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Predicting US summer precipitation using NCEP Climate Forecast System version 2 initialized by multiple ocean analyses

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Abstract

This study examines the prediction skill of the contiguous United States (CONUS) precipitation in summer, as well as its potential sources using a set of ensemble hindcasts conducted with the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 and initialized from four independent ocean analyses. The multiple ocean ensemble mean (MOCN_ESMEAN) hindcasts start from each April for 26 summers (1982–2007), with each oceanic state paired with four atmosphere-land states. A subset of hindcasts from the NCEP CFS Reanalysis and Reforecast (CFSRR) project for the same period, from the same initial month and with the same total ensemble size, is also analyzed. Compared with CFSRR, MOCN_ESMEAN is distinguished by its oceanic ensemble spread that introduces potentially larger perturbations and better spatial representation of the oceanic uncertainty. The prediction skill of the CONUS precipitation in summer shows a similar spatial pattern in both MOCN_ESMEAN and CFSRR, but the results suggested that initialization from multiple ocean analyses may bring more robust signals and additional skills to the seasonal prediction for both sea surface temperature and precipitation. Among the predictable areas for precipitation, the northwestern CONUS (NWUS) is the most robust. A further analysis shows that the enhanced summer precipitation prediction skill in NWUS is mainly associated with the El Niño/Southern Oscillation, with possible influence also from the Pacific Decadal Oscillation. Through this work, we argue that a large ensemble is necessary for precipitation forecast in mid-latitudes, such as the CONUS, and taking into account of the oceanic initial state uncertainty is an efficient way to build such an ensemble.

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Acknowledgments

Funding for this study is provided by grants from NSF (ATM-0830068), NOAA (NA09OAR4310058), and NASA (NNX09AN50G). The authors would like to thank Dr. J. Shukla for his guidance and support of this project, as well as the constructive comments and suggestions from two reviewers. We thank ECMWF and NCEP for providing their ocean data assimilation analysis datasets, which made this project possible. The authors gratefully acknowledge NCEP for the CFSv2 model made available to COLA. We also acknowledge NCEP’s assistance in porting the code to the computing platforms at the NASA Advanced Supercomputing (NAS) division. We particularly wish to thank Y. Hou, S. Moorthi and S. Saha for technical assistance and necessary data sets and W. Lapenta and L. Uccellini for enabling the collaborative activities. Computing resources provided by NAS are also gratefully acknowledged.

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Authors and Affiliations

  1. Center for Ocean-Land-Atmosphere Studies, Institute of Global Environment and Society, 4041 Powder Mill Road, Suite 302, Calverton, MD, 20705, USA

    Jieshun Zhu, Bohua Huang, James L. Kinter III & Lawrence Marx

  2. Department of Atmospheric, Oceanic, and Earth Sciences, College of Science, George Mason University, Fairfax, VA, USA

    Bohua Huang & James L. Kinter III

  3. Climate Prediction Center, National Centers for Environmental Prediction/NOAA, College Park, MD, USA

    Zeng-Zhen Hu

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  1. Jieshun Zhu
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Correspondence to Jieshun Zhu.

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Zhu, J., Huang, B., Hu, ZZ. et al. Predicting US summer precipitation using NCEP Climate Forecast System version 2 initialized by multiple ocean analyses. Clim Dyn 41, 1941–1954 (2013). https://doi.org/10.1007/s00382-013-1785-x

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  • DOI: https://doi.org/10.1007/s00382-013-1785-x

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