Predictors

LOTUS_regression.predictors.download.load_aao()[source]
LOTUS_regression.predictors.download.load_ao()[source]

Loads the arctic oscillation index from ncep

LOTUS_regression.predictors.download.load_eesc()[source]

Calculates an EESC from the polynomial values [9.451393e-10, -1.434144e-7, 8.5901032e-6, -0.0002567041, 0.0040246245, -0.03355533, 0.14525718, 0.71710218, 0.1809734]

LOTUS_regression.predictors.download.load_ehf(filename)[source]

Loads the eddy heat flux data from the file erai_ehf_monthly_1978_2016.txt provided on the LOTUS ftp server in the folder Proxies-Weber

LOTUS_regression.predictors.download.load_enso(lag_months=0)[source]

Downloads the ENSO from https://www.esrl.noaa.gov/psd/enso/mei/data/meiv2.data

Parameters:

lag_months (int, Optional. Default 0) – The numbers of months of lag to introduce to the ENSO signal

LOTUS_regression.predictors.download.load_giss_aod()[source]

Loads the giss aod index from giss

LOTUS_regression.predictors.download.load_glossac_aod()[source]
LOTUS_regression.predictors.download.load_independent_linear(pre_trend_end='1997-01-01', post_trend_start='2000-01-01')[source]

Creates the predictors required for performing independent linear trends.

Parameters:
  • pre_trend_end (str, Optional. Default '1997-01-01') –

  • post_trend_start (str, Optional. Default '2000-01-01') –

LOTUS_regression.predictors.download.load_linear(inflection=1997)[source]

Returns two piecewise linear components with a given inflection point in value / decade.

Parameters:

inflection (int, Optional. Default 1997) –

LOTUS_regression.predictors.download.load_nao()[source]

Loads the north atlantic oscillation index from noaa :return:

LOTUS_regression.predictors.download.load_orthogonal_eesc(filename)[source]

Calculates two orthogonal eesc terms from the predicted eesc at 6 different ages of air, uses the EESC.txt datafile from the LOTUS ftp server in the folder EESC_Damadeo

LOTUS_regression.predictors.download.load_qbo(pca=3)[source]

Loads the QBO from https://acd-ext.gsfc.nasa.gov/Data_services/met/qbo/QBO_Singapore_Uvals_GSFC.txt’. If pca is set to an integer (default 3) then that many principal components are taken. If pca is set to 0 then the raw QBO data is returned.

Parameters:

pca (int, optional. Default 3.) –

LOTUS_regression.predictors.download.load_solar()[source]

Gets the solar F10.7 from ‘https://spdf.gsfc.nasa.gov/pub/data/omni/low_res_omni/omni2_all_years.dat’.

LOTUS_regression.predictors.download.load_solar_mg2()[source]

Loads the bremen solar composite mg2 index

LOTUS_regression.predictors.download.load_trop(deseasonalize=True)[source]

Gets the tropical tropopause pressure from ftp.cdc.noaa.gov. The tropical tropopause pressure is automatically deseasonalized by default to remove the strong seasonal cycle.

Parameters:

deseasonalize (bool, optional. Default True) – If set to false deseasonalization will not be done.

LOTUS_regression.predictors.seasonal.add_seasonal_components(basis_df, num_components)[source]