weatherbench2.metrics.SpatialSEEPS
- class weatherbench2.metrics.SpatialSEEPS(climatology, dry_threshold_mm=0.25, precip_name='total_precipitation_24hr', min_p1=0.1, max_p1=0.85)
Computes Stable Equitable Error in Probability Space.
Definition in Rodwell et al. (2010): https://www.ecmwf.int/en/elibrary/76205-new-equitable-score-suitable-verifying-precipitation-nwp
- Parameters:
climatology (Dataset) –
dry_threshold_mm (float) –
precip_name (str) –
min_p1 (float) –
max_p1 (float) –
- climatology
climatology dataset containing seeps_threshold [meters] and seeps_dry_fraction [0-1] for given precip_name.
- Type:
xarray.core.dataset.Dataset
- dry_threshold_mm
Dry threhsold in mm, same as used to compute climatological values.
- Type:
float
- precip_name
Name of precipitation variable, e.g. total_precipitation_24hr.
- Type:
str
- min_p1
Mask out values with smaller average dry fraction.
- Type:
float
- max_p1
Mask out values with larger average dry fraction.
- Type:
float
- p1
Average dry fraction.
- __init__(climatology, dry_threshold_mm=0.25, precip_name='total_precipitation_24hr', min_p1=0.1, max_p1=0.85)
- Parameters:
climatology (Dataset) –
dry_threshold_mm (float) –
precip_name (str) –
min_p1 (float) –
max_p1 (float) –
- Return type:
None
Methods
__init__(climatology[, dry_threshold_mm, ...])compute(forecast, truth[, region, skipna])Evaluate this metric on datasets with full temporal coverages.
compute_chunk(forecast, truth[, region, skipna])Evaluate this metric on a temporal chunk of data.
Attributes