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supy.util.gen_forcing_era5¶
-
supy.util.
gen_forcing_era5
(lat_x: float, lon_x: float, start: str, end: str, dir_save=PosixPath('.'), grid=[0.125, 0.125], hgt_agl_diag=100.0, scale=0, simple_mode=True) → list[source]¶ Generate SUEWS forcing files using ERA-5 data.
Parameters: - lat_x (float) – Latitude of centre at the area of interest.
- lon_x (float) – Longitude of centre at the area of interest.
- start (str) – Any datetime-like string that can be parsed by
pandas.daterange()
. - end (str) – Any datetime-like string that can be parsed by
pandas.daterange()
. - dir_save (Path or path-like string) – path to directory for saving downloaded ERA5 netCDF files.
- grid (list, optional) – grid size used in CDS request API, by default [0.125, 0.125].
- hgt_agl_diag (float) – height above ground level to diagnose forcing variables, by default 0; the ground level is taken from ERA5 grid altitude.
- scale (int, optional) – scaling factor that determines the area of interest (i.e.,
area=grid[0]*scale
), by default 0 - simple_mode (boolean) – if use the simple mode for diagnosing the forcing variables, by default
True
. In the simple mode, temperature is diagnosed using environmental lapse rate 6.5 K/km and wind speed using MOST under neutral condition. IfFalse
, MOST with consideration of stability conditions will be used to diagnose forcing variables.
Returns: A list of files in SUEWS forcing input format.
Return type: List
Note
- This function uses CDS API to download ERA5 data; follow this for configuration first: https://cds.climate.copernicus.eu/api-how-to
- The generated forcing files can be imported using
supy.util.read_forcing
to get simulation-ready `pandas.DataFrame`s. - See Section 3.10.2 and 3.10.3 in the reference for details of diagnostics calculation.
ECMWF, S. P. (2016). In IFS documentation CY41R2 Part IV: Physical Processes. ECMWF: Reading, UK, 111-113. https://www.ecmwf.int/en/elibrary/16648-part-iv-physical-processes