Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast

Sahelian rainfall presents large interannual variability which is partly controlled by the sea surface temperature anomalies (SSTa) over the eastern Mediterranean, equatorial Pacifc and Atlantic oceans, making seasonal prediction of rainfall changes in Sahel potentially possible. However, it is not...

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Detalhes bibliográficos
Autores: Martín Gómez, Verónica, Mohino Harris, Elsa, Rodríguez De Fonseca, María Belén, Sánchez Gómez, Emilia
Formato: artículo
Fecha de publicación:2022
País:España
Recursos:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/71392
Acesso em linha:https://hdl.handle.net/20.500.14352/71392
Access Level:acceso abierto
Palavra-chave:550.3
Seasonal prediction systems Rainfall variability over Sahel Climate teleconnections
Sistemas de predicción estacional Variabilidad de las precipitciones en el Sahel Teleconexiones climáticas
Física atmosférica
Meteorología (Física)
2501 Ciencias de la Atmósfera
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oai_identifier_str oai:docta.ucm.es:20.500.14352/71392
network_acronym_str ES
network_name_str España
repository_id_str
spelling Understanding rainfall prediction skill over the Sahel in NMME seasonal forecastEntendiendo la destreza de los modelos de predicción estacional del NMME para predecir la precipitación en el SahelMartín Gómez, VerónicaMohino Harris, ElsaRodríguez De Fonseca, María BelénSánchez Gómez, Emilia550.3Seasonal prediction systems Rainfall variability over Sahel Climate teleconnectionsSistemas de predicción estacional Variabilidad de las precipitciones en el Sahel Teleconexiones climáticasFísica atmosféricaMeteorología (Física)2501 Ciencias de la AtmósferaSahelian rainfall presents large interannual variability which is partly controlled by the sea surface temperature anomalies (SSTa) over the eastern Mediterranean, equatorial Pacifc and Atlantic oceans, making seasonal prediction of rainfall changes in Sahel potentially possible. However, it is not clear whether seasonal forecast models present skill to predict the Sahelian rainfall anomalies. Here, we consider the set of models from the North American Multi-model ensemble (NMME) and analyze their skill in predicting the Sahelian precipitation and address the sources of this skill. Results show that though the skill in predicting the Sahelian rainfall is generally low, it can be mostly explained by a combination of how well models predict the SSTa in the Mediterranean and in the equatorial Pacifc regions, and how well they simulate the teleconnections of these SSTa with Sahelian rainfall. Our results suggest that Sahelian rainfall skill is improved for those models in which the Pacifc SST—Sahel rainfall teleconnection is correctly simulated. On the other hand, models present a good ability to reproduce the sign of the Mediterranean SSTa—Sahel teleconnection, albeit with underestimated amplitude due to an underestimation of the variance of the SSTa over this oceanic region. However, they fail to correctly predict the SSTa over this basin, which is the main reason for the poor Sahel rainfall skill in models. Therefore, results suggest models need to improve their ability to reproduce the variability of the SSTa over the Mediterranean as well as the teleconnections of Sahelian rainfall with Pacifc and Mediterranean SSTa.SpringerUniversidad Complutense de Madrid20222022-04-0520222022-04-05journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/71392reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Atribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/713922026-06-02T12:44:21Z
dc.title.none.fl_str_mv Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
Entendiendo la destreza de los modelos de predicción estacional del NMME para predecir la precipitación en el Sahel
title Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
spellingShingle Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
Martín Gómez, Verónica
550.3
Seasonal prediction systems Rainfall variability over Sahel Climate teleconnections
Sistemas de predicción estacional Variabilidad de las precipitciones en el Sahel Teleconexiones climáticas
Física atmosférica
Meteorología (Física)
2501 Ciencias de la Atmósfera
title_short Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
title_full Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
title_fullStr Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
title_full_unstemmed Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
title_sort Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast
dc.creator.none.fl_str_mv Martín Gómez, Verónica
Mohino Harris, Elsa
Rodríguez De Fonseca, María Belén
Sánchez Gómez, Emilia
author Martín Gómez, Verónica
author_facet Martín Gómez, Verónica
Mohino Harris, Elsa
Rodríguez De Fonseca, María Belén
Sánchez Gómez, Emilia
author_role author
author2 Mohino Harris, Elsa
Rodríguez De Fonseca, María Belén
Sánchez Gómez, Emilia
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 550.3
Seasonal prediction systems Rainfall variability over Sahel Climate teleconnections
Sistemas de predicción estacional Variabilidad de las precipitciones en el Sahel Teleconexiones climáticas
Física atmosférica
Meteorología (Física)
2501 Ciencias de la Atmósfera
topic 550.3
Seasonal prediction systems Rainfall variability over Sahel Climate teleconnections
Sistemas de predicción estacional Variabilidad de las precipitciones en el Sahel Teleconexiones climáticas
Física atmosférica
Meteorología (Física)
2501 Ciencias de la Atmósfera
description Sahelian rainfall presents large interannual variability which is partly controlled by the sea surface temperature anomalies (SSTa) over the eastern Mediterranean, equatorial Pacifc and Atlantic oceans, making seasonal prediction of rainfall changes in Sahel potentially possible. However, it is not clear whether seasonal forecast models present skill to predict the Sahelian rainfall anomalies. Here, we consider the set of models from the North American Multi-model ensemble (NMME) and analyze their skill in predicting the Sahelian precipitation and address the sources of this skill. Results show that though the skill in predicting the Sahelian rainfall is generally low, it can be mostly explained by a combination of how well models predict the SSTa in the Mediterranean and in the equatorial Pacifc regions, and how well they simulate the teleconnections of these SSTa with Sahelian rainfall. Our results suggest that Sahelian rainfall skill is improved for those models in which the Pacifc SST—Sahel rainfall teleconnection is correctly simulated. On the other hand, models present a good ability to reproduce the sign of the Mediterranean SSTa—Sahel teleconnection, albeit with underestimated amplitude due to an underestimation of the variance of the SSTa over this oceanic region. However, they fail to correctly predict the SSTa over this basin, which is the main reason for the poor Sahel rainfall skill in models. Therefore, results suggest models need to improve their ability to reproduce the variability of the SSTa over the Mediterranean as well as the teleconnections of Sahelian rainfall with Pacifc and Mediterranean SSTa.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-04-05
2022
2022-04-05
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/71392
url https://hdl.handle.net/20.500.14352/71392
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Atribución 3.0 España
https://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300724

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