Satellite_oceanography_lab.ipynb

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    "# COESSIN 2022\n",
    "## Satellite Oceanography Lab\n",
    "\n",
    "Precipitation, an important component of the hydrological cycle, plays an important role in the lives of humans and livelihoods in West Africa. In this lab exercise, we will be plotting precipitation in the Equatorial Atlantic Ocean and the Gulf of Guinea (GoG) during winter season (January) and summer season (August) using the Python program. \n",
    "\n",
    "The precipitation data is from the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) product. We will then discuss the possible causes of the differences in rainfall during the seasons. \n",
    "\n",
    "The GPM mission is an international network of satellites that provide the next-generation global observations of rain and snow. Building upon the success of the Tropical Rainfall Measuring Mission (TRMM), the GPM concept centers on the deployment of a “Core” satellite carrying an advanced radar / radiometer system to measure precipitation from space and serve as a reference standard to unify precipitation measurements from a constellation of research and operational satellites. \n",
    "\n",
    "The IMERG algorithm combines information from the GPM satellite constellation to estimate precipitation over the majority of the Earth's surface.  The IMERG algorithm fuses the early precipitation estimates collected during the operation of the TRMM satellite (2000 - 2015) with more recent precipitation estimates collected during operation of the GPM satellite (2014 - present).  \n",
    "----------------------------------------------------------------.---------------------------------------------------\n",
    "1.\tOpen your python program (or just use this notebook)\n",
    "2.\tChange the first line to point to your directory where the data is stored. datadir=r'PASTE YOUR DIRECTORY PATH ON THIS LINE/'. This should be datadir='~/coessing2022-hub/SatOcean_data/' if you are using the COESSING JupyterHub.\n",
    "3.\tThe first set of command lines load the python routines needed to make the plot. The second set of commands load the data. The rest of the commands make the plots: January rainfall, August rainfall and time series of seasonal anomalies of rainfall in southeastern Nigeria. \n",
    "4.\tSeasonal anomalies are gotten by removing the annual mean from the monthly values. We do this to see how the monthly values differ with respect to the annual mean. A positive number means the value for that month is higher than the annual mean. A negative number means the value for that month is lower than the annual mean. A zero means the value for that month is the same as the annual mean.\n",
    "5.\tThe last line in the set of commands saves the figure you just made in your directory. i.e.    \n",
    "    'Fig_PPT_JanAug_SeasAnom_TimeSeries.tif'\n",
    "----------------------------------------------------------------.---------------------------------------------------\n",
    "Please answer the following questions.\n",
    "In the figure you just plotted, the redder the color, the more the rainfall. \n",
    "\n",
    "1.\tWhat are the differences between the magnitudes of the mean rainfall in January and August? \n",
    "2.\tHow are these rainfall magnitudes likely to vary in a warming climate?\n",
    "3.\tWhat are some possible implications for such changes in rainfall magnitudes on the environment and livelihoods of West Africans? \n",
    "4.\tObserve the locations of the core of rainfall in January and August. What accounts for this spatial variability?  \n",
    "5.\tPlot (c) shows the seasonal anomalies. This is a box average of rainfall anomalies in southeastern Nigeria. What are some possible causes for the high rainfall during most of the summer months?\n",
    "6.\tWhat are some possible reasons for the dip in rainfall during July and August? \n",
    "----------------------------------------------------------------.---------------------------------------------------\n",
    "datadir = r'C:\\Users\\enyad\\Documents\\MyEdu\\SummerSch\\NG_2022\\ppt\\SatLab\\SatOcean_Lab/'\n",
    "#%matplotlib inline # only needed for Jupyter notebook\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cf\n",
    "import cartopy.mpl.ticker as cticker\n",
    "import matplotlib.gridspec as gridspec # allows for customized subplot sizes\n",
    "\n",
    "# Read in the data\n",
    "lon = pd.read_csv(datadir+'gpm.ppt.WA.lon.dat',header=None)\n",
    "lat = pd.read_csv(datadir+ 'gpm.ppt.WA.lat.dat',header=None)\n",
    "tjan = pd.read_csv(datadir+'gpm.ppt.WA.Jan.Clim.dat',header=None)\n",
    "taug = pd.read_csv(datadir+'gpm.ppt.WA.Aug.Clim.dat',header=None)\n",
    "data = pd.read_csv(datadir+'gpm.ppt.SENg.TimeSeries.SeasAnom.dat',header=None)\n",
    "data = data.drop(columns=0)\n",
    "ctime = np.arange(12)\n",
    "\n",
    "# Plot the data\n",
    "# Define useful quantities for labeling lat/lon\n",
    "X,Y = np.meshgrid(lon,lat)\n",
    "lon_labels = np.arange(-25,26,10)\n",
    "lat_labels = np.arange(0,19,5)\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "\n",
    "# Initiate the figure\n",
    "fig = plt.figure(figsize=(12,5))\n",
    "gs = fig.add_gridspec(2,2) # create a 2x2 square of subplot\n",
    "\n",
    "ax1 = fig.add_subplot(gs[0,0], projection=ccrs.PlateCarree()) # first subplot is in position (0,0)\n",
    "ax1.set_extent([-25, 25, 0, 18]) # set regional lat/lon extent\n",
    "\n",
    "# Plot the January data\n",
    "img = ax1.pcolor(X, Y, tjan,\n",
    "            transform=ccrs.PlateCarree(),\n",
    "            cmap='jet',vmin=0,vmax=0.5)\n",
    "\n",
    "# Set longitude labels\n",
    "ax1.set_xticks(lon_labels, crs=ccrs.PlateCarree())\n",
    "ax1.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "\n",
    "# Set latitude labels\n",
    "ax1.set_yticks(lat_labels, crs=ccrs.PlateCarree())\n",
    "ax1.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "# Add coastlines and country borders\n",
    "ax1.coastlines(color='lightgray')\n",
    "ax1.add_feature(cf.BORDERS, edgecolor='lightgray')\n",
    "\n",
    "# Add colorbar\n",
    "plt.colorbar(img, ax=ax1)\n",
    "ax1.set_aspect('auto') # needed to make colorbar same height as the subplot\n",
    "\n",
    "ax1.text(-25,17,'(a) Jan',fontsize=22,fontweight='bold',fontname='Times New Roman',color='white')\n",
    "\n",
    "#------------\n",
    "ax2 = fig.add_subplot(gs[0,1], projection=ccrs.PlateCarree())\n",
    "ax2.set_extent([-25, 25, 0, 18])\n",
    "\n",
    "img = ax2.pcolor(X, Y, taug,\n",
    "            transform=ccrs.PlateCarree(),\n",
    "            cmap='jet',vmin=0,vmax=0.5)\n",
    "\n",
    "# Set longitude labels\n",
    "ax2.set_xticks(lon_labels, crs=ccrs.PlateCarree())\n",
    "ax2.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Set latitude labels\n",
    "ax2.set_yticks(lat_labels, crs=ccrs.PlateCarree())\n",
    "ax2.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "ax2.coastlines(color='lightgray')\n",
    "ax2.add_feature(cf.BORDERS, edgecolor='lightgray')\n",
    "plt.colorbar(img, ax=ax2)\n",
    "ax2.set_aspect('auto')\n",
    "\n",
    "ax2.text(-25,17,'(b) Aug',fontsize=22,fontweight='bold',fontname='Times New Roman',color='white')\n",
    "\n",
    "#---------------------------------------\n",
    "ax3 = fig.add_subplot(gs[1, :])\n",
    "ax3.plot(data,linewidth=4,color='k')\n",
    "plt.axhline(0,linestyle='dashed',color='red')\n",
    "plt.grid()\n",
    "plt.ylim(-0.3,0.3)\n",
    "xlabels = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
    "plt.xticks(np.arange(12),xlabels,fontsize=14)\n",
    "plt.xlim(0,11)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.ylabel('Rain (mm/hour)',fontsize=14)\n",
    "ax3.text(0,0.22,'(c) Seas Anom',fontsize=22,fontweight='bold',fontname='Times New Roman')\n",
    "plt.tight_layout(h_pad=1)\n",
    "\n",
    "plt.savefig(datadir+'Fig_PPT_JanAug_SeasAnom_TimeSeries_cartopy.tif')\n"
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