U4r7E{M2iv5}P=9SD(^UdNCP?y8g{dZO&x89(?L};Ap(6mVH(mB|5?VOS)y-50yUK#!Hr26v173ZAB)FiADSAAMV6*{6m;u5x>6?7_i n>{Gx%|IU>E`{i Date: Thu, 22 Feb 2024 18:13:08 +0200 Subject: [PATCH 67/86] add simone's orcid --- docs/joss/paper.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index bcf7db804..a899ca6cd 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -29,6 +29,7 @@ authors: affiliation: 7 - name: Simone Silvestri + orcid: 0000-0002-7156-946X affiliation: 1 - name: Gregory L Wagner From 5a4e5a4940b6ae0baa1fb158ef8463a7d9b5a96c Mon Sep 17 00:00:00 2001 From: navidcy Date: Thu, 22 Feb 2024 16:14:26 +0000 Subject: [PATCH 68/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1460812 -> 1460892 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git 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addressed --- docs/joss/paper.bib | 13 +++++++++++++ docs/joss/paper.md | 9 +++++---- 2 files changed, 18 insertions(+), 4 deletions(-) diff --git a/docs/joss/paper.bib b/docs/joss/paper.bib index d2af0fb89..5dc2bf1ed 100644 --- a/docs/joss/paper.bib +++ b/docs/joss/paper.bib @@ -243,6 +243,19 @@ @misc{Malardel2016 journal = {ECMWF Newsletter}, abstract = {ECMWF will implement a resolution upgrade for high-resolution forecasts (HRES) and ensemble forecasts (ENS) in spring 2016. HRES will then be run on a grid with a grid-point distance between neighbouring points of approximately 9 km instead of 16 km in the current configuration.}, howpublished = {https://www.ecmwf.int/node/15041}, + doi = {10.21957/zwdu9u5i}, +} + +@INPROCEEDINGS{Mazlami2017, + author={Mazlami, Genc and Cito, Jürgen and Leitner, Philipp}, + booktitle={2017 IEEE International Conference on Web Services (ICWS)}, + title={Extraction of Microservices from Monolithic Software Architectures}, + year={2017}, + volume={}, + number={}, + pages={524-531}, + keywords={Couplings;Clustering algorithms;Computer architecture;Cloud computing;Industries;Tools;microservices;extraction;coupling;graph-based clustering}, + doi={10.1109/ICWS.2017.61}, } @article{Molteni2003, diff --git a/docs/joss/paper.md b/docs/joss/paper.md index a899ca6cd..d23b50e8e 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -73,7 +73,7 @@ affiliations: - name: The University of Melbourne, Parkville, VIC, Australia index: 8 -date: 14 September 2023 +date: 27 March 2024 bibliography: paper.bib --- @@ -105,8 +105,9 @@ experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by the Julia ocean model Oceananigans.jl [@Ramadhan2020]. -A monolithic interface based on parameter files is avoided in favor of a -library-style interface. +A monolithic interface [@Mazlami2017], controlling most of the model's functionality +through arguments of a single function or through parameter files (often called namelists in Fortran), +is avoided in favor of a library-style interface. A model is constructed bottom-up by first defining the discretization and any non-default model components with their respective parameters. All components are then collected into a single model object which, once @@ -217,7 +218,7 @@ who have also committed to the SpeedyWeather.jl repository, and the wider Julia for help and support. MK acknowledges funding from the National Science Foundation. MK and TK acknowledge funding from the European Research Council -under the European Union’s Horizon 2020 research and innovation programme for the ITHACA grant (no. 741112). +under the European Union's Horizon 2020 research and innovation programme for the ITHACA grant (no. 741112). NCC acknowledges support by the Australian Research Council DECRA Fellowship DE210100749. # References From aa936554fb54c9a40b33af9237069c97d8877f30 Mon Sep 17 00:00:00 2001 From: milankl Date: Wed, 27 Mar 2024 22:10:08 +0000 Subject: [PATCH 72/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1460892 -> 1462548 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index ae2fc02abed36a0d1bfa564bdb55d4e8df189509..8d25ff7188746e2a659b1f601791be684641561b 100644 GIT binary patch delta 43370 zcmZUaLv$vYzj&0kvoiDa+c5K_WZM$RZ?{n_@@8k}iwQ8{Uq$XAM?6z-iJFqzTe(xQK%H>NF`^uuf6Oxcybs{I^JY(swgaNy2+_>Hg8}sh_Y#o;#&70I{hO@- zhTiRvz};qZy;q0#=a*p!-w)6C%MfQvPIVZ5vQMs8yPogs&Ai@Q$x*xAmG@_!qwt6y z)}+Q}O&aoQ0j$G}l%8lwD8b9*U>{ilXye5o=qXK~ug%^s)Y3SBP>i*!o#*1lG1ls{ zi(4!USM(oaB}@wyj>J^YN_qCaKb!#ol5*BlF&{o@1cZ%L0ZcvT5Q4AOXZ+BOK5xAH z#(@1(_t$R-06}(CYpr?p6Pdis1TdL}grSaSPa5)s_jPY>iV}v>GaP?`MiTb&YKqf& 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z_1eT^mu;2Jqu7&%)IfE?<9r^?^i*gIDCyRdR)MRI8Q&VOxbw!}HDiAsoDVn1JXw9% YIEDLW2w|f@NJ~pdkn!@W8)%UIKh1F3T>t<8 From eee6555781f5a06072994585f35b8b1e06299a91 Mon Sep 17 00:00:00 2001 From: Milan Date: Fri, 29 Mar 2024 13:21:49 -0400 Subject: [PATCH 73/86] More slayoo's review comments --- docs/joss/paper.bib | 114 +++++++++++++++++++++++++++++++++++++++----- docs/joss/paper.md | 31 +++++++----- 2 files changed, 120 insertions(+), 25 deletions(-) diff --git a/docs/joss/paper.bib b/docs/joss/paper.bib index 5dc2bf1ed..d25c8ca1d 100644 --- a/docs/joss/paper.bib +++ b/docs/joss/paper.bib @@ -72,6 +72,20 @@ @manual{Cartopy url = {https://scitools.org.uk/cartopy} } +@article {CESM, + author = {James W. Hurrell and M. M. Holland and P. R. Gent and S. Ghan and Jennifer E. Kay and P. J. Kushner and J.-F. Lamarque and W. G. Large and D. Lawrence and K. Lindsay and W. H. Lipscomb and M. C. Long and N. Mahowald and D. R. Marsh and R. B. Neale and P. Rasch and S. Vavrus and M. Vertenstein and D. Bader and W. D. Collins and J. J. Hack and J. Kiehl and S. Marshall"}, + title = {The Community Earth System Model: A Framework for Collaborative Research}, + journal = {Bulletin of the American Meteorological Society}, + year = {2013}, + publisher = {American Meteorological Society}, + address = {Boston MA, USA}, + volume = {94}, + number = {9}, + doi = {10.1175/BAMS-D-12-00121.1}, + pages= {1339 - 1360}, + url = {https://journals.ametsoc.org/view/journals/bams/94/9/bams-d-12-00121.1.xml}, +} + @article{Corby1972, title = {A General Circulation Model of the Atmosphere Suitable for Long Period Integrations}, author = {Corby, G. A. and Gilchrist, A. and Newson, R. L.}, @@ -87,6 +101,13 @@ @article{Corby1972 langid = {english}, } +@Manual{Dask, + title = {Dask: Library for dynamic task scheduling}, + author = {{Dask Development Team}}, + year = {2016}, + url = {http://dask.pydata.org}, +} + @article{Gorski2005, title = {{{HEALPix}}: {{A Framework}} for {{High-Resolution Discretization}} and {{Fast Analysis}} of {{Data Distributed}} on the {{Sphere}}}, shorttitle = {{{HEALPix}}}, @@ -169,6 +190,20 @@ @article{Hunter2007 keywords = {application development,Computer languages,Equations,Graphical user interfaces,Graphics,Image generation,Interpolation,Operating systems,Packaging,Programming profession,Python,scientific programming,scripting languages,User interfaces}, } +@article{ICON, + author = {Giorgetta, M. A. and Brokopf, R. and Crueger, T. and Esch, M. and Fiedler, S. and Helmert, J. and Hohenegger, C. and Kornblueh, L. and Köhler, M. and Manzini, E. and Mauritsen, T. and Nam, C. and Raddatz, T. and Rast, S. and Reinert, D. and Sakradzija, M. and Schmidt, H. and Schneck, R. and Schnur, R. and Silvers, L. and Wan, H. and Zängl, G. and Stevens, B.}, + title = {ICON-A, the Atmosphere Component of the ICON Earth System Model: I. Model Description}, + journal = {Journal of Advances in Modeling Earth Systems}, + volume = {10}, + number = {7}, + pages = {1613-1637}, + keywords = {ICON-A, atmospheric GCM, model description, model tuning}, + doi = {10.1029/2017MS001242}, + url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2017MS001242}, + eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2017MS001242}, + year = {2018} +} + @article{Jablonowski2006, title = {A Baroclinic Instability Test Case for Atmospheric Model Dynamical Cores}, author = {Jablonowski, C. and Williamson, D. L.}, @@ -258,6 +293,19 @@ @INPROCEEDINGS{Mazlami2017 doi={10.1109/ICWS.2017.61}, } +@article{MITgcm, +author = {Marshall, John and Adcroft, Alistair and Hill, Chris and Perelman, Lev and Heisey, Curt}, +title = {A finite-volume, incompressible Navier Stokes model for studies of the ocean on parallel computers}, +journal = {Journal of Geophysical Research: Oceans}, +volume = {102}, +number = {C3}, +pages = {5753-5766}, +doi = {https://doi.org/10.1029/96JC02775}, +url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/96JC02775}, +eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/96JC02775}, +year = {1997}, +} + @article{Molteni2003, title = {Atmospheric Simulations Using a {{GCM}} with Simplified Physical Parametrizations. {{I}}: Model Climatology and Variability in Multi-Decadal Experiments}, shorttitle = {Atmospheric Simulations Using a {{GCM}} with Simplified Physical Parametrizations. {{I}}}, @@ -290,11 +338,46 @@ @article{Nakano2018 issn = {1520-0493, 0027-0644}, doi = {10.1175/MWR-D-17-0257.1}, urldate = {2021-06-02}, - abstract = {{$<$}section class="abstract"{$><$}h2 class="abstractTitle text-title my-1" id="d145702010e111"{$>$}Abstract{$<$}/h2{$><$}p{$>$}Reducing the computational cost of weather and climate simulations would lower electric energy consumption. From the standpoint of reducing costs, the use of reduced precision arithmetic has become an active area of research. Here the impact of using single-precision arithmetic on simulation accuracy is examined by conducting Jablonowski and Williamson's baroclinic wave tests using the dynamical core of a global fully compressible nonhydrostatic model. The model employs a finite-volume method discretized on an icosahedral grid system and its mesh size is set to 220, 56, 14, and 3.5 km. When double-precision arithmetic is fully replaced by single-precision arithmetic, a spurious wavenumber-5 structure becomes dominant in both hemispheres, rather than the expected baroclinic wave growth only in the Northern Hemisphere. It was found that this spurious wave growth comes from errors in the calculation of gridcell geometrics. Therefore, an additional simulation was conducted using double precision for calculations that only need to be performed for model setup, including calculation of gridcell geometrics, and single precision everywhere else, meaning that all calculations performed each time step used single precision. In this case, the model successfully simulated the growth of the baroclinic wave with only small errors and a 46\% reduction in runtime. These results suggest that the use of single-precision arithmetic will allow significant reduction of computational costs in next-generation weather and climate simulations using a fully compressible nonhydrostatic global model with the finite-volume method.{$<$}/p{$><$}/section{$>$}}, chapter = {Monthly Weather Review}, langid = {english}, } +@misc{NCDatasets, + author = {Alexander Barth}, + title = {NCDatasets: A julia package for manipulating netCDF data sets}, + year = {2023}, + publisher = {GitHub}, + journal = {GitHub repository}, + howpublished = {\url{https://github.com/Alexander-Barth/NCDatasets.jl}}, + commit = {90ed5641684604096558a77020038583e1f2459f} +} + +@misc{NEMO, + title = {NEMO ocean engine}, + url = {http://hdl.handle.net/2122/13309}, + author = {Gurvan Madec and Romain Bourdallé-Badie and Pierre-Antoine Bouttier and Clement Bricaud and Diego Bruciaferri and Daley Calvert and Jérôme Chanut and Emanuela Clementi and Andrew Coward and Damiano Delrosso and Christian Ethé and Simona Flavoni and Tim Graham and James Harle and Doroteaciro Iovino and Dan Lea and Claire Lévy and Tomas Lovato and Nicolas Martin and Sébastien Masson and Silvia Mocavero and Julien Paul and Clément Rousset and Dave Storkey and Andrea Storto and Martin Vancoppenolle}, + doi = {10.5281/zenodo.3248739}, + year = {2017}, +}, + +@article{Numpy, + title = {Array Programming with {{NumPy}}}, + author = {Harris, Charles R. and Millman, K. Jarrod and {van der Walt}, St{\'e}fan J. and Gommers, Ralf and Virtanen, Pauli and Cournapeau, David and Wieser, Eric and Taylor, Julian and Berg, Sebastian and Smith, Nathaniel J. and Kern, Robert and Picus, Matti and Hoyer, Stephan and {van Kerkwijk}, Marten H. and Brett, Matthew and Haldane, Allan and {del R{\'i}o}, Jaime Fern{\'a}ndez and Wiebe, Mark and Peterson, Pearu and {G{\'e}rard-Marchant}, Pierre and Sheppard, Kevin and Reddy, Tyler and Weckesser, Warren and Abbasi, Hameer and Gohlke, Christoph and Oliphant, Travis E.}, + year = {2020}, + month = sep, + journal = {Nature}, + volume = {585}, + number = {7825}, + pages = {357--362}, + publisher = {{Nature Publishing Group}}, + issn = {1476-4687}, + doi = {10.1038/s41586-020-2649-2}, + urldate = {2024-03-29}, + copyright = {2020 The Author(s)}, + langid = {english}, + keywords = {Computational neuroscience,Computational science,Computer science,Software,Solar physics}, +} + @article{Ramadhan2020, title = {Oceananigans.Jl: {{Fast}} and Friendly Geophysical Fluid Dynamics on {{GPUs}}}, shorttitle = {Oceananigans.Jl}, @@ -308,7 +391,6 @@ @article{Ramadhan2020 issn = {2475-9066}, doi = {10.21105/joss.02018}, urldate = {2023-09-14}, - abstract = {Ramadhan et al., (2020). Oceananigans.jl: Fast and friendly geophysical fluid dynamics on GPUs. Journal of Open Source Software, 5(53), 2018, https://doi.org/10.21105/joss.02018}, langid = {english}, } @@ -321,6 +403,7 @@ @article{Rasp2018 volume = {115}, number = {39}, pages = {9684--9689}, + doi = {10.1073/pnas.1810286115}, } @article{Schneider2023, @@ -336,7 +419,6 @@ @article{Schneider2023 issn = {1758-6798}, doi = {10.1038/s41558-023-01769-3}, urldate = {2023-09-14}, - abstract = {There are contrasting views on how to produce the accurate predictions that are needed to guide climate change adaptation. Here, we argue for harnessing artificial intelligence, building on domain-specific knowledge and generating ensembles of moderately high-resolution (10\textendash 50 km) climate simulations as anchors for detailed hazard models.}, copyright = {2023 Springer Nature Limited}, langid = {english}, keywords = {Climate and Earth system modelling,Projection and prediction}, @@ -355,7 +437,6 @@ @article{Simmons1978 issn = {1520-0493, 0027-0644}, doi = {10.1175/1520-0493(1978)106<0405:SOTSIM>2.0.CO;2}, urldate = {2023-03-07}, - abstract = {Abstract The stability of the semi-implicit method of time integration of the primitive equations is examined when the actual temperature deviates from the reference profile about which the implicitly treated gravity wave terms are linearized. The stability criterion is shown in general to be much more stringent than might he assumed from a simple analytical solution. Instability may occur when there exists a region in which the static stability of the actual atmosphere differs significantly from that of the reference atmosphere, and for realistic actual profiles and commonly chosen reference profiles it is likely to arise at vertical resolutions that are little higher than those used in previous tests of the scheme. Stabilization is achieved either by an appropriate change of reference profile or by a modification of the time-averaging of gravity wave terms. Both may result in a small further reduction in gravity wave phase speeds. Alternatives are mentioned which give better phase speeds at the expense of a reduced time step.}, chapter = {Monthly Weather Review}, langid = {english}, } @@ -373,7 +454,6 @@ @article{Simmons1981 issn = {1520-0493, 0027-0644}, doi = {10.1175/1520-0493(1981)109<0758:AEAAMC>2.0.CO;2}, urldate = {2023-03-07}, - abstract = {Abstract An energy and angular-momentum conserving vertical finite-difference scheme is introduced for a general terrain-following vertical coordinate which is a function of pressure and its surface value. A corresponding semi-implicit time scheme is also defined. These schemes am used to compare the usual sigma coordinate with the hybrid coordinate which reduces to pressure above a fixed level and with a modified hybrid coordinate which tends uniformly to pressure at upper levels. Error in the representation of the stratospheric pressure gradient over steep orography can be significantly reduced by use of the hybrid coordinate but the semi-implicit scheme is less stable. The modified hybrid coordinate offers a useful compromise.}, chapter = {Monthly Weather Review}, langid = {english}, } @@ -391,7 +471,6 @@ @article{Vana2017 issn = {0027-0644, 1520-0493}, doi = {10.1175/MWR-D-16-0228.1}, urldate = {2020-02-25}, - abstract = {Earth's climate is a nonlinear dynamical system with scale-dependent Lyapunov exponents. As such, an important theoretical question for modeling weather and climate is how much real information is carried in a model's physical variables as a function of scale and variable type. Answering this question is of crucial practical importance given that the development of weather and climate models is strongly constrained by available supercomputer power. As a starting point for answering this question, the impact of limiting almost all real-number variables in the forecasting mode of ECMWF Integrated Forecast System (IFS) from 64 to 32 bits is investigated. Results for annual integrations and medium-range ensemble forecasts indicate no noticeable reduction in accuracy, and an average gain in computational efficiency by approximately 40\%. This study provides the motivation for more scale-selective reductions in numerical precision.}, langid = {english} } @@ -408,7 +487,6 @@ @article{Williams2011 issn = {0027-0644, 1520-0493}, doi = {10.1175/2010MWR3601.1}, urldate = {2021-12-17}, - abstract = {Errors caused by discrete time stepping may be an important component of total model error in contemporary atmospheric and oceanic simulations. To reduce time-stepping errors in leapfrog integrations, the Robert\textendash Asselin\textendash Williams (RAW) filter was proposed by the author as a simple improvement to the widely used Robert\textendash Asselin (RA) filter. The present paper examines the behavior of the RAW filter in semi-implicit integrations. First, in a linear theoretical analysis, the stability and accuracy are interrogated by deriving analytic expressions for the amplitude errors and phase errors. Then, power-series expansions are used to interpret the leading-order errors for small time steps and hence to identify optimal values of the filter parameters. Finally, the RAW filter is tested in a realistic nonlinear setting, by applying it to semi-implicit integrations of the elastic pendulum equations. The results suggest that replacing the RA filter with the RAW filter could reduce time-stepping errors in semi-implicit integrations.}, langid = {english}, } @@ -423,7 +501,6 @@ @misc{Innes2019 publisher = {{arXiv}}, doi = {10.48550/arXiv.1907.07587}, urldate = {2023-09-15}, - abstract = {Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large amounts of data. At the same time, machine learning models are becoming increasingly sophisticated and exhibit many features often seen in scientific computing, stressing the capabilities of machine learning frameworks. Just as the disciplines of scientific computing and machine learning have shared common underlying infrastructure in the form of numerical linear algebra, we now have the opportunity to further share new computational infrastructure, and thus ideas, in the form of Differentiable Programming. We describe Zygote, a Differentiable Programming system that is able to take gradients of general program structures. We implement this system in the Julia programming language. Our system supports almost all language constructs (control flow, recursion, mutation, etc.) and compiles high-performance code without requiring any user intervention or refactoring to stage computations. This enables an expressive programming model for deep learning, but more importantly, it enables us to incorporate a large ecosystem of libraries in our models in a straightforward way. We discuss our approach to automatic differentiation, including its support for advanced techniques such as mixed-mode, complex and checkpointed differentiation, and present several examples of differentiating programs.}, archiveprefix = {arxiv}, keywords = {Computer Science - Machine Learning,Computer Science - Programming Languages}, } @@ -437,7 +514,7 @@ @inproceedings{Moses2020 pages = {12472--12485}, publisher = {{Curran Associates, Inc.}}, urldate = {2023-09-15}, - abstract = {Applying differentiable programming techniques and machine learning algorithms to foreign programs requires developers to either rewrite their code in a machine learning framework, or otherwise provide derivatives of the foreign code. This paper presents Enzyme, a high-performance automatic differentiation (AD) compiler plugin for the LLVM compiler framework capable of synthesizing gradients of statically analyzable programs expressed in the LLVM intermediate representation (IR). Enzyme synthesizes gradients for programs written in any language whose compiler targets LLVM IR including C, C++, Fortran, Julia, Rust, Swift, MLIR, etc., thereby providing native AD capabilities in these languages. Unlike traditional source-to-source and operator-overloading tools, Enzyme performs AD on optimized IR. On a machine-learning focused benchmark suite including Microsoft's ADBench, AD on optimized IR achieves a geometric mean speedup of 4.2 times over AD on IR before optimization allowing Enzyme to achieve state-of-the-art performance. Packaging Enzyme for PyTorch and TensorFlow provides convenient access to gradients of foreign code with state-of-the-art performance, enabling foreign code to be directly incorporated into existing machine learning workflows.}, + doi = {10.48550/arXiv.2010.01709}, } @@ -457,7 +534,7 @@ @phdthesis{Meyer2022b year = {2022}, school = {University of Reading}, type = {PhD thesis}, - note = {Available at \url{https://www.doi.org/10.48683/1926.00109229}} + doi = {10.48683/1926.00109229}, } @article{Rose2018, @@ -504,13 +581,26 @@ @misc{stompor2011 eprintclass = {ascl}, eprint = {1110.013}, adsurl = {https://ui.adsabs.harvard.edu/abs/2011ascl.soft10013S}, - adsnote = {Provided by the SAO/NASA Astrophysics Data System} + adsnote = {Provided by the SAO/NASA Astrophysics Data System}, + howpublished = {\url{https://ascl.net/1110.013}}, } @misc{Willmert2020, author = {Willmert, J.}, title = {Blog Series: Notes on Calculating the Spherical Harmonics}, - howpublished = {\url{https://justinwillmert.com/articles/2020/notes-on-calculating-the-spherical-harmonics/}}, + howpublished = {\url{http://web.archive.org/web/*/https://justinwillmert.com/articles/2020/notes-on-calculating-the-spherical-harmonics/}}, year = 2020, note = {Accessed: 2023-10-16} } + +@article{Xarray, + title = {xarray: {N-D} labeled arrays and datasets in {Python}}, + author = {Hoyer, S. and J. Hamman}, + journal = {Journal of Open Research Software}, + volume = {5}, + number = {1}, + year = {2017}, + publisher = {Ubiquity Press}, + doi = {10.5334/jors.148}, + url = {https://doi.org/10.5334/jors.148} +} diff --git a/docs/joss/paper.md b/docs/joss/paper.md index d23b50e8e..399901a95 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -132,14 +132,15 @@ evaporation, and precipitation due to large-scale condensation and convection. \label{fig:primitive}](primitive.png) SpeedyWeather.jl relies on Julia's multiple dispatch programming paradigm [@Bezanson2017] -to be extensible with new components including parameterizations, forcings, drag, +to be extensible with new components including parameterizations, forcing, drag, or even the grid. All such supported model components define an abstract type that can be subtyped to introduce, for example, a new parameterization. -To define precipitation due to the physical process of large-scale condensation, -one would define `MyCondensation` as a new subtype of `AbstractCondensation`. -One then only needs to extend the `initialize!` and `condensation!` -functions for this new type. Passing on `condensation = MyCondensation()` +To define a new parameterization for convection in a given vertical column of the atmosphere, +one would define `MyConvection` as a new subtype of `AbstractConvection`. +One then only needs to extend the `initialize!` (executed once during model initialization) +and `convection!` (executed on every time step) +functions for this new type. Passing on `convection = MyConvection()` to the model constructor then implements this new model component without the need to branch off or overwrite existing model components. Conceptually similar scientific modelling paradigms have been very successful @@ -165,7 +166,10 @@ but Float64 and other custom number formats can be used with a single code basis [@Klower2022; @Klower2020]. Julia will compile to the choice of number format, the grid, and and other model components just-in-time. A simple parallelization -across vertical layers is supported by Julia's multithreading. +(across vertical layers for the dynamical core, across horizontal grid points +for the parameterizations) is supported by Julia's multithreading. +No distributed-memory parallelization is currently supported, +GPU support is planned. SpeedyWeather.jl internally uses three sub-modules `RingGrids`, `LowerTriangularMatrices`, and `SpeedyTransforms`. `RingGrids` is a module that discretizes @@ -176,8 +180,7 @@ their coefficients in a lower triangular matrix representation. the grid-point space as defined by `RingGrids` and the spectral space defined in `LowerTriangularMatrices`. These three modules are independently usable and therefore support SpeedyWeather's library-like user interface. -Output is stored as NetCDF files using -[NCDatasets.jl](https://github.com/Alexander-Barth/NCDatasets.jl). +Output is stored as NetCDF files using NCDatasets.jl[@NCDatasets]. ![Relative vorticity simulated with the shallow water model in SpeedyWeather.jl. The simulation used a spectral resolution of T1023 (about 20 km) and Float32 @@ -191,18 +194,20 @@ NASA's blue marble from June 2004. \label{fig:swm}](swm.png) SpeedyWeather.jl is a fresh approach to atmospheric models that have been very influential in many areas of scientific and high-performance computing as well as climate change mitigation and adaptation. -Most weather, ocean and climate models are written in Fortran and have been +Most weather, ocean and climate models are written in Fortran +(e.g. ICON [@ICON], CESM [@CESM], MITgcm [@MITgcm], NEMO [@NEMO]) and have been developed over decades. From this tradition follows a specific programming style and associated user interface. SpeedyWeather.jl aims to overcome the constraints of traditional Fortran-based models. -The modern trend sees simulations in Fortran and data analysis in Python, +The modern trend sees simulations in Fortran and data analysis in Python +(e.g. NumPy [@Numpy], Xarray [@Xarray], Dask [@Dask], Matplotlib [@Hunter2007]), making it virtually impossible to interact with various model components directly. In SpeedyWeather.jl, interfaces to the model components are exposed to the user. Furthermore, data-driven climate modelling [@Rasp2018; @Schneider2023], which replaces existing model components with machine learning, -is more difficult in Fortran due to the lack of -established machine learning frameworks [@Meyer2022a]. -In Julia, Flux.jl is available for machine learning [@Innes2019] as well as automatic +is more difficult in Fortran due to the lack of established machine learning +frameworks [@Meyer2022a]. +In Julia, Flux.jl [@Innes2019] is available for machine learning as well as automatic differentiation with Enzyme [@Moses2020] for gradients-based optimization. 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z%*YrL-i%1LAerL{7?Qc&|E3g=Nvle)U;Wb@-813jSm*&2t}vY&&Q1=c*tZZKugyH4 zu&JiwBk9bUo9_2UGth{9EloLxQB-bjMwGVkuGFR-GXgfe0^uvKdF_JI&p~0!67j>! z%#nm;9qtBmxNP_OK(#N2p^#jbU=pv-xj^6wnvI&B(pDnG-hKU){7(u&!>3I{pm!u6DHstLO-p{nYk2-l1OjC@|3q45qw zbT)4J1;Dus=7Q6_%6ln%6TkT(qW(<+=kcnUGbRu|KY zu9fwvOoqAU_`8E9=MvJu06!ggicwwYk@4H<5=y9J6*ek$-{hBrM4b^)nX!#p_=AI+ z3uR%yoWaOO5Ru+px+TiWVGyG%y1Vic+GqHZB@J6?$zTlAHff1>;MfL%PVDM{!Bk1$ z5=opRfZb7z4If2KgRMgimR8?}#9420^zbIE-3wiD)3PaHdd=NrfctGda+-eNWcuw< z8HKQ`ZWAh5EgB$*S`K>HdC8M^h;vu*qUBjOLkbNN010@QzLfVLy|tMGv#Bq_{kV#a zTcEW)O!7dLdl9Ax(?>Ha!ykUdIXVdB5y&n6@Z>pdA+8j-Fp3fI8w={bz=P}+0Tr?x zvYjn^Og2m{OpT%O9q$^q^|b(5;oD zRH3at#U67mRD6K*HG$LHZ}?U2u9^enF8hkMtnQ9eLyPzm?H*%p@2+};$dSk~6=NSB zNAY>nA1|&aSG;T)i!MEXuf99sWmG+*Zu(7qyacp_Zhc-nn4zJkEEW4$B_#5&8(HaZ DC+QkD From 4d7702fa5a4b095dc91dadae04ae391250956535 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Milan=20Kl=C3=B6wer?= Date: Wed, 25 Oct 2023 15:38:11 -0400 Subject: [PATCH 53/86] JOSS paper: more tweaks following restructure --- docs/joss/paper.md | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index c47599304..9e801980b 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -90,16 +90,16 @@ models which solve different sets of equations: - the shallow water equations (\autoref{fig:swm}), and - the barotropic vorticity equation. -Several simple parameterizations for unresolved physical processes -including precipitation or boundary layer mixing are implemented, and new ones can +The primitive equation model in SpeedyWeather.jl is an +atmospheric general circulation model [@Kucharski2013] with simple parameterizations +for unresolved physical processes including precipitation or boundary layer mixing. +It can be thought of as a conceptual reinvention of the Fortran SPEEDY model [@Molteni2003] +in the Julia programming language [@Bezanson2017]. However, all models here are written in a modular +way to make its components easily extensible. For example, a new parameterization can be externally defined and passed as an argument to the model constructor. -The primitive equation model in SpeedyWeather.jl is an intermediate-complexity -atmospheric general circulation model [@Kucharski2013] and can be thought of as a -conceptual reinvention of the Fortran SPEEDY model [@Molteni2003] in the Julia -programming language [@Bezanson2017]. However, all models are written in a modular -way to make its components easily extensible. Furthermore, operators used inside -SpeedyWeather.jl are exposed to the user, facilitating analysis of the simulation -data. SpeedyWeather.jl is therefore, beyond its main purpose of simulating +Operators used inside SpeedyWeather.jl are exposed to the user, +facilitating analysis of the simulation data. +SpeedyWeather.jl is therefore, beyond its main purpose of simulating atmospheric motion, also a library for the analysis of gridded data on the sphere. Running and analyzing simulations can be interactively combined, enhancing user experience and productivity. @@ -154,7 +154,7 @@ as an argument. Many grids are already implemented: the conventional Gaussian grid, a regular longitude-latitude grid, the octahedral Gaussian grid [@Malardel2016], the octahedral Clenshaw-Curtis grid [@Hotta2018], and the HEALPix grid [@Gorski2005]. -Both SpeedyWeather.jl and its spherical harmonic transform `SpeedyTransforms` are also +Both SpeedyWeather.jl and its spherical harmonic transform are also number format-flexible. Single-precision floating-point numbers (Float32) are the default as adopted by other modelling efforts [@Vana2017; @Nakano2018], but Float64 and other custom number formats can be used with a single From f083a9ad1dbcdf14189e6a4dba158eaa97fc240a Mon Sep 17 00:00:00 2001 From: milankl Date: Wed, 25 Oct 2023 19:39:07 +0000 Subject: [PATCH 54/86] Saved new PDF of paper --- docs/joss/paper.pdf | Bin 1344244 -> 1343662 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/docs/joss/paper.pdf b/docs/joss/paper.pdf index eebc4d635adbc480989c2693a796ef1aa59965c4..756b61260a7723f837451cdafa5504378d382661 100644 GIT binary patch delta 35105 zcmZUaQ;;UWvTmoRZQHhO+qP{Rf7`ZgPurfhZQC~P?7ibW-G{ZJo-?ANBEQUf3{k2L zP^u?{24YSts6$2pT=9<85_3AeyhDBYubMc32mgLVgXL*`M%f)SkTZ?;EpK4#nY`g{ z1Hm*glcMZC357=J(36&QgasoG{8Pds@p%LICI*ZS_I{s5jq5K8a*{SNfh$O@LWJG$ z_kJEk-Of*Vl;e-wF*XlsDFp+6mBg+QUwlh^;jjIo-|6`TxG7=**abmQ_xCn-*vTKS zPWI}^Df^`=Sp9x~dw$yWeqU|m^^X1>*zVQU-ndyMQvF_#n&2}p0&R1sXM+GQ7$6z8 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zv(1kS+i_Z=qg7OZ{o@89AqBxn3Ji`MjqE2UFs+=x_HqK_>IBo2LsBQ2a8aT2Z@nvezqn)q;DyZEK(ZUo`#i^}9>&-&zE`+K<`xN;K>3 zhOeHs%&q}EssVX#6Q=B5%XICq+YOfb*$bt%Iq6<;R5o!m&S{suz_fOQFrS0;1czzilfO*tl?h_qz2WrxKV$4v8(`i{}mKIe+ycL+%D{F3kz$`fI#ya3wOggmS(X zzNWLr-$r`Yztx#l(T9s$nOb{=zWKf?DLKWvA^K6-YXzAmJ_{cAoG<-Zi}&C5KE*LZ zwVti-kf8Nt zRNL)T*7~MPo@0YRg5m+EhE@|!O)>Gkm(41EF8i(Rr28cD#O8vk7Gq@@p^t_?d%mty z*?F>Z0zd16xN4S;DFT|B?3Yxgnwi)=&r|kr(ow0u&E_s0BOk53Q-G~WQ^n~-;{;~K zJ|~G5AFi2GWTdOUhM2$q+GOf5Y#_x;q`iPl-mhG9Dc*@yM znSaVp|5LxKQXfwIl Date: Thu, 30 Nov 2023 10:21:02 -0500 Subject: [PATCH 55/86] joss paper: with new figure, incl precip --- docs/joss/paper.md | 12 ++++++++---- docs/joss/primitive.jpg | Bin 288095 -> 0 bytes docs/joss/primitive.png | Bin 0 -> 526363 bytes 3 files changed, 8 insertions(+), 4 deletions(-) delete mode 100644 docs/joss/primitive.jpg create mode 100644 docs/joss/primitive.png diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 9e801980b..2f0e8fb1f 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -140,8 +140,12 @@ in the Python-based generic partial differential equation solver Dedalus [@Burns the process-oriented climate model CLIMLAB [@Rose2018], and the Julia ocean model Oceananigans.jl [@Ramadhan2020]. -![Surface temperature simulated with the primitive equation model in SpeedyWeather.jl. -(Figure will be updated) \label{fig:primitive}](primitive.jpg) +![Surface humidity, air temperature, wind speed and precipitation simulated +with the primitive equation model in SpeedyWeather.jl. Spectral resolution is +T127 (about 100km) on an octahedral Gaussian grid [@Malardel2016] with simple +physics to represent unresolved processes such as surface fluxes including +evaporation, and precipitation due to large-scale condensation and convection. +\label{fig:primitive}](primitive.png) The dynamical core of SpeedyWeather.jl uses established numerics [@Bourke1972; @Hoskins1975; @Simmons1978; @Simmons1981], @@ -212,8 +216,8 @@ NASA's blue marble from June 2004. \label{fig:swm}](swm.png) We acknowledge contributions from David Meyer, Mosè Giordano, Valentin Churavy, and Pietro Monticone who have also committed to the SpeedyWeather.jl repository, and the wider Julia community -for help and support. MK acknowledges funding from the -National Science Foundation (Chris please add). +for help and support. +MK acknowledges funding from the National Science Foundation. MK and TK acknowledge funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme for the ITHACA grant (no. 741112). 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[PATCH 43/86] JOSS paper: Alistair's next comments Co-authored-by: Alistair White <59571934+white-alistair@users.noreply.github.com> --- docs/joss/paper.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/joss/paper.md b/docs/joss/paper.md index 8d72f852e..09e74b295 100644 --- a/docs/joss/paper.md +++ b/docs/joss/paper.md @@ -114,8 +114,8 @@ harmonic coefficients. `SpeedyTransforms` implements the spectral transform betw the grid-point space as defined by `RingGrids` and the spectral space defined in `LowerTriangularMatrices`. These three modules are independently usable and therefore make SpeedyWeather.jl, beyond its main purpose of simulating -atmospheric motion also a library for the analysis of gridded data on the sphere. -Running and analysing simulations can be interactively combined, enhancing user +atmospheric motion, also a library for the analysis of gridded data on the sphere. +Running and analyzing simulations can be interactively combined, enhancing user experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by @@ -172,7 +172,7 @@ number format-flexible. Single-precision floating-point numbers (Float32) are the default as adopted by other modelling efforts [@Vana2017; @Nakano2018], but Float64 and other custom number formats can be used with a single code basis [@Klower2022; @Klower2020]. -Julia will compile to the choice of the number format, the grid, +Julia will compile to the choice of number format, the grid, and and other model components just-in-time. A simple parallelization across vertical layers is supported by Julia's multithreading. 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affiliation: 6 - - name: David Meyer - orcid: 0000-0002-7071-7547 - affiliation: "8,9" - - name: Tom Kimpson orcid: 0000-0002-6542-6032 - affiliation: "2,10" + affiliation: "2,8" - name: Navid C Constantinou orcid: 0000-0002-8149-4094 - affiliation: 11 + affiliation: 9 - name: Chris Hill affiliation: 1 @@ -73,14 +69,10 @@ affiliations: index: 6 - name: University of Minnesota, Minneapolis, MN, USA index: 7 - - name: Imperial College London, UK - index: 8 - - name: European Centre for Medium-Range Weather Forecasts, Bonn, Germany - index: 9 - name: University of Melbourne, Australia - index: 10 + index: 8 - name: Australian National University, Canberra, Australia - index: 11 + index: 9 date: 14 September 2023 bibliography: paper.bib @@ -121,7 +113,8 @@ experience and productivity. The user interface of SpeedyWeather.jl is heavily influenced by the Julia ocean model Oceananigans.jl [@Ramadhan2020]. A monolithic interface based on parameter files is avoided in favor of a -library-style interface in which users write short scripts to run models +library-style interface. Users write notebooks, directly into +Julia's read-evaluate-print loop (REPL) or short scripts to run models rather than merely supplying parameters and input arrays. A model is created bottom-up by first defining the discretization and any non-default model components with their respective parameters. @@ -133,7 +126,7 @@ visualize the current variables, or individual terms of the equations. One can also adjust parameters or define new model components before resuming the simulation. While these steps can be written into a script for reproducibility, the same steps can be executed and interacted with one-by-one in -Julia's read-evaluate-print loop (REPL) or in a single Jupyter or Pluto notebook. +the REPL or in a single Jupyter or Pluto notebook. We thereby achieve an interactivity of a simulation and its various model components far beyond the options provided in a monolithic interface. At the same time, defaults, set to well-established test cases, @@ -188,7 +181,7 @@ developed over decades. From this tradition follows a specific programming style and associated user interface. SpeedyWeather.jl aims to overcome the constraints of traditional Fortran-based models. The modern trend sees simulations in Fortran and data analysis in Python, -making virtually impossible to interact with various model components directly. +making it virtually impossible to interact with various model components directly. In SpeedyWeather.jl, interfaces to the model components are exposed to the user. Furthermore, data-driven climate modelling [@Rasp2018; @Schneider2023], which replaces existing model components with machine learning, @@ -213,7 +206,7 @@ NASA's blue marble from June 2004. \label{fig:swm}](swm.png) # Acknowledgements -We acknowledge contributions from Mosè Giordano, Valentin Churavy, and Pietro Monticone +We acknowledge contributions from David Meyer, Mosè Giordano, Valentin Churavy, and Pietro Monticone who have also committed to the SpeedyWeather.jl repository, and the wider Julia community for help and support. MK acknowledges funding from the National Science Foundation (Chris please add). 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