Syewoon Hwang, Wendy Graham, José L Hernandez, Chris Martinez, James W. Jones , Quantitative Spatiotemporal Evaluation of dynamically downscaled MM5 precipitation predictions over the Tampa Bay region, Florida, 
Journal of Hydrometeorology (accepted), 2011-04-11

Abstract [-]: This research quantitatively evaluated the ability of the Fifth-Generation Mesoscale Model (MM5) to reproduce observed spatiotemporal variability of precipitation in the Tampa Bay region over the 1986 to 2008 period. Raw MM5 model results were positively biased, therefore the raw model precipitation outputs were bias-corrected at 53 long-term precipitation stations in the region using the cumulative probability distribution (CDF) mapping approach. CDF mapping effectively removed the bias in the mean daily, monthly and annual precipitation totals and improved the root mean square error (RMSE) of these rainfall totals. Observed daily precipitation transition probabilities were also well predicted by the bias-corrected MM5 results. Nevertheless significant error remained in predicting specific daily, monthly and annual total time series. After bias-correction, MM5 successfully reproduced seasonal geostatistical precipitation patterns, with higher spatial variance of daily precipitation in the wet season and lower spatial variance of daily precipitation in the dry season. Bias-corrected daily precipitation fields were kriged over the study area to produce spatiotemporally distributed precipitation fields over the dense grids needed to drive hydrologic models in the Tampa Bay Region. Cross-validation at the 53 long-term precipitation gages showed that kriging reproduced observed rainfall with average RMSEs lower than the RMSEs of individually bias-corrected point predictions. Results indicate that although significant error remains in predicting actual daily precipitation at rain gages, kriging the bias-corrected MM5 predictions over a hydrologic model grid produces distributed precipitation fields with sufficient realism in the daily, seasonal and inter-annual patterns to be useful for multi-decadal water resource planning in the Tampa Bay Region.

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