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temperature_zone

generate_temperature_zone_main(gcm_member: str, scenario: str, output_dir: str | Path) -> None

Generate the temperature zone for a given scenario and gcm member.

Parameters

gcm_member The gcm member to generate the temperature zone for. scenario The scenario to generate the temperature zone for. Pass historical (with gcm_member="era5") to build a pure-ERA5 zone from the raw historical annual mean temperature rather than the compiled historical+forecast series; the output then spans EXPOSURE_START_YEAR through the last historical year present on disk. output_dir The directory to save the temperature zone to (root for this run mode).

Source code in src/climate_data/special/temperature_zone.py 
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def generate_temperature_zone_main(
    gcm_member: str,
    scenario: str,
    output_dir: str | Path,
) -> None:
    """Generate the temperature zone for a given scenario and gcm member.

    Parameters
    ----------
    gcm_member
        The gcm member to generate the temperature zone for.
    scenario
        The scenario to generate the temperature zone for.  Pass ``historical``
        (with ``gcm_member="era5"``) to build a pure-ERA5 zone from the raw
        historical annual mean temperature rather than the compiled
        historical+forecast series; the output then spans ``EXPOSURE_START_YEAR``
        through the last historical year present on disk.
    output_dir
        The directory to save the temperature zone to (root for this run mode).
    """
    print(f"Generating temperature zone for {scenario} {gcm_member}")
    cdata = ClimateData(output_dir)
    if scenario == "historical":
        ds = cdata.load_raw_annual_mfdataset("historical", "mean_temperature")
    else:
        ds = cdata.load_compiled_annual_results(
            scenario, "mean_temperature", gcm_member
        )
    temperature_zone = (
        ds.rolling(year=10)
        .mean()
        .sel(year=slice(cdc.EXPOSURE_START_YEAR, int(cdc.FORECAST_YEARS[-1])))
    )
    print(f"Saving temperature zone for {scenario} {gcm_member}")
    cdata.save_compiled_annual_results(
        temperature_zone,
        scenario=scenario,
        variable="temperature_zone",
        gcm_member=gcm_member,
        encoding_kwargs={"scale_factor": 0.01, "add_offset": 0.0},
    )