The potential added value of Regional Climate Models in South America using a multiresolution approach

This paper aims to identify those regions within the South American continent where the Regional Climate Models (RCMs) have the potential to add value (PAV) compared to their coarser-resolution global forcing. For this, we used a spatial-scale filtering method based on the wavelet theory to distingu...

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Veröffentlicht in:Climate dynamics 2020-02, Vol.54 (3-4), p.1553-1569
Hauptverfasser: Falco, Magdalena, Carril, Andrea F., Li, Laurent Z. X., Cabrelli, Carlos, Menéndez, Claudio G.
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container_issue 3-4
container_start_page 1553
container_title Climate dynamics
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creator Falco, Magdalena
Carril, Andrea F.
Li, Laurent Z. X.
Cabrelli, Carlos
Menéndez, Claudio G.
description This paper aims to identify those regions within the South American continent where the Regional Climate Models (RCMs) have the potential to add value (PAV) compared to their coarser-resolution global forcing. For this, we used a spatial-scale filtering method based on the wavelet theory to distinguish the regional climatic signal present in atmospheric surface fields from observed data (CPC and TRMM) and 6 RCM simulations belonging to the CORDEX Project. The wavelet used for filtering was Haar wavelet, but a comparative analysis with Daubechies 4 wavelet indicated that meteorological fields or regional indices were not very sensitive to the wavelet selected. Once the longer wavelengths were filtered, we focused on analyzing the spatial variability of extreme rainfall and the spatiotemporal variability of maximum and minimum surface air temperature on a daily basis. The results obtained suggest essential differences in the spatial distribution of the small-scale signal of extreme precipitation between TRMM and regional models, together with a large dispersion between models. While TRMM and CPC register a large signal throughout the continent, the RCMs place it over the Andes Cordillera and some over tropical South America. PAV signal for surface air temperature was found over the Andes Cordillera and the Brazilian Highlands, which are regions characterized by complex topography, and also on the coasts of the continent. The signal came specially from the small-scale stationary component. The transient part is much smaller than the stationary one, except over la Plata Basin where they are of the same order of magnitude. Also, the RCMs and CPC showed a large spread between them in representing this transient variability. The results confirm that RCMs have the potential to add value in the representation of extreme precipitation and the mean surface temperature in South America. However, this condition is not applicable throughout the whole continent but is particularly relevant in those terrestrial regions where the surface forcing is strong, such as the Andes Cordillera or the coasts of the continent.
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X.</au><au>Cabrelli, Carlos</au><au>Menéndez, Claudio G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The potential added value of Regional Climate Models in South America using a multiresolution approach</atitle><jtitle>Climate dynamics</jtitle><stitle>Clim Dyn</stitle><date>2020-02-01</date><risdate>2020</risdate><volume>54</volume><issue>3-4</issue><spage>1553</spage><epage>1569</epage><pages>1553-1569</pages><issn>0930-7575</issn><eissn>1432-0894</eissn><abstract>This paper aims to identify those regions within the South American continent where the Regional Climate Models (RCMs) have the potential to add value (PAV) compared to their coarser-resolution global forcing. For this, we used a spatial-scale filtering method based on the wavelet theory to distinguish the regional climatic signal present in atmospheric surface fields from observed data (CPC and TRMM) and 6 RCM simulations belonging to the CORDEX Project. The wavelet used for filtering was Haar wavelet, but a comparative analysis with Daubechies 4 wavelet indicated that meteorological fields or regional indices were not very sensitive to the wavelet selected. Once the longer wavelengths were filtered, we focused on analyzing the spatial variability of extreme rainfall and the spatiotemporal variability of maximum and minimum surface air temperature on a daily basis. The results obtained suggest essential differences in the spatial distribution of the small-scale signal of extreme precipitation between TRMM and regional models, together with a large dispersion between models. While TRMM and CPC register a large signal throughout the continent, the RCMs place it over the Andes Cordillera and some over tropical South America. PAV signal for surface air temperature was found over the Andes Cordillera and the Brazilian Highlands, which are regions characterized by complex topography, and also on the coasts of the continent. 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subjects Air temperature
Analysis
Atmospheric models
Atmospheric precipitations
Climate
Climate models
Climatology
Coasts
Comparative analysis
Computer simulation
Earth and Environmental Science
Earth Sciences
Extreme weather
Fields
Filtration
Geophysics/Geodesy
Oceanography
Precipitation
Precipitation variability
Rain
Rain and rainfall
Rainfall
Regional climate models
Regional climates
Regions
Sciences of the Universe
Spatial distribution
Spatial variability
Spatial variations
Surface temperature
Surface-air temperature relationships
TRMM satellite
Tropical climate
Tropical Rainfall Measuring Mission (TRMM)
Wavelengths
Wavelet analysis
title The potential added value of Regional Climate Models in South America using a multiresolution approach
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