mesmer.create_emulations.create_emus_lv(params_lv, preds_lv, cfg, save_emus=True, submethod='')#

Create local variablity emulations.

  • 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

  • save_emus (bool, optional) – determines if emulation is saved or not, default = True

  • submethod (str, optional) – determines if only submethod should be used, default = “” indicating using the full method


emus_lv (dict) – local variability emulations dictionary with keys

  • [scen] (3d array (emu, time, gp) of local variability emulation time series)


  • Assumptions:
    • if stochastic realizations are drawn, preds_lv must contain concatenated hist + future scenarios or only future scenarios

    • if no preds_lv needed, pass time as predictor instead such that can get info about how many scenarios / ts per scenario should be drawn for stochastic part

    • submethod specific assumptions are listed in the submethod description

  • Long-term TODO:
    • improve consistency with actual esms by sharing same realizations in historical time period and diff one for each scen in future

    • improve this function in terms of generalization properties + design (+ consistency with rest of code)

    • improve function to also work if only part of predictors are used for OLS and others for other methods