@Article{OsmanCoelVera:2021:CaCoSe,
author = "Osman, Marisol and Coelho, Caio Augusto dos Santos and Vera,
Carolina S.",
affiliation = "{Universidad de Buenos Aires} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Universidad de Buenos Aires}",
title = "Calibration and combination of seasonal precipitation forecasts
over South America using Ensemble Regression",
journal = "Climate Dynamics",
year = "2021",
volume = "57",
number = "9/10",
pages = "2889--2904",
month = "Nov.",
keywords = "Climate prediction, NMME, Multi-model ensemble.",
abstract = "Models participating in the North American Multi Model Ensemble
project were calibrated and combined to produce reliable
precipitation probabilistic forecast over South America. Ensemble
Regression method (EREG) was chosen as it is computationally
affordable and uses all the information from the ensemble. Two
different approaches based on EREG were applied to combine
forecasts while different ways to weight the relative contribution
of each model to the ensemble were used. All the consolidated
forecast obtained were confronted against the simple multi-model
ensemble. This work assessed the performance of the predictions
initialized in November to forecast the austral summer
(December-January-February) for the period 1982-2010 using
different probabilistic measures. Results show that the
consolidated forecasts produce more skillful forecast than the
simple multi-model ensemble, although no major differences were
found between the combination and weighting approaches considered.
The regions that presented better results are well-known to be
impacted by El Nino Southern Oscillation.",
doi = "10.1007/s00382-021-05845-2",
url = "http://dx.doi.org/10.1007/s00382-021-05845-2",
issn = "0930-7575",
language = "en",
targetfile = "osman_calibration.pdf",
urlaccessdate = "15 jun. 2024"
}