v2.1.1

A minor release to address an issue likely stems from cartopy0.18 #318
As a workaround, polar plots are now in square shape.

v2.1.0

New Features:

• Two components of ENSO-diags:
  maps of regression coefficient of atmospheric fields over SST anomaly;
  scatter plots of atmospheric feedback on SST anomaly.

• Quasi-biennial Oscillation (QBO) analysis

• Initial support for lat-lon map for Regional Refined Model (RRM) data.

v2.0.0

Some major changes in this new release:

• Refactored the code structure to make the code base more flexible to incorporate new diagnostics sets.
• Introduced a new way of running: run with API (i.e. python run_e3sm_diags.py). The old way (e3sm_diags -p) is backward compatible for the core diagnostics sets.
• Added time-series diagnostics for annual mean trend for selected variables (can be ran only with the new way)
• Variables P-E from (GPCP and OAflux), and from Core v2 fluxes are added.
• Dataset class is refactored to be cleaner and more flexible.
• Documentation is updated to reflect the new changes.

v1.7.1

• Add OMEGA to lat lon diagnostics set
• Fix Dockerfile
• Other bug fixes

We will have a big release for a new way of running the package, including adding set-specific parameters (i.g., plevs for the zonal_mean_2d diags set).
Please stay tuned!

v1.7.0

• Python 3 is now supported in lieu of Python 2.
• Pressure-Longitude meridional mean contour plots added.
• Added quick guide for using Docker.
• Added quick guide for ANL ALCF Cooley using Singularity.
• Added support for Singularity.
• Other small issues fixed.

v1.6.1

• No longer pinning specific versions of CDAT.
  • So using >= instead of =.
• Builds are now noarch.

v1.6.0

• In addition to climatology files, e3sm_diags now supports time series input (monthly data of multiple years saved in one file per each variable) to have climatology computed during runtime.
  • Users are able to specify the time slices for model vs model and model vs obs diagnostics runs.
    • An example is here, with the diags results here.
  • Both NCO-generated time series files and CMIP-compliant time series files can be used as input files.
    • For examples with CMIP data, see here for a model vs obs comparison or here for a model vs model comparison.
• New quick start guide for NERSC Cori.
• Major code refactor for reading in data and getting variables.
• Scripts added for creating the time series and climatology files for the observational data.
• User-facing instances of "acme" are replaced with "e3sm".
  • Please don't change the project name again.

v1.5.0

• e3sm_diags can now be ran as a container, in addition to being manually installed and ran that way.
  • View how to do so on Edison at NERSC via Shifter here.
  • The auxiliary script to run a container,e3sm_diags_container.py, supports Docker and Shifter.
  • Singularity support will be added in the next release or so.
  • A quick guide will be added for Docker and Singularity soon as well.
• Scripts added for creating the time-series observational data.
• Minor additions to the viewer.

v1.4.0

• Added selectors parameter.
  • View the documentation here.
• Major bug-fix regarding issue #156, where too many threads were used.
• Added scripts to create climo and timeseries data for the observational data. Located in the analysis_data_preprocess folder.

v.1.3.4

• Fixed major issue where NetCDF-4 files would not open on Edison compute nodes.
• Added output_format_subplot parameter to save individual panels when using matplotlib for the plotsets:
  • lat_lon
  • polar
  • zonal_mean_xy
  • zonal_mean_2d
  • cosp_histogram
• Expanded provenance. Now for each run, the command used, the py file, and the cfg file used are save in {results_dir}/prov. A yml file of the environment is also saved there as well.