Application of the NCEP Regional Spectral Model to improve mesoscale weather forecasts in Hawaii

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Abstract

The operational implementation of the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) in Hawaii is the first application of a mesoscale model to improve weather forecasts in the Pacific region. The primary model guidance for the National Weather Service Pacific region has been provided by the NCEP Aviation (AVN) run of the Global Spectral Model (GSM). In this paper, three recent synoptic-scale disturbances that affected the Hawaiian Islands are selected to demonstrate the potential utility of model guidance produced by the RSM and contrast it qualitatively with that from the AVN. NCEP RSM simulations, with enhanced grid resolution, can resolve convective rainbands and the interaction between the environmental airflow and the complex island topography, features the GSM cannot capture. RSM model performance in reproducing mesoscale structures associated with the synoptic-scale systems is encouraging. For the first simulation, a kona low case on 3 November 1995, the RSM predicted a northeast-southwest-oriented rainband that closely matched a convective cloud band in the satellite imagery and maximum rainfall over Kauai. The second RSM simulation, a cyclogenesis event on 3 March 1996, shows remarkable agreement with observations. Important features such as the heavy rains and high winds over portions of Maui and Hawaii are accurately forecast. The third RSM simulation, a heavy rain event on 13 November 1996, is associated with convergence along a trailing cold-frontal trough. In this case the RSM correctly forecast the timing and distribution of heavy rainfall on the island of Oahu. Subjective comparisons between RSM output and observations demonstrate the potential utility of the model guidance for local weather forecasts in Hawaii.

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APA

Wang, J. J., Juang, H. M. H., Kodama, K., Businger, S., Chen, Y. L., & Partain, J. (1998). Application of the NCEP Regional Spectral Model to improve mesoscale weather forecasts in Hawaii. Weather and Forecasting, 13(3 PART 1), 560–575. https://doi.org/10.1175/1520-0434(1998)013<0560:aotnrs>2.0.co;2

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