#### README FILE FOR GATHERING THE NECESSARY DATA AND CREATING MAPS ####

## CREATE NCEP ANALYSIS OF PRECIPITATION ##
  DATABASE URL - https://psl.noaa.gov/data/composites/day/
    SELECT THE FOLLOWING
      Variables - Precipitation Rate
      Analysis level - surface
      Date (OR) - Ex. Select June 01 - June 09 2020
      Plot type - anomaly
      Region of globe - ALL
    ACTIONS
    - Create plot
    - (On next page) Download "Get a copy of the netCDF data file used for the plot"
    - Rename file to "precip_analysis.nc"
    - Move file to github/data/
  JUYPTER NOTEBOOK
    RUN github/scripts/precip-analysis.ipynb
      BLOCK 7 - Replace 'f_path = r'../data/precip_analysis.nc' with file location
      Run script

## CREATE ECMWF PRECIPITATION FORECAST ##
  CREATE DB ACCOUNT
    URL - https://cds.climate.copernicus.eu/#!/home
    DATA FORM - https://cds.climate.copernicus.eu/cdsapp#!/dataset/seasonal-postprocessed-single-levels?tab=form
      SELECT THE FOLLOWING
        Originating centre - ECMWF
        System - 5
        Variable - Total precipitation anomalous rate of accumulation
        Ensemble - Ensemble mean
        Year - (2020)
        Month - (June)
        Leadtime Month - 3
      ACTIONS
      - Show API request
      - Copy code
        replace "format: 'grib,'" with 'format': 'netcdf'
        replace 'download.grib' with 'filename.nc'
      JUYPTER NOTEBOOK
        RUN github/scripts/ecmwf-precip-forecastv1.ipynb
          BLOCK 7 - Replace 'f_path = r'../data/precip_analysis.nc' with file location
          Run script

##  DOWNGRADES ##
  Plotly
    version - 2.1
  Pandas
    version - 0.25