BASTET/DataRequest.py

import os
import sys
import cdsapi
from datetime import datetime
from datetime import date
import numpy as np
import xarray as xr
from netCDF4 import Dataset
from dask.diagnostics import ProgressBar

folder = "ERA5"
ident = "McMurdo"



north_lim, south_lim, east_lim, west_lim = 90, 45, 180, -180  # Northern Polar Region
# north_lim, south_lim, east_lim, west_lim = -45, -90, 180, -180  # Southern Polar Region

start_lat = 67.887382  # Kiruna
start_lon = 21.081452

# SOME START LOCATIONS:

# start_lat = 78.22  # Svalbard
# start_lon = 15.65
#
# start_lat = -77.8535  # McMurdo
# start_lon = 167.2022

startdate = '2019-12-15'
enddate = '2020-01-10'

try:
    os.makedirs(folder)
except FileExistsError:
    pass


start = datetime.fromisoformat(startdate)
end = datetime.fromisoformat(enddate)

#"""
# DOWNLOAD OF ERA5-DATA:

startdays = [str(start.day+i).zfill(2) for i in range((date(start.year, start.month + 1, 1) - date(start.year, start.month, 1)).days - start.day + 1)]
endascent = [str(i+1).zfill(2) for i in range(30 - len(startdays))]
days = [str(i+1).zfill(2) for i in range(31)]
endfloat = [str(i+1).zfill(2) for i in range(end.day)]


def ERAsingle(year, month, days, nlim, slim, elim, wlim, name):
    single = cdsapi.Client().retrieve(
        'reanalysis-era5-single-levels',
        {
            'product_type': 'reanalysis',
            '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': [
            nlim, wlim, slim, elim,
            ],
            'format': 'netcdf',
        })
    single.download(name)


def ERAlevelAscent(year, month, dayrange, start_lat, start_lon, name):
    nlim = start_lat + 10.0
    slim = start_lat - 10.0
    elim = start_lon + 10.0
    wlim = start_lon - 10.0

    ascent = cdsapi.Client().retrieve(
        'reanalysis-era5-pressure-levels',
        {
            'product_type': 'reanalysis',
            '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': dayrange,
            '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': [
            nlim, wlim, slim, elim,
            ],
            'format': 'netcdf',
        })
    ascent.download(name)


def ERAlevelFloat(year, month, dayrange, nlim, slim, elim, wlim, name):
    floating = cdsapi.Client().retrieve(
        'reanalysis-era5-pressure-levels',
        {
            'product_type': 'reanalysis',
            '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': dayrange,
            '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': [
            nlim, wlim, slim, elim,
            ],
            'format': 'netcdf',
        })
    floating.download(name)


ERAlevelAscent(start.year, start.month, startdays, start_lat, start_lon, os.path.join(folder, "ascent1.nc"))
ERAlevelAscent(start.year, start.month + 1, endascent, start_lat, start_lon, os.path.join(folder, "ascent2.nc"))

ERAsingle(start.year, start.month, startdays, north_lim, south_lim, east_lim, west_lim, os.path.join(folder, "single" + str(start.month) + ".nc"))
ERAlevelFloat(start.year, start.month, startdays, north_lim, south_lim, east_lim, west_lim, os.path.join(folder, "float" + str(start.month) + ".nc"))

for m in range(end.month - start.month - 1):
    ERAsingle(start.year, start.month + m + 1, days, north_lim, south_lim, east_lim, west_lim, os.path.join(folder, "single" + str(start.month + m + 1) + ".nc"))
    ERAlevelFloat(start.year, start.month + m + 1, days, north_lim, south_lim, east_lim, west_lim, os.path.join(folder, "float" + str(start.month + m + 1) + ".nc"))

ERAsingle(start.year, end.month, endfloat, north_lim, south_lim, east_lim, west_lim, os.path.join(folder, "single" + str(end.month) + ".nc"))
ERAlevelFloat(start.year, end.month, endfloat, north_lim, south_lim, east_lim, west_lim, os.path.join(folder, "float" + str(end.month) + ".nc"))

#"""

# STITCHING OF MULTIPLE *.NC-FILES TO ONE:

floatfiles = []
singlefiles = []
ascentfiles = []


for (root, dirs, files) in os.walk("ERA5"):
    for name in files:
        if name.startswith("float"):
            floatfiles.append(os.path.join(folder, str(name)))
        elif name.startswith("radiation"):
            singlefiles.append(os.path.join(folder, str(name)))
        else:
            ascentfiles.append(os.path.join(folder, str(name)))


startfile = Dataset(floatfiles[0], "r", format="NETCDF4")
endfile = Dataset(floatfiles[-1], "r", format="NETCDF4")

tstart = int(startfile.variables['time'][0])
tend = int(endfile.variables['time'][-1])

startfile.close()
endfile.close()

df1 = xr.open_mfdataset(floatfiles, chunks={'time': 100}, combine="nested", engine='netcdf4', concat_dim="time", parallel=True)
df1 = df1.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
df1.to_netcdf(os.path.join(folder, "FLOAT_" + str(ident) + "_" + str(start.year) + "_" + str(start.month) + "to" + str(end.year) + "_" + str(end.month) + ".nc"), mode='w', format="NETCDF4", engine="netcdf4", encoding={"z": {"dtype": "float32"}, "t": {"dtype": "float32"}, "u": {"dtype": "float32"}, "v": {"dtype": "float32"}, "w": {"dtype": "float32"}})

df2 = xr.open_mfdataset(singlefiles, chunks={'time': 500}, combine="nested", engine='netcdf4', concat_dim="time", parallel=True)
df2 = df2.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
df2.to_netcdf(os.path.join(folder, "SINGLE_" + str(ident) + "_" + str(start.year) + "_" + str(start.month) + "to" + str(end.year) + "_" + str(end.month) + ".nc"), mode='w', format="NETCDF4", engine="netcdf4", encoding={"cbh": {"dtype": "float32"}, "hcc": {"dtype": "float32"}, "lcc": {"dtype": "float32"}, "mcc": {"dtype": "float32"}, "skt": {"dtype": "float32"}, "ssr": {"dtype": "float32"}, "str": {"dtype": "float32"}, "sp": {"dtype": "float32"}, "ssrd": {"dtype": "float32"}, "strdc": {"dtype": "float32"}, "strd": {"dtype": "float32"}, "tisr": {"dtype": "float32"}, "tsr": {"dtype": "float32"}, "ttr": {"dtype": "float32"}, "tcc": {"dtype": "float32"}, "fdir": {"dtype": "float32"}})

startfile = Dataset(ascentfiles[0], "r", format="NETCDF4")
endfile = Dataset(ascentfiles[-1], "r", format="NETCDF4")

tstart = int(startfile.variables['time'][0])
tend = int(endfile.variables['time'][-1])

startfile.close()
endfile.close()

df3 = xr.open_mfdataset(ascentfiles, chunks={'time': 800}, combine="nested", engine='netcdf4', concat_dim="time", parallel=True)
df3 = df3.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
df3.to_netcdf(os.path.join(folder, "ASCENT_" + str(ident) + "_" + str(start.year) + "_" + str(start.month) + ".nc"), mode='w', format="NETCDF4", engine="netcdf4", encoding={"z": {"dtype": "float32"}, "t": {"dtype": "float32"}, "u": {"dtype": "float32"}, "v": {"dtype": "float32"}, "w": {"dtype": "float32"}})


# DELETING ORIGINAL FILES:

"""
for (root, dirs, files) in os.walk("ERA5"):
    for name in files:
        if name in floatfiles + singlefiles + ascentfiles:
            os.remove(name)
        else:
            pass
"""