Script for download and stitching of ERA5 atmospheric data
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@ -47,7 +47,7 @@ Operations you want to be performed:
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ascent_only = False # True # get only ERA5 data for ascent (e. g. for new location or time within same region)
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download = False # True # download raw ERA5 files
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stitch = True # False # create stitched files
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delete = False # False # delete original files
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delete = True # False # delete original files
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"""
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@ -328,32 +328,28 @@ if stitch == True:
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if ascent_only == True:
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pass
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else:
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df1 = xr.open_mfdataset(floatfiles, chunks={'time': 100}, combine="nested", engine='netcdf4', concat_dim="time",
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parallel=True)
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df1 = df1.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
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df1.to_netcdf(os.path.join(folder,
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"FLOAT_" + str(ident2) + "_" + str(start.year) + str(start.month) + "_to_" + str(
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end.year) + str(end.month) + ".nc"), mode='w', format="NETCDF4",
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engine="netcdf4",
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encoding={"z": {"dtype": "float32"}, "t": {"dtype": "float32"}, "u": {"dtype": "float32"},
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"v": {"dtype": "float32"}, "w": {"dtype": "float32"}})
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df2 = xr.open_mfdataset(singlefiles, chunks={'time': 500}, combine="nested", engine='netcdf4',
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concat_dim="time",
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parallel=True)
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df2 = df2.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
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df2.to_netcdf(os.path.join(folder,
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"RAD_" + str(ident2) + "_" + str(start.year) + str(start.month) + "_to_" + str(
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end.year) + str(end.month) + ".nc"), mode='w', format="NETCDF4",
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engine="netcdf4",
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encoding={"cbh": {"dtype": "float32"}, "hcc": {"dtype": "float32"}, "lcc": {"dtype": "float32"},
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"mcc": {"dtype": "float32"}, "skt": {"dtype": "float32"}, "ssr": {"dtype": "float32"},
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"str": {"dtype": "float32"}, "sp": {"dtype": "float32"}, "ssrd": {"dtype": "float32"},
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"strdc": {"dtype": "float32"}, "strd": {"dtype": "float32"},
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"tisr": {"dtype": "float32"},
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"tsr": {"dtype": "float32"}, "ttr": {"dtype": "float32"}, "tcc": {"dtype": "float32"},
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"fdir": {"dtype": "float32"}})
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with xr.open_mfdataset(floatfiles, chunks={'time': 100}, combine="nested", engine='netcdf4', concat_dim="time", parallel=True) as df1:
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df1 = df1.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
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df1.to_netcdf(os.path.join(folder, "FLOAT_" + str(ident2) + "_" + str(start.year) + str(start.month) + "_to_" + str(end.year) + str(end.month) + ".nc"),
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mode='w', format="NETCDF4", engine="netcdf4",
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encoding={"z": {"dtype": "float32"}, "t": {"dtype": "float32"}, "u": {"dtype": "float32"}, "v": {"dtype": "float32"}, "w": {"dtype": "float32"}})
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with xr.open_mfdataset(singlefiles, chunks={'time': 500}, combine="nested", engine='netcdf4', concat_dim="time", parallel=True) as df2:
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df2 = df2.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
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df2.to_netcdf(os.path.join(folder, "RAD_" + str(ident2) + "_" + str(start.year) + str(start.month) + "_to_" + str(end.year) + str(end.month) + ".nc"),
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mode='w', format="NETCDF4",
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engine="netcdf4",
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encoding={"cbh": {"dtype": "float32"}, "hcc": {"dtype": "float32"},
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"lcc": {"dtype": "float32"},
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"mcc": {"dtype": "float32"}, "skt": {"dtype": "float32"},
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"ssr": {"dtype": "float32"},
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"str": {"dtype": "float32"}, "sp": {"dtype": "float32"},
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"ssrd": {"dtype": "float32"},
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"strdc": {"dtype": "float32"}, "strd": {"dtype": "float32"},
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"tisr": {"dtype": "float32"},
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"tsr": {"dtype": "float32"}, "ttr": {"dtype": "float32"},
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"tcc": {"dtype": "float32"},
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"fdir": {"dtype": "float32"}})
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startfile = Dataset(ascentfiles[0], "r", format="NETCDF4")
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endfile = Dataset(ascentfiles[-1], "r", format="NETCDF4")
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@ -364,15 +360,13 @@ if stitch == True:
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startfile.close()
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endfile.close()
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df3 = xr.open_mfdataset(ascentfiles, chunks={'time': 800}, combine="nested", engine='netcdf4', concat_dim="time",
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parallel=True)
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df3 = df3.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
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df3.to_netcdf(os.path.join(folder, "ASCENT_" + str(ident1) + "_" + str(start.year) + str(start.month) + ".nc"),
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mode='w', format="NETCDF4", engine="netcdf4",
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encoding={"z": {"dtype": "float32"}, "t": {"dtype": "float32"}, "u": {"dtype": "float32"},
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"v": {"dtype": "float32"}, "w": {"dtype": "float32"}})
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print("Stitching finished!")
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with xr.open_mfdataset(ascentfiles, chunks={'time': 800}, combine="nested", engine='netcdf4', concat_dim="time", parallel=True) as df3:
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df3 = df3.assign_coords(time=np.linspace(tstart, tend, (tend - tstart) + 1))
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df3.to_netcdf(os.path.join(folder, "ASCENT_" + str(ident1) + "_" + str(start.year) + str(start.month) + ".nc"),
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mode='w', format="NETCDF4", engine="netcdf4",
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encoding={"z": {"dtype": "float32"}, "t": {"dtype": "float32"}, "u": {"dtype": "float32"},
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"v": {"dtype": "float32"}, "w": {"dtype": "float32"}})
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print("Stitching finished!")
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else:
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pass
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