pcmdi_metrics.sea_ice.calc_iiee_annual_cycle

pcmdi_metrics.sea_ice.calc_iiee_annual_cycle(ds_obs, ds_model, obs_data_var='ice_conc', model_data_var='siconc', syear=1988, eyear=2014, identifier=None, save_dir='output', debug=False)[source]

Compute the monthly climatological annual cycle of Integrated Ice-Edge Error (IIEE) between observational and model sea ice concentration datasets.

The function subsets the input datasets to the requested time range, computes monthly climatologies, evaluates IIEE for each month, and optionally saves monthly comparison plots plus a seasonal-cycle summary plot.

Parameters:

  • ds_obs (xarray.Dataset) – Observational dataset containing sea ice concentration and a status_flag variable used to identify land points on the observational grid.

  • ds_model (xarray.Dataset) – Model dataset containing sea ice concentration to compare with the observations.

  • obs_data_var (str, optional) – Name of the observational sea ice concentration variable in ds_obs. Default is "ice_conc".

  • model_data_var (str, optional) – Name of the model sea ice concentration variable in ds_model. Default is "siconc".

  • syear (int, optional) – Starting year of the analysis period, inclusive. Default is 1988.

  • eyear (int, optional) – Ending year of the analysis period, inclusive. Default is 2014.

  • identifier (str, optional) – Text identifier that to be added to diagnostics’ headser and as a part of output files

  • save_dir (str or None, optional) – Directory where figures are saved. If None, figures are not saved. Default is "output".

  • debug (bool, optional) – If True, print additional diagnostic information. Default is False.

Returns:

dict – Dictionary containing metadata and monthly IIEE metrics.

Examples

This function is mainly intended for development testing or command-line execution. In package usage, call calc_iiee_annual_cycle() directly:

>>> import xcdat as xc
>>> ds_obs = xc.open_dataset("data/ice_conc_nh_ease2-250_cdr-v3p0_198801-202012.nc")
>>> ds_model = xc.open_mfdataset("data/siconc_SImon_E3SM-1-0_historical_r1i1p1f1_*_*.nc")
>>> from pcmdi_metrics.sea_ice import calc_iiee_annual_cycle
>>> result = calc_iiee_annual_cycle(
...     ds_obs=ds_obs,
...     ds_model=ds_model,
...     obs_data_var="ice_conc",
...     model_data_var="siconc",
...     syear=2010,
...     eyear=2014,
...     save_dir="output",
... )