Predictability of Monthly and Seasonal Average Circulation of the Atmosphere

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One of the very exciting frontiers of research in atmospheric sciences is understanding and extending the limits of dynamic predictibility on monthly and seasonal time scales. The potential societal impact of successful extended range forecasting is enormous. The main objective of this proposal is to carry out numerical modeling and diagnostic studies to investigate the predictibility of the monthly and seasonally averaged circulation of the atmosphere. The longer term goal of the research is to investigate the predictibility of the coupled land-ocean-atmosphere system. The focus of the work is practical, seeking to put together a numerical model, adapted from the operational version used by the National Meteorological Center(NMC), that should be able to produce extended range forecasts, and to put such a model to test. To accomplish this, the strategy is to utilize realistic models of individual components (atmosphere, ocean, and land surface processes) and to carry out sensitivity and predictibility studies, first to examine the predictibility of each component separately, and ultimately to examine the predictibility of the fully coupled interactive system. This is important because it will not only provide a crucial interface between the university research community and the NMC, but also allow development of better data sets as well as improve NMC's forecast capabilities beyond the current limit of around two weeks.