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Potential Predictability of the Monsoon Subclimate SystemsWhile El Nino/Southern Oscillation (ENSO) phenomenon can be predicted with some success using coupled oceanic-atmospheric models, the skill of predicting the tropical monsoons is low regardless of the methods applied. The low skill of monsoon prediction may be either because the monsoons are not defined appropriately or because they are not influenced significantly by boundary forcing. The latter characterizes the importance of internal dynamics in monsoon variability and leads to many eminent chaotic features of the monsoons. In this study, we analyze results from nine AMIP-type ensemble experiments with the NASA/GEOS-2 general circulation model to assess the potential predictability of the tropical climate system. We will focus on the variability and predictability of tropical monsoon rainfall on seasonal-to-interannual time scales. It is known that the tropical climate is more predictable than its extratropical counterpart. However, predictability is different from one climate subsystem to another within the tropics. It is important to understand the differences among these subsystems in order to increase our skill of seasonal-to-interannual prediction. We assess potential predictability by comparing the magnitude of internal and forced variances as defined by Harzallah and Sadourny (1995). The internal variance measures the spread among the various ensemble members. The forced part of rainfall variance is determined by the magnitude of the ensemble mean rainfall anomaly and by the degree of consistency of the results from the various experiments.
Document ID
19990009996
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Yang, Song
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Lau, K.-M.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Chang, Y.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Schubert, S.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Date Acquired
September 6, 2013
Publication Date
January 15, 1999
Subject Category
Meteorology And Climatology
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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