BASTET/DataRequest.py

155 lines
6.0 KiB
Python

import cdsapi
from input.user_input import *
# start_lat = 78.22 Svalbard
# start_lon = 15.65
# start_lat = 67.887382 Kiruna
# start_lon = 21.081452
startdays = ['23', '24', '25', '26', '27', '28', '29', '30', '31']
days = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31']
endascent = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15', '16', '17', '18', '19', '20', '21', '22']
endfloat = ['1']
def ERAsingle(year, month, days, north_lim, south_lim, east_lim, west_lim, name):
single = cdsapi.Client().retrieve(
'reanalysis-era5-single-levels',
{
'product_type': 'reanalysis',
'format': 'netcdf',
'variable': [
'cloud_base_height', 'high_cloud_cover', 'low_cloud_cover', 'medium_cloud_cover',
'skin_temperature', 'surface_net_solar_radiation', 'surface_net_thermal_radiation',
'surface_pressure', 'surface_solar_radiation_downwards', 'surface_thermal_radiation_downward_clear_sky',
'surface_thermal_radiation_downwards', 'toa_incident_solar_radiation',
'top_net_solar_radiation', 'top_net_thermal_radiation', 'total_cloud_cover',
'total_sky_direct_solar_radiation_at_surface',
],
'time': [
'00:00', '01:00', '02:00',
'03:00', '04:00', '05:00',
'06:00', '07:00', '08:00',
'09:00', '10:00', '11:00',
'12:00', '13:00', '14:00',
'15:00', '16:00', '17:00',
'18:00', '19:00', '20:00',
'21:00', '22:00', '23:00',
],
'year': str(year),
'month': str(month),
'day': days,
'area': [
north_lim, west_lim, south_lim, # north_lim, west_lim, south_lim, # North, West, South 72, -111, 67,
east_lim, # east_lim, # East 22,
],
})
single.download(name)
def ERAlevelAscend(year, month, days, start_lat, start_lon, name):
north_lim = start_lat + 10.0
south_lim = start_lat - 10.0
east_lim = start_lon - 10.0
west_lim = start_lon + 10.0
ascend = cdsapi.Client().retrieve(
'reanalysis-era5-pressure-levels',
{
'product_type': 'reanalysis',
'format': 'netcdf',
'variable': [
'geopotential', 'temperature', 'u_component_of_wind',
'v_component_of_wind', 'vertical_velocity',
],
'pressure_level': [
'1', '2', '3',
'5', '7', '10',
'20', '30', '50',
'70', '100', '125',
'150', '175', '200',
'225', '250', '300',
'350', '400', '450',
'500', '550', '600',
'650', '700', '750',
'775', '800', '825',
'850', '875', '900',
'925', '950', '975',
'1000',
],
'year': str(year),
'month': str(month),
'day': days,
'time': [
'00:00', '01:00', '02:00',
'03:00', '04:00', '05:00',
'06:00', '07:00', '08:00',
'09:00', '10:00', '11:00',
'12:00', '13:00', '14:00',
'15:00', '16:00', '17:00',
'18:00', '19:00', '20:00',
'21:00', '22:00', '23:00',
],
'area': [
north_lim, west_lim, south_lim,
east_lim,
],
})
ascend.download(name)
def ERAlevelFloat(year, month, days, north_lim, south_lim, east_lim, west_lim, name):
floating = cdsapi.Client().retrieve(
'reanalysis-era5-pressure-levels',
{
'product_type': 'reanalysis',
'format': 'netcdf',
'variable': [
'geopotential', 'temperature', 'u_component_of_wind',
'v_component_of_wind', 'vertical_velocity',
],
'pressure_level': [
'1', '2', '3',
'5', '7', '10',
'20',
],
'year': str(year),
'month': str(month),
'day': days,
'time': [
'00:00', '01:00', '02:00',
'03:00', '04:00', '05:00',
'06:00', '07:00', '08:00',
'09:00', '10:00', '11:00',
'12:00', '13:00', '14:00',
'15:00', '16:00', '17:00',
'18:00', '19:00', '20:00',
'21:00', '22:00', '23:00',
],
'area': [
north_lim, west_lim, south_lim,
east_lim,
],
})
floating.download(name)
##ERAsingle(2018, 5, startdays, 90, 45, 180, -180, "single_2018_1.nc")
##ERAsingle(2018, 6, days, 90, 45, 180, -180, "single_2018_2.nc")
##ERAsingle(2018, 7, days, 90, 45, 180, -180, "single_2018_3.nc")
##ERAsingle(2018, 8, endfloat, 90, 45, 180, -180, "single_2018_4.nc")
##ERAlevelAscend(2018, 5, startdays, start_lat, start_lon, "ascend_2018_kiruna_1.nc") # start_lat = 67.887382 Kiruna
ERAlevelAscend(2018, 6, endascent, start_lat, start_lon, "ascend_2018_kiruna_2.nc") # start_lon = 21.081452
ERAlevelFloat(2018, 5, startdays, 90, 45, -180, 180, "float_2018_1.nc")
ERAlevelFloat(2018, 6, days, 90, 45, -180, 180, "float_2018_2.nc")
ERAlevelFloat(2018, 7, days, 90, 45, -180, 180, "float_2018_3.nc")
ERAlevelFloat(2018, 8, endfloat, 90, 45, -180, 180, "float_2018_4.nc")
#ERAlevelAscend(2016, 7, ['12', '13', '14'], start_lat, start_lon, "ascend_2016_kiruna_new.nc")
#ERAsingle(2016, 7, ['12', '13', '14', '15', '16', '17', '18', '19'], 90, 45, 180, -180, "single_2016_new.nc")
#ERAlevelFloat(2016, 7, ['12', '13', '14', '15', '16', '17', '18', '19'], 90, 45, -180, 180, "float_2016_new.nc")