import cdsapi
from datetime import datetime, timedelta



def get_monthsdays(start =[2019,1,1],end=[2019,12,31]):
# reforecast time index
start, end = datetime(*start),datetime(*end)
days = [start + timedelta(days=i) for i in range((end - start).days + 1)]
monthday = [d.strftime("%B-%d").split("-") for d in days if d.weekday() in [0,3] ] 

return monthday



if __name__ == '__main__':
c = cdsapi.Client()


# station coordinates (lat,lon)
COORDS = {
"Thames":[51.35,-0.45]
}

# select date index corresponding to the event 
MONTHSDAYS = get_monthsdays(start =[2019,7,11],end=[2019,7,11])

YEAR = '2007' 

LEADTIMES = ['%d'%(l) for l in range(24,1128,24)]

# loop over date index (just 1 in this case)
for md in MONTHSDAYS:

month = md[0].lower()
day = md[1]

# loop over station coordinates
for station in COORDS:

station_point_coord = COORDS[station]*2 # coordinates input for the area keyword

c.retrieve(
'cems-glofas-reforecast',
{
'system_version': 'version_2_2',
'variable': 'river_discharge_in_the_last_24_hours',
'format': 'grib',
'hydrological_model': 'htessel_lisflood',
'product_type': ['control_reforecast','ensemble_perturbed_reforecasts'],
'area':station_point_coord, 
'hyear': YEAR,
'hmonth': month ,
'hday': day ,
'leadtime_hour': LEADTIMES,
},
f'glofas_reforecast_{station}_{month}_{day}.grib')

## === retrieve GloFAS Seasonal Reforecast ===

## === subset South America/Amazon region === 

import cdsapi

if __name__ == '__main__':


    c = cdsapi.Client()

    YEARS  = ['%d'%(y) for y in range(1981,2021)]

    MONTHS = ['january', 'february', 'march', 'april', 'may', 'june', 'july', 'august', 'september', 'october', 'november', 'december']

    LEADTIMES = ['%d'%(l) for l in range(24,2976,24)]
    
    for year in YEARS:
        for month in MONTHS:

            c.retrieve(
                'cems-glofas-seasonal-reforecast',
                {
                    'system_version': 'version_2_2',
                    'variable':'river_discharge_in_the_last_24_hours',
                    'format':'grib',
                    'hydrological_model':'htessel_lisflood',
                    'hyear': year,
                    'hmonth': month,
                    'leadtime_hour': LEADTIMES,
                    'area': [ 10.95, -90.95, -30.95, -29.95 ]
                }, 
                f'glofas_seasonal_reforecast_{year}_{month}.grib')

import cdsapi

c = cdsapi.Client()

c.retrieve(
    'cems-glofas-historical',
    {
        'variable': 'river_discharge_in_the_last_24_hours',
        'format': 'grib',
        'hydrological_model': 'lisflood',
        'product_type': 'intermediate',
        'hyear': '2021',
        'hmonth': 'january',
        'hday': [
            '01', '02', '03',
            '04', '05', '06',
            '07', '08', '09',
            '10', '11', '12',
            '13', '14', '15',
            '16', '17', '18',
            '19', '20', '21',
            '22', '23', '24',
            '25', '26', '27',
            '28', '29', '30',
            '31',
        ],
        'system_version': 'version_3_1',
    },
    'glofas_historical.grib')

When transforming from lat/lon (source coordinates) to projected LAEA (target coordinates), you need to consider that the number of decimal places of the source coordinates affects the target coordinates precision:

An interval of 0.001 degrees corresponds to about 100 metres in LAEA.

An interval of 0.00001 degrees corresponds to about 1 metre in LAEA.

import cdsapi

c = cdsapi.Client()

c.retrieve(
    'efas-reforecast',
    {
        'format': 'grib',
        'product_type': 'ensemble_perturbed_reforecasts',
        'variable': 'river_discharge_in_the_last_6_hours',
        'model_levels': 'surface_level',
        'hyear': '2007',
        'hmonth': 'march',
        'hday': [
            '04', '07',
        ],
        'leadtime_hour': [
            '0', '12', '18',
            '6',
        ],
    },
    'efas_reforecast.grib')