Evaluación de métodos de regionalización estadística para la generación de proyecciones climáticas en España

Abstract

The study presents an evaluation and selection of global climate models for downscaled projections, aligning with the requirements of Spain's second National Adaptation Plan to Climate Change. It highlights the use of regionally downscaled climate projections with higher spatial resolution, provided by the spanish meteorological service (AEMET). Specifically, it focuses on the application of empirical-statistical methods to downscale daily data of maximum temperature, minimum temperature, and accumulated precipitation. The results indicate the selection of eleven global climate models for downscaling and the choice of specific methods for each climatic variable: regression-analogues for temperatures and eXtreme Gradient Boost for precipitation. Additionally, bias correction using Quantile Delta Mapping is recommended to improve projections. This research lays a robust groundwork for future studies on climate change in Spain.