Prediction of Near-Surface Variables at Independent Locations from a Bias-Corrected Ensemble Forecasting System

Abstract

Abstract The ability of a multimodel short-range bias-corrected ensemble (BCE) forecasting system, created as part of NOAA’s New England High Resolution Temperature Program during the summer of 2004, to obtain accurate predictions of near-surface variables at independent locations within the model domain is explored. The original BCE approach produces bias-corrected forecasts only at National Weather Service (NWS) observing surface station locations. To extend this approach to obtain bias-corrected forecasts at any given location, an extended BCE technique is developed and applied to the independent observations provided by the Oklahoma Mesonet. First, a Cressman weighting scheme is used to interpolate the bias values of 2-m temperature, 2-m dewpoint temperature, and 10-m wind speeds calculated from the original BCE approach at the NWS observation station locations to the Oklahoma Mesonet locations. These bias values are then added to the raw numerical model forecasts bilinearly interpolated to this same specified location. This process is done for each forecast member within the ensemble and at each forecast time. It is found that the performance of the extended BCE is very competitive with the original BCE approach across the state of Oklahoma. Therefore, a simple postprocessing scheme like the extended BCE system can be used as part of an operational forecasting system to provide reasonably accurate predictions of near-surface variables at any location within the model domain.