The Weather Research and Forecasting (WRF) model is used for dynamic downscaling of 2.5-degree National Centers for Environmental Prediction-U.S. Department of Energy Reanalysis II (NCEP-R2) data for 1980–2010 at 12 km resolution over most of North America. The model’s performance for surface air temperature and precipitation is evaluated by comparison with high-resolution observational data sets. The model’s ability to add value is investigated by comparison with NCEP-R2 data and a 50 km regional climate simulation. The causes for major model bias are studied through additional sensitivity experiments with various model setup/integration approaches and physics representations. The WRF captures the main features of the spatial patterns and annual cycles of air temperature and precipitation over most of the contiguous United States. However, simulated air temperatures over the south central region and precipitation over the Great Plains and the Southwest have significant biases. Allowing longer spin-up time, reducing the nudging strength, or replacing the WRF Single-Moment six-class microphysics with Morrison microphysics reduces the bias over some subregions. However, replacing the Grell-Devenyi cumulus parameterization with Kain-Fritsch shows no improvement. The 12 km simulation does add value above the NCEP-R2 data and the 50 km simulation over mountainous and coastal zones.

Areas of Focus: Climate Change
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Climate Change
Climate change is an urgent global challenge. EPIC research is helping to assess its impacts, quantify its costs, and identify an efficient set of policies to reduce emissions and adapt...
Climate Science
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Climate Science
EPIC’s interdisciplinary team of researchers is contributing to a cross-cutting body of knowledge on the scientific causes of climate change and its social consequences.