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process_era5.py
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from pathlib import Path
import numpy as np
import datetime as dt
from osgeo import gdal
from pyproj import Proj
import cdsapi
from meteo_utils import ecmwf_utils as eu
from meteo_utils import solar_irradiance as sun
METEO_DATA_FIELDS = ["TA", "EA", "WS", "PA", "AOT", "TCWV", "SW-IN", "LW-IN"]
CDS_VARIABLES = ['100m_u_component_of_wind',
'100m_v_component_of_wind',
'10m_u_component_of_wind',
'10m_v_component_of_wind',
'2m_dewpoint_temperature',
'2m_temperature',
'surface_pressure',
'surface_solar_radiation_downwards',
'surface_thermal_radiation_downwards',
'total_column_water_vapour',
'geopotential']
ADS_VARIABLES = ["total_aerosol_optical_depth_550nm"]
DAILY_VARS = ["ETr", "SW-IN-DD"]
def process_single_date(elev_input_file,
slope_input_file,
aspect_input_file,
date_int,
acq_time,
dst_folder=None,
svf_input_file=None,
blending_height=100):
"""
Parameters
----------
elev_input_file : str
Path to a GDAL compatible Digital Elevation Model
slope_input_file : str
Path to a GDAL compatible slope image (degrees)
aspect_input_file : str
Path to a GDAL compatible aspect image (0 for flat surfaces)
date_int : int or str
Acquisition date (YYYYMMDD)
acq_time : float
Acquistion time in decimal hour
dst_folder : str, optional
Path to the destination folder in which meteo products will be stored.
svf_input_file : str, optional
Path to a GDAL compatible Sky View Fraction image (0-1)
blending_height : float, optional
Elevation above ground level at which meteo products will be generated, default=100 magl
Returns
-------
output : dict
Dictionary of arrays with the output meteo products
"""
dst_folder = Path(dst_folder)
print(f"Downloading \"{', '.join(CDS_VARIABLES)}\" from the Copernicus Climate Store")
fid = gdal.Open(elev_input_file, gdal.GA_ReadOnly)
gt = fid.GetGeoTransform()
proj = fid.GetProjection()
p = Proj(proj)
minx = gt[0]
maxy = gt[3]
maxx = minx + gt[1] * fid.RasterXSize
miny = maxy + gt[5] * fid.RasterYSize
del fid
date_obj = dt.datetime.strptime(str(date_int), "%Y%m%d")
date_ini = (date_obj - dt.timedelta(1))
date_end = date_obj + dt.timedelta(1)
date_str = f"{date_ini.strftime('%Y-%m-%d')}/{date_end.strftime('%Y-%m-%d')}"
# Area is North, West, South, East
extent_geo = p(minx, maxy, inverse=True), p(maxx, miny, inverse=True)
area = [extent_geo[0][1] + 1, extent_geo[0][0] - 1,
extent_geo[1][1] - 1, extent_geo[1][0] + 1]
print(f"Querying products for extent {area}\n"
f"..and dates {date_obj - dt.timedelta(1)} to {date_obj + dt.timedelta(1)}")
# Connect to the server and download the data
s = {'data_format': 'grib',
'variable': CDS_VARIABLES,
'date': date_str,
'area': area,
'product_type': ["reanalysis"],
'time': [str(t).zfill(2) + ":00" for t in range(0, 24, 1)]}
cds_target = dst_folder / f"{date_int}_era5.grib"
if not cds_target.exists():
c = cdsapi.Client(quiet=True, progress=False)
print(f"Saving into {cds_target}")
c.retrieve('reanalysis-era5-single-levels', s, cds_target)
print(f"Saved to file {cds_target}")
# If we are working on the currrent year we need to query the forecast cams data, otherwise download reanalysis
if date_obj.year == dt.date.today().year:
dataset = "cams-global-atmospheric-composition-forecasts"
else:
dataset = "cams-global-reanalysis-eac4"
ads_target = dst_folder / f"{date_int}_cams.grib"
if not ads_target.exists():
print(f"Downloading \"{', '.join(ADS_VARIABLES)}\" "
f"from the Copernicus Atmospheric Store")
eu.download_ADS_data(dataset,
date_obj - dt.timedelta(1),
date_obj + dt.timedelta(1),
ADS_VARIABLES,
ads_target,
overwrite=False,
area=area)
print(f"Saved to file {ads_target}")
date_obj = date_obj + dt.timedelta(hours=acq_time)
time_zone = sun.angle_average(extent_geo[0][0], extent_geo[1][0]) / 15.
print(f"Processing ECMWF data for UTC time {date_obj}\n"
"This may take some time...")
meteo_data_fields = METEO_DATA_FIELDS + DAILY_VARS
output = eu.get_ECMWF_data(cds_target,
date_obj,
meteo_data_fields,
elev_input_file,
blending_height,
aod550_data_file=ads_target,
time_zone=time_zone,
is_forecast=False,
slope_file=slope_input_file,
aspect_file=aspect_input_file,
svf_file=svf_input_file)
out_dict = {}
if dst_folder:
for param, array in output.items():
if param not in DAILY_VARS:
hour = int(np.floor(acq_time))
minute = int(60 * acq_time - hour)
acq_time_str = f"{hour:02}{minute:02}"
if param == "SW-IN":
for i, var1 in enumerate(["DIR", "DIF"]):
for j, var2 in enumerate(["PAR", "NIR"]):
param = f"{var2}-{var1}"
filename = f"{date_int}T{acq_time_str}_{param.upper()}.tif"
dst_file = str(dst_folder / filename)
print(f"Saving {param} to {dst_file}")
driver = gdal.GetDriverByName("MEM")
values = np.maximum(array[i][j], 0)
dims = values.shape
ds = driver.Create("MEM", dims[1], dims[0], 1, gdal.GDT_Float32)
ds.SetProjection(proj)
ds.SetGeoTransform(gt)
ds.GetRasterBand(1).WriteArray(values)
driver_opt = ['COMPRESS=DEFLATE', 'PREDICTOR=1', 'BIGTIFF=IF_SAFER']
gdal.Translate(dst_file, ds, format="GTiff",
creationOptions=driver_opt, stats=True)
else:
filename = f"{date_int}T{acq_time_str}_{param.upper()}.tif"
dst_file = str(dst_folder / filename)
print(f"Saving {param} to {dst_file}")
driver = gdal.GetDriverByName("MEM")
dims = array.shape
ds = driver.Create("MEM", dims[1], dims[0], 1, gdal.GDT_Float32)
ds.SetProjection(proj)
ds.SetGeoTransform(gt)
ds.GetRasterBand(1).WriteArray(array)
driver_opt = ['COMPRESS=DEFLATE', 'PREDICTOR=1', 'BIGTIFF=IF_SAFER']
gdal.Translate(dst_file, ds, format="GTiff",
creationOptions=driver_opt, stats=True)
else:
filename = f"{date_int}_{param.upper()}.tif"
dst_file = str(dst_folder / filename)
print(f"Saving {param} to {dst_file}")
driver = gdal.GetDriverByName("MEM")
dims = array.shape
ds = driver.Create("MEM", dims[1], dims[0], 1, gdal.GDT_Float32)
ds.SetProjection(proj)
ds.SetGeoTransform(gt)
ds.GetRasterBand(1).WriteArray(array)
driver_opt = ['COMPRESS=DEFLATE', 'PREDICTOR=1', 'BIGTIFF=IF_SAFER']
gdal.Translate(dst_file, ds, format="GTiff",
creationOptions=driver_opt, stats=True)
del ds
return output
if __name__ == "__main__":
elev_input_file = "/path/to/the/dem/file"
slope_input_file = "/path/to/the/slope/file" # In degrees
aspect_input_file = "/path/to/the/aspect/file" # 0 for flat
svf_input_file = "/path/to/the/sky/view/fraction/file" # 0-1
elev_input_file = "./test/dem.tif"
slope_input_file = "./test/slope.tif"
aspect_input_file = "./test/aspect.tif"
svf_input_file = "./test/svf.tif"
date_int = 20210612 # YYYYMMDD
acq_time = 11.5 # Decimal hour
dst_folder = "./test"
blending_height = 100 # m above ground level at which meteo will be produced
process_single_date(elev_input_file,
slope_input_file,
aspect_input_file,
date_int,
acq_time,
dst_folder,
svf_input_file=svf_input_file,
blending_height=100)