Journal
CLIMATE DYNAMICS
Volume 40, Issue 11-12, Pages 3071-3088Publisher
SPRINGER
DOI: 10.1007/s00382-013-1772-2
Keywords
Northern Hemisphere monsoons; Most predictable patterns; NCEP Climate Forecast System
Categories
Funding
- National Natural Science Foundation of China [41205059, 41221064]
- Special Fund for Public Welfare Industry (Meteorology) [GYHY201206017]
- International S&T Cooperation Project of the Ministry of Science and Technology of China [2009DFA21430]
- Basic Research Fund of Chinese Academy of Meteorological Sciences [2012Z001]
- Sun Yat-sen University 985 Project Phase 3
- NOAA-CMA Bilateral Program
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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 Nio-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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