Abstract
<p>Agriculture and livestock represent 21% of the economic sector of the Department of Chocó (Colombia), being drought and flood events one of the main difficulties. Although this Department has the largest records of annual precipitation, in some seasons with scarce precipitation, it shows great drought problems and crop deterioration.</p><p>Consequently, several institutes use short-term decadal climate simulations using general circulation models (GCM), which consider climate warming as well as the predictable climate signal associated with the initial climate conditions to inform water resource managers.</p><p>This work analyzes the potential use of the decadal predictions of precipitation from the Japanese model BCC-CSM2-MR to predict of drought events in the Department of Chocó through the analysis of the hindcasts in the period 1960-2018. The choice of this model is based on its suitability to reproduce the main patterns of climate variability that affect the study area. Drought events will be characterized by the Standardized Index of Precipitation (SPI) on different time scales.</p><p>Since the resolution of this GCM is very vast and does not allow to solve regionalized characteristics, such as topographic factors, land-sea distribution, or vegetation types, etc., a statistical downscaling of the decadal hindcasts for precipitation will be carried out from which the SPI will be calculated. These results will be compared with those obtained from the observational database "<em>Global Precipitation Climatology Centre</em> (GPCC)”.</p><p>Keywords: drought, Colombia, SPI, decadal predictions, GCM, statistical downscaling.</p><p>Acknowledgments: Y.M. Toro-Ortiz acknowledges the Colombian Ministry of Science, Technology, and Innovation for the predoctoral fellowship (grant code: 860). This research was funded by the Spanish Ministry of Economy and Competitiveness project CGL2017-89836-390R, with additional support from FEDER Funds, by FEDER/Junta de Andalucía-Consejería de Economía y Conocimiento, project B-RNM-336-UGR18, and by FEDER/Junta de Andalucía-Consejería de Transformación Económica, Industria, Conocimiento y Universidades (project P20_00035).</p>
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