Download necessary CAMS data

First, you have to register and install the CAMS api from: CDS api site

import os, sys

import numpy as np
import pandas
from scipy.interpolate import interp1d
import xarray as xr
import calendar
import matplotlib.pyplot as plt

import logging
import calendar, datetime
import cdsapi

opj = os.path.join

odir = '/data/cams/france'
latmax,lonmin,latmin,lonmax = 52.,-6.,41,10

odir = '/data/cams/world'
latmax,lonmin,latmin,lonmax = 90,-180,-90,180
year=2023


for month in range(10,13):
    
    date_start='{:4d}-{:02d}-{:02d}'.format(year,month,1)
    date_end='{:4d}-{:02d}-{:02d}'.format(year,month,calendar.monthrange(year, month)[1])
    name = '{:4d}-{:02d}'.format(year,month)
    filepath = opj(odir,'cams_forecast_'+name+'.nc')
    if os.path.exists(filepath):
        continue
    print(filepath)

    type='forecast'
    variable = [
                '10m_u_component_of_wind', '10m_v_component_of_wind',
                '2m_temperature',
                'mean_sea_level_pressure', 'surface_pressure',
                'ammonium_aerosol_optical_depth_550nm', 'black_carbon_aerosol_optical_depth_550nm',
                'dust_aerosol_optical_depth_550nm',
                'nitrate_aerosol_optical_depth_550nm', 'organic_matter_aerosol_optical_depth_550nm',
                'sea_salt_aerosol_optical_depth_550nm',
                'secondary_organic_aerosol_optical_depth_550nm', 'sulphate_aerosol_optical_depth_550nm',
                'total_aerosol_optical_depth_1240nm',
                'total_aerosol_optical_depth_469nm',
                'total_aerosol_optical_depth_550nm',
                'total_aerosol_optical_depth_670nm',
                'total_aerosol_optical_depth_865nm',
                'total_column_carbon_monoxide',
                'total_column_methane',
                'total_column_nitrogen_dioxide',
                'total_column_ozone', 'total_column_water_vapour']
    area = [latmax,lonmin,latmin,lonmax]
    c = cdsapi.Client()
    
    c.retrieve(
        'cams-global-atmospheric-composition-forecasts',
        {
            'date': date_start + '/' + date_end,
            'type': type,
            'format': 'netcdf'
            ,
            'variable': variable,
            'time': ['00:00', '12:00'],
            'leadtime_hour': ['0', '3', '6', '9'],
            'area': area,
        },
        filepath)