Influence of climate change on precipitation extremes in Ecuador

Understanding the spatiotemporal variability of extreme precipitation is crucial for risk management. The effects of climate change can increase the frequency and severity of these extremes, generating more environmental hazards. Although there is research about climate extremes in specific areas of Ecuador, knowledge of extreme precipitation on an entire national scale still needs to be available. This study contributes to this gap by comprehensively evaluating continental Ecuador’s precipitation extremes. Climate precipitation indices of the Group of Experts on Detection and Climate Change Indices (ETCCDI) are assessed with observed data and future data derived from projections of regional climate models of Ecuador in two Representative Concentration Pathways (RCP), 4.5 and 8.5. Ground meteorological data and the MSWEP satellite product are merged by applying a Random Forest-based methodology (RF-MEP) to generate an observations data grid (1981-2015) containing the spatiotemporal distribution of precipitation throughout Ecuador. On the other hand, the future projections (2016-2070) are bias-corrected through statistical downscaling using Quantile Delta Mapping (QMD). Consequently, eleven extreme precipitation indices are evaluated, and trends with the Mann-Kendall test are analyzed. The results show an increase in total rainfall and intensities, especially in the north and center of the Coast and the Amazon, with a maximum of approximately 32 mm/year in the RCP 8.5 scenario. This scenario presents significantly increasing precipitation trends in all regions on highly wet days. Some notable indices are the days of heavy rain greater than 10 and 20 mm, which would increase in the future scenarios to 148 and 76 days/year, respectively, especially in some areas of the center and north of the Amazon and the north of the Coast. The present research fills knowledge gaps of extreme precipitation trends in Ecuador that could assist decision-makers in applying measures for climatic threat reduction.