/BAMS_STOC_2022

Jupyter notebooks to reproduce the figures for the 'Pacific Convergence Zones' chapter of the BAMS State of the Climate report for 2022

Primary LanguageJupyter Notebook

code to produce the figures included in the BAMS "State of the Climate" report section on Pacific Convergence Zones

  1. update the MSWEP daily dataset:
rclone sync -v --exclude 3hourly/ --exclude Monthly/ --drive-shared-with-me GoogleDrive:/MSWEP_V280 /media/nicolasf/END19101/ICU/data/glo2ho/MSWEP280
  1. calculate the MSWEP monthly climatology (1991 - 2020):
notebooks/calculate_MSWEP_monthly_from_daily_climatology.ipynb
  1. calculate the monthly averages for each year, as well as the anomalies:
notebooks/calculate_MSWEP_monthly_from_daily.ipynb
  1. calculate the anomalies (WRT to 1991 - 2020 climatology) in mm and percentage of normal then plots (maps) the average rainfall and anomalies for a chosen date (year-month) from MSWEP:
notebooks/plot_monthly_maps_MSWEP.ipynb 
  1. calculate the longitudinal sectors averages from MSWEP and plots (x-axis = Rainfall in mm, y-axis = latitude)
notebooks/plot_sectors_MSWEP.ipynb 
  1. calculate longitudinal sector averages as above and compares a chosen 3 months season to recent ENSO years composites (La Nina, El Nino and Neutral) based on the 3 months values of the Oceanic Nino Index (ONI) downloaded from NOAA at https://www.cpc.ncep.noaa.gov/data/indices/oni.ascii.txt.
notebooks/plot_ENSOs_vs_current_year_MSWEP.ipynb

Additional notebooks:

notebooks/ERSST_Pacific_anomalies.ipynb: 

calculates and plot the ERSST SST anomalies for each month of the year to process

There are also some versions of the above notebooks using CMAP (downloaded from ) for comparison with MSWEP ...