easyclimate.field.air_sea_interaction.index_pdo

Pacific Decadal Oscillation (PDO) Index

Functions

calc_index_PDO_EOF1(, lon_dim, lat_dim, time_dim, ...)

The calculation of monthly mean Pacific Decadal Oscillation (PDO) index using empirical orthogonal functions (EOFs) method over the North Pacific basin.

Module Contents

easyclimate.field.air_sea_interaction.index_pdo.calc_index_PDO_EOF1(sst_monthly_data: xarray.DataArray, time_range: slice = slice(None, None), lon_dim: str = 'lon', lat_dim: str = 'lat', time_dim: str = 'time', random_state: int | None = None, solver: Literal['auto', 'full', 'randomized'] = 'auto', solver_kwargs: dict = {}, normalized: bool = True, detrend_spatial: bool = True) xarray.DataArray

The calculation of monthly mean Pacific Decadal Oscillation (PDO) index using empirical orthogonal functions (EOFs) method over the North Pacific basin.

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.

lon_dim: str, default: lon.

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

lat_dim: str, default: lat.

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

time_dim: str, default: time.

The time coordinate dimension name.

random_state: int, default None.

Seed for the random number generator.

solver: {“auto”, “full”, “randomized”}, default: “auto”.

Solver to use for the EOFs computation.

solver_kwargs: dict, default {}.

Additional keyword arguments to be passed to the EOFs solver.

normalized: bool, default True, optional.

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

normalized: bool, default True, optional.

Remove linear trend along time coordinate dimension from data.

Returns

The monthly mean PDO index (xarray.DataArray).

Reference

See also

get_EOF_model