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])

Evaluate this metric on datasets with full temporal coverages.

compute_chunk(forecast, truth[, region])

Evaluate this metric on a temporal chunk of data.

Attributes

dry_threshold_mm

max_p1

min_p1

p1

precip_name

climatology