A metrics-based analysis of seasonal daily precipitation and near-surface temperature within seven Coordinated Regional Climate Downscaling Experiment domains

Abstract

We compare ensemble mean daily precipitation and near-surface temperatures from regional climate model simulations over seven Coordinated Regional Climate Downscaling Experiment domains for the winter and summer seasons. We use Taylor diagrams to show the domain-wide pattern similarity between the model ensemble and the observational data sets. We use the Climatic Research Unit (CRU) and the University of Delaware gridded observations and ERA-Interim reanalysis data as an additional observationally based estimate of historical climatology. Taylor diagrams determine the relative skill of the seven sets of simulations and quantify these results in terms of center pattern root-mean square error and correlation coefficient. Results suggest that there is good agreement between the models and the CRU, in terms of their respective seasonal cycles, as shown in Taylor diagrams and bias plots. There is also good agreement between both gridded observation sets. In addition, downscaled ERA-Interim precipitation is closer to observations than raw ERA-Interim precipitation. Domains located in the low latitudes and those having high topography appear to have larger biases, especially precipitation.