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The science and practice of seasonal climate forecasts have progressed significantly in the last couple of decades (Carson 1998; Goddard et al. 2001; Palmer and Anderson 1994). It has been demonstrated that seasonal forecasts are skillful in many regions, particularly in the tropics (Goddard et al. 2003; Gong et al. 2003; Stockdale et al. 1998). General circulation models (GCMs) have been employed in seasonal climate forecasting at various centers (Derome et al. 2001; Frederiksen et al. 2001; Mason et al. 1999; O’Lenic 1994; Ward et al. 1993). Due to computational constraints, GCMs typically are run at relatively coarse spatial resolutions generally greater than 2.0° for both latitude and longitude. The direct result of the poor spatial resolution of GCMs is a serious mismatch of spatial scale between the available climate forecasts and the scale of interest to most climate forecast users. Some applications also require climate forecasts with higher temporal resolution. Most crop models, for example, require daily weather input. GCM outputs are available as the required daily values, but GCM daily precipitation shows very low daily variability and many high errors compared to observations (Mearns et al. 1990). |
