nicolasfauchereau / 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

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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 ...

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


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