Dynamic regionalization over Peru: HadGEM2-ES / WRF

Descripción del Articulo

The present work has as objective the elaboration of a new gridded data base to 16 km, for the analysis of the changes of the future climate on Peru, mainly in the variables of precipitation, maximum and minimum temperature. The methodology used is the dynamic regionalization technique, using the re...

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Detalles Bibliográficos
Autores: Llacza Rodríguez, Alan, Jácome Vergaray, Gerardo
Formato: informe técnico
Fecha de Publicación:2008
Institución:Servicio Nacional de Meteorología e Hidrología del Perú
Repositorio:SENAMHI-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.senamhi.gob.pe:20.500.12542/1554
Enlace del recurso:https://hdl.handle.net/20.500.12542/1554
Nivel de acceso:acceso abierto
Materia:Dynamic regionalization
Cambio Climático
https://purl.org/pe-repo/ocde/ford#1.05.09
variabilidad climatica - Clima y Eventos Naturales
Descripción
Sumario:The present work has as objective the elaboration of a new gridded data base to 16 km, for the analysis of the changes of the future climate on Peru, mainly in the variables of precipitation, maximum and minimum temperature. The methodology used is the dynamic regionalization technique, using the regional climate model Weather Research and Forecasting (WRF), using the initial conditions of the HadGEM2-ES global model, for the period of 1981-2065, with the RCP 8.5 emission scenario. The analysis of the results for the observed period indicates a better representation of the precipitation in the central and southern part of the Peruvian Andes and overestimation mainly in the summer period (December, January and February). With regard to temperatures, there is a better representation of the minimum temperature compared to the maximum. While the results of the changes to 2030 indicate non-uniform values over Peru, with an increase in precipitation over the coast and jungle, and decreases over part of the Andes and southern coast of Peru. Regarding the temperatures, there are increases over the whole country, mainly over the Andes.
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