U.S. regional climate simulations and seasonal forecasts

[1] Does a regional climate model provide a more useful regional climatology than can be obtained from larger-scale global analyses or a better regional forecast than can be obtained by a large-scale seasonal prediction model? To examine these questions, U.S. regional spectral model (RSM) climate simulations forced by 1-day global spectral model (GSM) forecasts initialized from the National Centers for Environmental Prediction (NCEP) operational analysis are compared with regional RSM simulations forced by the NASA Seasonal to Interannual Prediction Project general circulation model (GCM). The GCM was continuously forced by observed sea surface temperature variations, but since sea surface temperatures (SSTs) are so persistent, these forced GCM simulations were equivalent to seasonal GCM predictions, which are mainly based upon persistent SSTs anyhow. RSM simulations forced by these two global modes were compared at the same spatial resolution as the global models (200 km) and at higher resolution (50 km). Resolution was important for producing better geographic pictures but does not currently produce significantly more skillful regional climate simulations or forecasts of the temporal variability, which already have significant skill from the global models. However, regional climate simulations and forecasts better depict the precipitation intensity, especially over the U.S. West. Finally, re-initialized (from the large-scale analysis) 1-day RSM forecasts were compared with continuous RSM simulations, and this increased the overall regional skill back to the original GSM skill, which was somewhat degraded in continuous RSM simulations.

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