The Use of BOIVerify at WFO Miami to Maximize Efficiency as a Way to Better Achieve the Advances in Science and Technology Needed to Realize the Vision of a Weather-Ready Nation

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Thursday, 8 January 2015: 4:15 PM
232A-C (Phoenix Convention Center - West and North Buildings)
Malarie Dauginikas, Univ. of Miami, Miami, FL; and J. G. Estupiñán, A. Kennedy, and P. Santos

The issuance of gridded temperature forecasts by NWS Weather Forecast Offices requires an assessment of the accuracy of the various guidance products available to the forecasters. During late winter and early spring of 2012, WFO Miami conducted a study investigating the accuracy of gridded temperature forecasts using BOIVerify. BOIVerify was designed in 2006 by Tim Barker, a meteorologist at the Boise WFO (Barker, 2006) as a way to archive and verify gridded forecasts made by both human and models of various elements. This initial study evaluated the temperature performance for different wind regimes and for the initial set of models used in BOIVerify. We found that both the bias-corrected statistical and dynamical models performed best for South Florida for the evaluation period. Since then, WFO Miami has been using BOIVerify to verify the gridded forecasts and visualize the guidance before it is used in the official forecasts. In the winter of 2013/2014, WFO Miami upgraded to AWIPS II operational platform, which allowed us to increase considerably the number of models used in BOIVerify. In this 2nd study, we evaluated the performance of temperature forecasts on both a point and grid scale for many different models, and compared the results to the performance of MAV/MEX, the benchmark originally used by the NWS and other weather forecasting entities to evaluate the performance of their temperature forecasts. We assessed model performance over different forecast time periods and during high impact weather events to determine how individual models perform under these varying circumstances. The value added by the official forecast is investigated under various weather conditions. The Probablity of Precipitation (PoP) forecasts are also evaluated for several models in terms of reliability and accuracy, and during different time periods and high impact events. Initial results show that several model blends are performing better than MAV/MEX for both maximum and minimum temperature. PoP reliability diagrams show that certain PoP values were underestimated suggesting a possible dry bias. The results of this study will be used to maximize efficiency addressing the improvements and advances in science and technology needed to realize the vision of a Weather-Ready Nation. BOIVerify will be used as an essential tool to create and improve policy and guidelines set forth locally, regionally, and nationally related to the construction of our gridded forecasts.