Performance of the coupling RegCM4.3 and CLM3.5: An analysis over southeastern Brazil

This work analyzed the 3.5 land surface scheme coupled in the Regional Climate Model RegCM4 (RegCLM), seeking to identify the impact of this coupling in the climatology and in the interannual variability, mainly in the Southeast of Brazil. The climatology analysis showed that the RegCLM, for DJF, is...

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Detalles Bibliográficos
Autores: Llopart, Marta Pereira [UNESP], Reboita, Michelle Simões [UNESP], Rocha, Rosmeri Porfírio da [UNESP], Machado, Jeferson Prietsch [UNESP]
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2018
País:Brasil
Institución:Universidade Estadual Paulista (UNESP)
Repositorio:Repositório Institucional da UNESP
Idioma:portugués
OAI Identifier:oai:repositorio.unesp.br:11449/228673
Acceso en línea:http://dx.doi.org/10.11137/2018_3_113_124
http://hdl.handle.net/11449/228673
Access Level:acceso abierto
Palabra clave:CLM3.5
CORDEX
Interannual variability
RegCM4
SDE
Descripción
Sumario:This work analyzed the 3.5 land surface scheme coupled in the Regional Climate Model RegCM4 (RegCLM), seeking to identify the impact of this coupling in the climatology and in the interannual variability, mainly in the Southeast of Brazil. The climatology analysis showed that the RegCLM, for DJF, is more humid than the set of observations used, overestimating the South Atlantic Convergence Zone (SACZ) due to the RegCLM simulate more intense the northeast trade winds, and with this, there is a transportation of moisture from the Tropical Atlantic Ocean to the continent trhought the Low Level Jet (LLJ), intensifying the SACZ. For air temperature, RegCLM is colder than observations in the SDE region. This result also occurs in the analysis of the annual cycle and, especially in winter, reaching the difference of 1.8oC. During summer, lowest simulation errors were found for this variable. For the interannual variability for the SDE, the simulated precipitation presents an intensify pattern of the signal and reverse the phase of the observed anomaly. For air temperature, the simulation agrees with the observations, intensifying in some years the anomalies.