easyclimate.field.air_sea_interaction.index_enso

ENSO Index

Functions

calc_index_nino1and2(, lat_dim, lon_dim, time_dim, ...)

Calculate the Niño 1+2 index.

calc_index_nino3(, lat_dim, lon_dim, time_dim, normalized)

Calculate the Niño 3 index.

calc_index_nino34(, lat_dim, lon_dim[, running_mean])

Calculate the Niño 3.4 index.

calc_index_OMI(, lat_dim, lon_dim[, running_mean])

Calculate the ONI (Oceanic Niño Index) index.

calc_index_nino4(, lat_dim, lon_dim, time_dim, normalized)

Calculate the Niño 4 index.

Module Contents

easyclimate.field.air_sea_interaction.index_enso.calc_index_nino1and2(sst_monthly_data: xarray.DataArray | xarray.Dataset, time_range: slice = slice(None, None), lat_dim: str = 'lat', lon_dim: str = 'lon', time_dim: str = 'time', normalized: bool = False) → xarray.DataArray | xarray.Dataset

Calculate the Niño 1+2 index.

The Niño 1+2 region (0°-10°S, 90°W-80°W) is the smallest and eastern-most of the Niño SST regions, and corresponds with the region of coastal South America where El Niño was first recognized by the local populations. This index tends to have the largest variance of the Niño SST indices.

Parameters

sst_monthly_data: xarray.DataArray.

The monthly sea surface temperature (SST) dataset.

time_range: slice, default: slice(None, None).

The time range of seasonal cycle means to be calculated. The default value is the entire time range.

lat_dim: str, default: lat.

Latitude coordinate dimension name. By default extracting is applied over the lat dimension.

lon_dim: str, default: lon.

Longitude coordinate dimension name. By default extracting is applied over the lon dimension.

time_dim: str, default: time.

The time coordinate dimension name.

normalized: bool, default False, optional.

Whether to standardize the index based on standard deviation over time_range.

Returns

Niño 1+2 index.

Reference

easyclimate.field.air_sea_interaction.index_enso.calc_index_nino3(sst_monthly_data: xarray.DataArray | xarray.Dataset, time_range: slice = slice(None, None), lat_dim: str = 'lat', lon_dim: str = 'lon', time_dim: str = 'time', normalized: bool = False) → xarray.DataArray | xarray.Dataset

Calculate the Niño 3 index.

This region (5°N-5°S, 150°W-90°W) was once the primary focus for monitoring and predicting El Niño, but researchers later learned that the key region for coupled ocean-atmosphere interactions for ENSO lies further west (Trenberth, 1997). Hence, the Niño 3.4 and ONI became favored for defining El Niño and La Niña events.

Parameters

sst_monthly_data: xarray.DataArray.

The monthly sea surface temperature (SST) dataset.

time_range: slice, default: slice(None, None).

The time range of seasonal cycle means to be calculated. The default value is the entire time range.

lat_dim: str, default: lat.

Latitude coordinate dimension name. By default extracting is applied over the lat dimension.

lon_dim: str, default: lon.

Longitude coordinate dimension name. By default extracting is applied over the lon dimension.

time_dim: str, default: time.

The time coordinate dimension name.

normalized: bool, default False, optional.

Whether to standardize the index based on standard deviation over time_range.

Returns

Niño 3 index.

Reference

easyclimate.field.air_sea_interaction.index_enso.calc_index_nino34(sst_monthly_data: xarray.DataArray | xarray.Dataset, time_range: slice = slice(None, None), lat_dim: str = 'lat', lon_dim: str = 'lon', running_mean=5, time_dim: str = 'time', normalized: bool = False) → xarray.DataArray | xarray.Dataset

Calculate the Niño 3.4 index.

The Niño 3.4 (5°N-5°S, 170°W-120°W) anomalies may be thought of as representing the average equatorial SSTs across the Pacific from about the dateline to the South American coast. The Niño 3.4 index typically uses a 5-month running mean, and El Niño or La Niña events are defined when the Niño 3.4 SSTs exceed +/- 0.4℃ for a period of six months or more.

Parameters

sst_monthly_data: xarray.DataArray.

The monthly sea surface temperature (SST) dataset.

time_range: slice, default: slice(None, None).

The time range of seasonal cycle means to be calculated. The default value is the entire time range.

lat_dim: str, default: lat.

Latitude coordinate dimension name. By default extracting is applied over the lat dimension.

lon_dim: str, default: lon.

Longitude coordinate dimension name. By default extracting is applied over the lon dimension.

running_mean: int, default: 5.

Running mean value. If running_mean is None or 0, it will not perform running average operation.

time_dim: str, default: time.

The time coordinate dimension name.

normalized: bool, default False, optional.

Whether to standardize the index based on standard deviation over time_range.

Returns

Niño 3.4 index.

Reference

easyclimate.field.air_sea_interaction.index_enso.calc_index_OMI(sst_monthly_data: xarray.DataArray | xarray.Dataset, time_range: slice = slice(None, None), lat_dim: str = 'lat', lon_dim: str = 'lon', running_mean=3, time_dim: str = 'time', normalized: bool = False) → xarray.DataArray | xarray.Dataset

Calculate the ONI (Oceanic Niño Index) index.

The ONI (5°N-5°S, 170°W-120°W) uses the same region as the Niño 3.4 index. The ONI uses a 3-month running mean, and to be classified as a full-fledged El Niño or La Niña, the anomalies must exceed +0.5℃ or -0.5℃ for at least five consecutive months. This is the operational definition used by NOAA.

Parameters

sst_monthly_data: xarray.DataArray.

The monthly sea surface temperature (SST) dataset.

time_range: slice, default: slice(None, None).

The time range of seasonal cycle means to be calculated. The default value is the entire time range.

lat_dim: str, default: lat.

Latitude coordinate dimension name. By default extracting is applied over the lat dimension.

lon_dim: str, default: lon.

Longitude coordinate dimension name. By default extracting is applied over the lon dimension.

running_mean: int, default: 3.

Running mean value. If running_mean is None or 0, it will not perform running average operation.

time_dim: str, default: time.

The time coordinate dimension name.

normalized: bool, default False, optional.

Whether to standardize the index based on standard deviation over time_range.

Returns

ONI index.

Reference

easyclimate.field.air_sea_interaction.index_enso.calc_index_nino4(sst_monthly_data: xarray.DataArray | xarray.Dataset, time_range: slice = slice(None, None), lat_dim: str = 'lat', lon_dim: str = 'lon', time_dim: str = 'time', normalized: bool = False) → xarray.DataArray | xarray.Dataset

Calculate the Niño 4 index.

The Niño 4 index (5°N-5°S, 160°E-150°W) captures SST anomalies in the central equatorial Pacific. This region tends to have less variance than the other Niño regions.

Parameters

sst_monthly_data: xarray.DataArray.

The monthly sea surface temperature (SST) dataset.

time_range: slice, default: slice(None, None).

The time range of seasonal cycle means to be calculated. The default value is the entire time range.

lat_dim: str, default: lat.

Latitude coordinate dimension name. By default extracting is applied over the lat dimension.

lon_dim: str, default: lon.

Longitude coordinate dimension name. By default extracting is applied over the lon dimension.

time_dim: str, default: time.

The time coordinate dimension name.

normalized: bool, default False, optional.

Whether to standardize the index based on standard deviation over time_range.

Returns

Niño 4 index.

Reference