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Predictable patterns and predictive skills of monsoon precipitation in Northern Hemisphere summer in NCEP CFSv2 reforecasts
Authors:Zhiyan Zuo  Song Yang  Zeng-Zhen Hu  Renhe Zhang  Wanqiu Wang  Bohua Huang  Fang Wang
Institution:1. Chinese Academy of Meteorological Sciences, Beijing, 100081, China
2. Department of Atmospheric Sciences, Sun Yat-sen University, 123 West Xingang Road, Guangzhou, 510275, Guangdong, China
3. NOAA’s Climate Prediction Center, College Park, MD, 20740, USA
4. Department of Atmospheric, Oceanic, and Earth Sciences, George Mason University, Fairfax, VA, 22030, USA
5. Center for Ocean–Land–Atmosphere Studies, Calverton, MD, 20705, USA
6. National Climate Center, CMA, Beijing, 100081, China
Abstract:The predictable patterns and predictive skills of monsoon precipitation in the Northern Hemisphere summer (June–July–August) are examined using reforecasts (1983–2010) from the National Center for Environmental Prediction Climate Forecast System version 2 (CFSv2). The possible connections of these predictable patterns with global sea surface temperature (SST) are investigated. The empirical orthogonal function analysis with maximized signal-to-noise ratio is used to isolate the predictable patterns of the precipitation for three regional monsoons: the Asian and Indo-Pacific monsoon (AIPM), the Africa monsoon (AFM), and the North America monsoon (NAM). Overall, the CFSv2 well predicts the monsoon precipitation patterns associated with El Niño-South Oscillation (ENSO) due to its good prediction skill for ENSO. For AIPM, two identified predictable patterns are an equatorial dipole pattern characterized by opposite variations between the equatorial western Pacific and eastern Indian Ocean, and a tropical western Pacific pattern characterized by opposite variations over the tropical northwestern Pacific and the Philippines and over the regions to its west, north, and southeast. For NAM, the predictable patterns are a tropical eastern Pacific pattern with opposite variations in the tropical eastern Pacific and in Mexico, the Guyana Plateau and the equatorial Atlantic, and a Central American pattern with opposite variations in the eastern Pacific and the North Atlantic and in the Amazon Plains. The CFSv2 can predict these patterns at least 5 months in advance. However, compared with the good skill in predicting AIPM and NAM precipitation patterns, the CFSv2 exhibits little predictive skill for AFM precipitation, probably because the variability of the tropical Atlantic SST plays a more important than ENSO in the AFM precipitation variation and the prediction skill is lower for the tropical Atlantic SST than the tropical Pacific SST.
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