mesmer.create_emulations.create_emus_lv_AR1_sci

mesmer.create_emulations.create_emus_lv_AR1_sci#

mesmer.create_emulations.create_emus_lv_AR1_sci(emus_lv, params_lv, preds_lv, cfg)#

Create local variablity emulations with AR(1) process with spatially-correlated innovations.

Parameters:
  • emus_lv (dict) – local variability emulations dictionary with keys

    • [scen] 3d array (emu, time, gp) of local variability from previous submethods

    • empty dict if no previous submethod

  • params_lv (dict) – dictionary with the trained local variability parameters

    • [“targ”] (variable which is emulated, str)

    • [“esm”] (Earth System Model, str)

    • [“method”] (applied method, str)

    • [“preds”] (predictors, list of strs)

    • [“scenarios”] (scenarios which are used for training, list of strs)

    • [xx] (additional keys depend on employed method)

  • preds_lv (dict) – nested dictionary of predictors for local variability with keys

    • [pred][scen] 1d/ 2d arrays (time)/(run, time) of predictor for specific scenario

  • cfg (module) – config file containing metadata

Returns:

emus_lv (dict) – local variability emulations dictionary with keys

  • [scen] (2d array (emu, time, gp) of local variability in response to global variability emulation time series)

Notes

  • Assumptions:
    • do for each target variable independently.

    • the variability is Gaussian

  • Long-term TODO:
    • add possibility to account for cross-correlation between different variables