CategoricalEnsCombination {CSTools} | R Documentation |
This function converts a multi-model ensemble forecast into a categorical forecast by giving the probability for each category. Different methods are available to combine the different ensemble forecasting models into probabilistic categorical forecasts.
See details in ?CST_CategoricalEnsCombination
CategoricalEnsCombination(fc, obs, cat.method, eval.method, amt.cat, ...)
fc |
a multi-dimensional array with named dimensions containing the seasonal forecast experiment data in the element named |
obs |
a multidimensional array with named dimensions containing the observed data in the element named |
cat.method |
method used to produce the categorical forecast, can be either |
eval.method |
is the sampling method used, can be either |
amt.cat |
is the amount of categories. Equally-sized quantiles will be calculated based on the amount of categories. |
... |
other parameters to be passed on to the calibration procedure. |
an array containing the categorical forecasts in the element called $data
. The first two dimensions of the returned object are named dataset and member and are both of size one. An additional dimension named category is introduced and is of size amt.cat.
Bert Van Schaeybroeck, bertvs@meteo.be
Rajagopalan, B., Lall, U., & Zebiak, S. E. (2002). Categorical climate forecasts through regularization and optimal combination of multiple GCM ensembles. Monthly Weather Review, 130(7), 1792-1811.
Robertson, A. W., Lall, U., Zebiak, S. E., & Goddard, L. (2004). Improved combination of multiple atmospheric GCM ensembles for seasonal prediction. Monthly Weather Review, 132(12), 2732-2744.
Van Schaeybroeck, B., & Vannitsem, S. (2019). Postprocessing of Long-Range Forecasts. In Statistical Postprocessing of Ensemble Forecasts (pp. 267-290).