Comment on “The added value to global model projections of climate change by dynamical downscaling: A case study over the continental U.S. using the GISS‐ModelE2 and WRF models” by Racherla et al.

Abstract

Racherla et al. [2012, hereinafter RSF12] analyzed two decades, 1968–1978 and 1995–2005, comparing time slices of global and regional climate models simulations with analyses of observations and in particular verifying the skill of models at capturing the changes in seasonal mean surface air temperature and precipitation between the two decades over 11 regions of the U.S. The global simulation is from the Goddard Institute for Space Studies (GISS)-ModelE2 coupled atmosphere-ocean global climate model (AOGCM), integrated on a 2° by 2.5° grid and incorporating anthropogenic and natural forcings with a detailed representation of gas phase, sulfate, black carbon, nitrate, and secondary organic aerosol chemistry. Dynamical downscaling was achieved with a version of the Weather Research and Forecasting (WRF) atmospheric regional climate model (RCM), integrated over a North American domain on a 45 km mesh with 216 by 126 cells in the west-east and south-north directions, respectively. WRF was driven by atmospheric fields and sea surface temperature (SST) and sea ice concentrations (SIC) from the GISSModelE2 simulation. The WRF model did not include anthropogenic aerosol forcings nor land use changes. RSF12 found very modest skill at reproducing the observed trend of temperature and precipitation over the past 37 years for their single AOGCM simulation, and very little improvement if any from dynamical downscaling with the higher-resolution RCM.