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Simulation of seasonal US precipitation and temperature by the nested CWRF-ECHAM system

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Abstract

This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980–2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavy precipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with observations are significant. These results indicate that CWRF can greatly improve mesoscale regional climate structures but it cannot change interannual variations of the large-scale patterns, which are determined by the driving lateral boundary conditions.

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Acknowledgments

We thank Liqiang Sun for helping to provide the ECHAM simulation output and related post-processing code and documents, Tiejun Ling for helping to develop job scripts, Fengxue Qiao for compiling observed precipitation and surface air temperature data, and Min Xu for constructive discussions. We acknowledge the DOE/NERSC and NOAA/ZEUS supercomputing facilities. This research is supported by the NOAA Climate Prediction Program for the Americas (CPPA) Grants NA08OAR4310575 and NA08OAR4310875. The views expressed are those of the authors and do not necessarily reflect those of the sponsoring agency.

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  1. David DeWitt

    Present address: NOAA National Weather Service, Silver Spring, MD, USA

Authors and Affiliations

  1. Earth System Science Interdisciplinary Center, University of Maryland, 5825 University Research Court, Suite 4001, College Park, MD, 20740, USA

    Ligang Chen & Xin-Zhong Liang

  2. Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, 20740, USA

    Xin-Zhong Liang

  3. International Research Institute for Climate Prediction, Columbia University, Palisades, NY, 10964, USA

    David DeWitt

  4. Department of Geography, Bowling Green State University, Bowling Green, OH, 43403, USA

    Arthur N. Samel

  5. NOAA Air Resources Laboratory, College Park, MD, 20740, USA

    Julian X. L. Wang

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  1. Ligang Chen
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Correspondence to Ligang Chen.

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Chen, L., Liang, XZ., DeWitt, D. et al. Simulation of seasonal US precipitation and temperature by the nested CWRF-ECHAM system. Clim Dyn 46, 879–896 (2016). https://doi.org/10.1007/s00382-015-2619-9

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  • DOI: https://doi.org/10.1007/s00382-015-2619-9

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