Evaluation of WRF capability to detect dry and wet periods in Spain using drought indices

Abstract

AbstractThe Weather Research and Forecasting (WRF) model has been used to show the benefits provided by downscaled fields to detect and analyze wet and dry periods over a region with high precipitation variability such as Spain. We have analyzed the spatiotemporal behavior of two widely used drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), computed at 3 and 12 month time scales, which provide important information in an agricultural and water‐resource context. These two indices were computed from WRF outputs and compared with those calculated from observational (monthly precipitation and temperature databases of Spain, MOPREDAS and MOTEDAS) and from the European Centre for Medium‐Range Weather Forecasts Interim Re‐Analysis (ERA‐Interim) data sets. This evaluation was made by using a regional scale and a multistep regionalization method and by comparison of individual grid points. In general, results indicate that the drought indices obtained by using WRF outputs provide a noticeable improvement regarding those computed by using ERA‐Interim, higher at longer time scales. Although results show no significant differences between drought indices analyzed, the improvement offered by WRF is greater for SPI than for SPEI. In terms of averaged duration, magnitude, and severity of drought, the benefits provided by WRF are not so evident, presenting better agreement with the observational data at 12 month time scale, being clearer for the intensity. These findings evidence the benefit of using WRF climate fields to monitor, analyze, and detect drought events, being a valuable source of knowledge for a suitable decision making, especially for water‐resource management.