...
| Code Block | ||||
|---|---|---|---|---|
| ||||
## === retrieve GloFAS Medium-Range Forecast ===
import cdsapi
import datetime
import warnings
def compute_dates_range(start_date,end_date,loop_days=True):
start_date = datetime.date(*[int(x) for x in start_date.split('-')])
end_date = datetime.date(*[int(x) for x in end_date.split('-')])
ndays = (end_date - start_date).days + 1
dates = []
for d in range(ndays):
dates.append(start_date + datetime.timedelta(d))
if not loop_days:
dates = [i for i in dates if i.day == 1]
else:
pass
return dates
if __name__ == '__main__':
# start the client
c = cdsapi.Client()
# user inputs
START_DATE = '2019-11-05' # first date with available data
END_DATE = '2021-03-15'
LEADTIMES = [str(lt) for lt in range(24,744,24)]
# loop over dates and save to disk
dates = compute_dates_range(START_DATE,END_DATE)
for date in dates:
year = date.strftime('%Y')
month = date.strftime('%m')
day = date.strftime('%d')
print(f"RETRIEVING: {year}-{month}-{day}")
c.retrieve(
'cems-glofas-forecast',
{
'format': 'grib',
'system_version':'operational',
'hydrological_model': 'htessel_lisflood',
'product_type':'ensemble_perturbed_forecasts',
'variable': 'river_discharge_in_the_last_24_hours',
'year': year,
'month': month,
'day': day,
'leadtime_hour':LEADTIMES
},
f'glofas_forecast_{year}_{month}_{day}.grib') |
GloFAS Medium-range reforecast
| Code Block | ||||
|---|---|---|---|---|
| ||||
## === retrieve GloFAS Medium-Range Reforecast ===
## === subset India, Pakistan, Nepal and Bangladesh region ===
import cdsapi
from datetime import datetime, timedelta
def get_monthsdays():
start, end = datetime(2019, 1, 1), datetime(2019, 12, 31)
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
MONTHSDAYS = get_monthsdays()
if __name__ == '__main__':
c = cdsapi.Client()
# user inputs
BBOX = [40.05 ,59.95, 4.95, 95.05] # North West South East
YEARS = ['%d'%(y) for y in range(1999,2019)]
LEADTIMES = ['%d'%(l) for l in range(24,1128,24)]
# submit request
for md in MONTHSDAYS:
month = md[0].lower()
day = md[1]
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',
'area': BBOX,# < - subset
'hyear': YEARS,
'hmonth': month ,
'hday': day ,
'leadtime_hour': LEADTIMES,
},
f'glofas_reforecast_{month}_{day}.grib') |
GloFAS Seasonal forecast
| Code Block | ||||
|---|---|---|---|---|
| ||||
## === retrieve GloFAS Seasonal Forecast ===
## === subset South America/Amazon region ===
import cdsapi
if __name__ == '__main__':
c = cdsapi.Client()
YEARS = ['%d'%(y) for y in range(2020,2022)]
MONTHS = ['%02d'%(m) for m in range(1,13)]
LEADTIMES = ['%d'%(l) for l in range(24,2976,24)]
for year in YEARS:
for month in MONTHS:
c.retrieve(
'cems-glofas-seasonal',
{
'variable': 'river_discharge_in_the_last_24_hours',
'format': 'grib',
'year': year,
'month': '12' if year == '2020' else month,
'leadtime_hour': LEADTIMES,
'area': [ 10.95, -90.95, -30.95, -29.95 ]
},
f'glofas_seasonal_{year}_{month}.grib') |
...