Siegfried Schubert (PI)
NASA Goddard Space Flight Center
siegfried.d.schubert@nasa.gov

Pathways to Predictability on Sub-Seasonal Time Scales: Assessing the Role of Tropical Forcing and Land Surface Conditions

A major gap exists in our understanding and predictive capabilities for time scales that lie just beyond the limits of deterministic weather prediction and just short of one season (approximately 2 weeks to 2 months).  These so-called “sub-seasonal” time scales are the link between weather and short-term climate and are a responsible for modulating weather predictability and for limiting predictability on seasonal and longer time scales.   NASA (in collaboration with NOAA) is now in a position to contribute to this important prediction problem, having taken important steps in the acquisition and development of key global data sets (e.g., precipitation, clouds, tropical heating estimates) and in the development of the next generation of comprehensive Earth System Models and data assimilation capabilities. Together, these will allow us to produce the long-term, consistent data sets required for subseasonal prediction.   This submission proposes to take advantage of these capabilities and data sets to assess and advance subseasonal prediction capabilities.   Our emphasis will be on extracting the potential skill associated with tropical diabatic heating and the land surface processes—two particularly important sources of untapped subseasonal predictability on these time scales (Schubert et al. 2002; Waliser et al. 2003).  Specifically, we will use the Global Modeling and Assimilation Office (GMAO) coupled models and assimilation systems to:   1)Establish our current baseline subseasonal forecast capabilities. 2)Assess the impact of improved tropical initialization provided by TRMM and other satellite data using both current and anticipated (Modern Era Reanalysis for Research and Applications or MERRA) reanalyses 3)Further quantify and assess the impact of soil moisture and snow estimates, including new experimental data products being developed at the GMAO.  Comparisons will be made with forecasts carried out with the new operational NOAA climate forecast system (CFS) model, with forecasts made by Linear Inverse Models (LIMs), as well as with “hybrid” forecasts that utilize information from the LIMs and other empirical/statistical models. The hindcasts and the analysis of the results will be closely coordinated with a companion GMAO proposal to this announcement on modeling and prediction of seasonal-to-interannual variability. All model simulations will be made available to the scientific community, and are expected to make an important contribution to NASA’s participation in NOAA’s new Climate Test Bed activities.  The work cuts across NASA-ESE research foci on Climate Variability and Change, the Global Water and Energy cycle, and weather.  Specific ESE foci questions being addressed include: How can predictions of climate variability and change be improved? and How are variations in local weather, precipitation and water resources related to global climate variations?

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