CIMA   09099
CENTRO DE INVESTIGACIONES DEL MAR Y LA ATMOSFERA
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Initial results of the CORDEX FPS on extreme precipitation events in Southeastern South America: dynamical downscaling at convection-permitting resolution
Autor/es:
MARTA LLOPART; SIN CHAN CHOU; MARTIN FEIJOO; SILVINA A SOLMAN; JESUS FERNANDEX; ERIKA COPPOLA; JOSE MANUEL GUTIERREZ; ROSMERI PORFIRIO DA ROCHA; MARIA LAURA BETTOLLI ; MOIRA DOYLE; ALVARO LAVIN-GULLON
Lugar:
BEIJING
Reunión:
Conferencia; ICRC CORDEX - 2019; 2019
Resumen:
The CORDEX Flagship Pilot Study (FPS) on extreme precipitation events in Southeastern South America (SESA) aims at studying multi-scale processes and interactions leading to extreme precipitation events.It will foster cooperation with the impacts and user community to obtain actionable climateinformation from different sources, including both statistical and dynamical downscaling. Regarding the latter, we designed an experimental setup exploring the uncertainties arising from the use of (1) different regional climate models and configurations (ETA, RegCM4, WRF3.8, WRF3.9), (2) different resolutions, with an intermediate resolution nest (20km) to reach convection-permitting resolution (4km) over the target area, (3) different heavy precipitation events and (4) different simulation setups, comparing a ?Weather-like? mode, benefiting from predictability arising from initial conditions as in NWP, and a ?climate mode?, where predictability arises only from the lateral boundary conditions.These driving boundary conditions are taken in all cases from the ERA-Interim reanalysis, in order to compare with observations and leave out global climate modelling uncertainty.In this work, we present some initial results focusing only on precipitation and exploring the above mentioned uncertainty sources. In particular, we focus on the ability of the models to represent the diurnal cycle of precipitation, total precipitation amount and spatial distribution as compared to the driving reanalysis and several station and gridded observational datasets over the region.