How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods

Different techniques for obtaining probabilistic quantitative precipitation forecasts (PQPFs) over South America are tested during the 2002-2003 warm season. They have been applied to a regional ensemble system which uses the breeding technique to generate initial and boundary conditions perturbatio...

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Autores principales: Ruiz, J.J., Saulo, C.
Formato: JOUR
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_13504827_v19_n3_p302_Ruiz
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spelling todo:paper_13504827_v19_n3_p302_Ruiz2023-10-03T16:09:59Z How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods Ruiz, J.J. Saulo, C. Ensemble forecasting Ensemble generation Probabilistic quantitative precipitation forecasts Different techniques for obtaining probabilistic quantitative precipitation forecasts (PQPFs) over South America are tested during the 2002-2003 warm season. They have been applied to a regional ensemble system which uses the breeding technique to generate initial and boundary conditions perturbations. This comparison involves seven algorithms and also includes experiments to select an adequate size for the training period. Results show that the sensitivity to different calibration strategies is small with the exception of the rank histogram algorithm. The inclusion of the ensemble spread or the use of different ensemble members for the computation of probabilities shows almost no improvement with respect to probabilistic forecasts computed using the ensemble mean. This is basically due to the strong relationship between precipitation error and its amount. © 2011 Royal Meteorological Society. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_13504827_v19_n3_p302_Ruiz
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Ensemble forecasting
Ensemble generation
Probabilistic quantitative precipitation forecasts
spellingShingle Ensemble forecasting
Ensemble generation
Probabilistic quantitative precipitation forecasts
Ruiz, J.J.
Saulo, C.
How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods
topic_facet Ensemble forecasting
Ensemble generation
Probabilistic quantitative precipitation forecasts
description Different techniques for obtaining probabilistic quantitative precipitation forecasts (PQPFs) over South America are tested during the 2002-2003 warm season. They have been applied to a regional ensemble system which uses the breeding technique to generate initial and boundary conditions perturbations. This comparison involves seven algorithms and also includes experiments to select an adequate size for the training period. Results show that the sensitivity to different calibration strategies is small with the exception of the rank histogram algorithm. The inclusion of the ensemble spread or the use of different ensemble members for the computation of probabilities shows almost no improvement with respect to probabilistic forecasts computed using the ensemble mean. This is basically due to the strong relationship between precipitation error and its amount. © 2011 Royal Meteorological Society.
format JOUR
author Ruiz, J.J.
Saulo, C.
author_facet Ruiz, J.J.
Saulo, C.
author_sort Ruiz, J.J.
title How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods
title_short How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods
title_full How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods
title_fullStr How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods
title_full_unstemmed How sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? Part I: Sensitivity to calibration methods
title_sort how sensitive are probabilistic precipitation forecasts to the choice of calibration algorithms and the ensemble generation method? part i: sensitivity to calibration methods
url http://hdl.handle.net/20.500.12110/paper_13504827_v19_n3_p302_Ruiz
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AT sauloc howsensitiveareprobabilisticprecipitationforecaststothechoiceofcalibrationalgorithmsandtheensemblegenerationmethodpartisensitivitytocalibrationmethods
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