Ensemble downscaling of seasonal forecasts

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Wednesday, 20 January 2010: 11:30 AM
B215 (GWCC)
R. W. Arritt, Iowa State University, Ames, IA

The Multi-Regional climate model Ensemble Downscaling (MRED) project is downscaling ensemble forecasts from coupled-atmosphere ocean seasonal prediction model, the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS). MRED addresses the question, Can regional climate models provide additional information from global seasonal forecasts made by coupled atmosphere-ocean models? Nested regional climate models (RCMs) have long been used to downscale global climate simulations but have seldom been applied in seasonal forecasting. MRED is systematically testing the RCM downscaling methodology by downscaling historical winter forecasts from a T62L64 version of the CFS, using eight regional models at approximately 32 km node spacing. Each RCM downscales a 15-member CFS ensemble per year from 1982 to 2003 for the forecast period 1 December – 30 April. The CFS ensemble is produced by integrating the model beginning from different start dates in the month immediately preceding the forecast period. This procedure produces a 120-member ensemble for each season; i.e., 15 CFS simulations each downscaled by 8 regional models.

Preliminary results show that dynamical downscaling can add regional detail to global seasonal predictions. An example is the strong El Niño event of winter 1982-83, in which the regional models produce heavy precipitation observed over California that was lacking in the CFS. This is attributed mainly to better resolution of terrain in the regional model, as the heavy precipitation is closely related to coastal topography. The fact that not all CFS ensemble members produced the heavy observed precipitation when downscaled by the regional model has two major implications. First, it emphasizes that the skill of this downscaling approach ultimately depends on the ability of the global model to represent large-scale winds and thermodynamics. Second, it shows that while there is potential skill in combining a coupled atmosphere-ocean global seasonal forecast model with nested regional climate models, an ensemble approach is essential to realizing the added value from such an approach.