An enhanced downscaling methodology for the elaboration of high-resolution climate scenarios for Peru to 2050

Abstract

This study aims to describe a downscaling method for the generation of high-resolution climate scenarios for Peru using data from Global Circulation Models (GCM). The approach is based on the combination of dynamical downscaling methods and statistical techniques that will allow obtaining better precipitation and temperature patterns at a regional and local level. In conclusions considering the spatial heterogeneity of climates due to the complex topography of Peru and other factors, a methodology has been developed to elaborate on high-resolution climate scenarios for 2050. The methodological scheme consisted of data preparation from CMIP5 models, dynamical downscaling, bias correction to the downscaled output, and the application of geostatistical methods. Through this methodology, it was possible to obtain more representative information on precipitation and temperature patterns at a resolution of 5 km. As a result, reliable climate information was obtained that will be useful for climate risk analysis and climate change impacts studies in Peru

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