Seasonal Forecasting of Global Hydrologic Extremes: System Development and Evaluation over GEWEX Basins

Xing Yuan Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, and RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Joshua K. Roundy Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey

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Eric F. Wood Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey

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Justin Sheffield Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey

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Abstract

Seasonal hydrologic extremes in the form of droughts and wet spells have devastating impacts on human and natural systems. Improving understanding and predictive capability of hydrologic extremes, and facilitating adaptations through establishing climate service systems at regional to global scales are among the grand challenges proposed by the World Climate Research Programme (WCRP) and are the core themes of the Regional Hydroclimate Projects (RHP) under the Global Energy and Water Cycle Experiment (GEWEX). An experimental global seasonal hydrologic forecasting system has been developed that is based on coupled climate forecast models participating in the North American Multimodel Ensemble (NMME) project and an advanced land surface hydrologic model. The system is evaluated over major GEWEX RHP river basins by comparing with ensemble streamflow prediction (ESP). The multimodel seasonal forecast system provides higher detectability for soil moisture droughts, more reliable low and high f low ensemble forecasts, and better “real time” prediction for the 2012 North American extreme drought. The association of the onset of extreme hydrologic events with oceanic and land precursors is also investigated based on the joint distribution of forecasts and observations. Climate models have a higher probability of missing the onset of hydrologic extremes when there is no oceanic precursor. But oceanic precursor alone is insufficient to guarantee a correct forecast—a land precursor is also critical in avoiding a false alarm for forecasting extremes. This study is targeted at providing the scientific underpinning for the predictability of hydrologic extremes over GEWEX RHP basins and serves as a prototype for seasonal hydrologic forecasts within the Global Framework for Climate Services (GFCS).

CORRESPONDING AUTHOR: Xing Yuan, RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Huayanli No. 40, Qijiahuozi, Chaoyang District, Beijing 100029, China, E-mail: yuanxing@tea.ac.cn

A supplement to this article is available online (DOI:10.1175/BAMS-D-14-00003.2)

Abstract

Seasonal hydrologic extremes in the form of droughts and wet spells have devastating impacts on human and natural systems. Improving understanding and predictive capability of hydrologic extremes, and facilitating adaptations through establishing climate service systems at regional to global scales are among the grand challenges proposed by the World Climate Research Programme (WCRP) and are the core themes of the Regional Hydroclimate Projects (RHP) under the Global Energy and Water Cycle Experiment (GEWEX). An experimental global seasonal hydrologic forecasting system has been developed that is based on coupled climate forecast models participating in the North American Multimodel Ensemble (NMME) project and an advanced land surface hydrologic model. The system is evaluated over major GEWEX RHP river basins by comparing with ensemble streamflow prediction (ESP). The multimodel seasonal forecast system provides higher detectability for soil moisture droughts, more reliable low and high f low ensemble forecasts, and better “real time” prediction for the 2012 North American extreme drought. The association of the onset of extreme hydrologic events with oceanic and land precursors is also investigated based on the joint distribution of forecasts and observations. Climate models have a higher probability of missing the onset of hydrologic extremes when there is no oceanic precursor. But oceanic precursor alone is insufficient to guarantee a correct forecast—a land precursor is also critical in avoiding a false alarm for forecasting extremes. This study is targeted at providing the scientific underpinning for the predictability of hydrologic extremes over GEWEX RHP basins and serves as a prototype for seasonal hydrologic forecasts within the Global Framework for Climate Services (GFCS).

CORRESPONDING AUTHOR: Xing Yuan, RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Huayanli No. 40, Qijiahuozi, Chaoyang District, Beijing 100029, China, E-mail: yuanxing@tea.ac.cn

A supplement to this article is available online (DOI:10.1175/BAMS-D-14-00003.2)

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  • Ye, A., Q. Duan, X. Yuan, E. F. Wood, and J. Schaake, 2014: Hydrologic post-processing of MOPEX streamflow simulations. J. Hydrol., 508, 147156, doi:10.1016/j.jhydrol.2013.10.055.

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  • Yoon, J. H., K. Mo, and E. F. Wood, 2012: Dynamic-model-based seasonal prediction of meteorological drought over the contiguous United States. J. Hydrometeor., 13, 463481, doi:10.1175/JHM-D-11-038.1.

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  • Yossef, N. C., H. Winsemius, A. Weerts, R. van Beek, and M. F. P. Bierkens, 2013: Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing. Water Resour. Res., 49, 46874699, doi:10.1002/wrcr.20350.

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  • Yuan, X., and E. F. Wood, 2012a: Downscaling precipitation or bias-correcting streamflow? Some implications for coupled general circulation model (CGCM)-based ensemble seasonal hydrologic forecast. Water Resour. Res., 48, W12519, doi:10.1029/2012WR012256.

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  • Yuan, X., and E. F. Wood, 2012b: On the clustering of climate models in ensemble seasonal forecasting. Geophys. Res. Lett., 39, L18701, doi:10.1029/2012GL052735.

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  • Yuan, X., and E. F. Wood, 2013: Multimodel seasonal forecasting of global drought onset. Geophys. Res. Lett., 40, 49004905, doi:10.1002/grl.50949.

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  • Yuan, X., E. F. Wood, L. Luo, and M. Pan, 2011: A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction. Geophys. Res. Lett., 38, L13402, doi:10.1029/2011GL047792.

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  • Yuan, X., E. F. Wood, N. W. Chaney, J. Sheffield, J. Kam, M. Liang, and K. Guan, 2013a: Probabilistic seasonal forecasting of African drought by dynamical models. J. Hydrometeor., 14, 17061720, doi:10.1175/JHM-D-13-054.1.

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  • Yuan, X., E. F. Wood, J. K. Roundy, and M. Pan, 2013b: CFSv2-based seasonal hydroclimatic forecasts over conterminous United States. J. Climate, 26, 48284847, doi:10.1175/JCLI-D-12-00683.1.

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  • Zhao, M., and H. H. Hendon, 2009: Representation and prediction of the Indian Ocean dipole in the POAMA seasonal forecast model. Quart. J. Roy. Meteor. Soc., 135, 337352, doi:10.1002/qj.370.

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