WCD-26. Development and Analysis of Operational Forecast Tools at the Weather Prediction Center

Abstract
The Weather Prediction Center (WPC) is one of nine national centers within the National Weather Service (NWS) and primarily focuses on forecasting precipitation, temperature, and hazards for the contiguous United States. The WPC Development and Training Branch (DTB) is home to many CIRES scientists and developers who work alongside federally-employed developers and operational forecasters. Collaborating both internally and externally, this team of scientists works to develop and improve products for use in operational processes for NWS forecasters. Therefore, the scope of this presentation is broad, encompassing a wide array of topics that our team works on spanning winter to warm season weather and impacts. Four major projects currently fund a large portion of the work that is completed at the WPC by CIRES scientists. The first of these projects is the HydroMeteorology Testbed (HMT), which evaluates new technologies, research results, and other scientific advancements to enhance NWS products & services. The testbed welcomes collaborative relationships from across the weather enterprise. The HMT includes three major components: Flash Flood and Intense Rainfall (FFaIR), the Winter Weather Experiment (WWE), and the Day 8-10 Experiment. After evaluating experimental precipitation forecasts with input and feedback from their attendees, the HMT provides final reports which summarize the experiment results, which includes transition to operations recommendations, and are shared with their stakeholders. CIRES scientists also contribute to the Winter Storm Severity Index (WSSI) suite of products. The WSSI displays the severity of anticipated societal impacts due to winter weather on a 4-tiered scale (minor, moderate, major, and extreme). The product has undergone years of development with a successful transition to operations. The WSSI has been used during many extreme winter weather events in WPC’s Key Messages infographic, and has been shared by many media outlets both in local and national markets. Additional WSSI products include an experimental probabilistic version, an hourly version in development, and a version for Alaska that is in the early stages of development. Probabilistic forecasting is a valuable tool when trying to communicate the uncertainty within a forecasted event. The Dynamic Ensemble-based Scenarios for Impact-based Decision Support Services (DESI) is a prototype tool constructed to allow a forecaster to investigate forecast uncertainty. CIRES scientists have contributed significantly to this product through developing cluster analysis tools and comparing the forecasts of precipitation and temperature to climatological patterns. While still in its infancy, DESI has been shown to improve the forecast process through effectively increasing useful information without unnecessarily overwhelming the user. Finally, a number of CIRES scientists are working on a project to improve and operationalize object-based precipitation products. Products that employ Model Evaluation Tools (MET) are analyzed to discover areas where forecasts can be improved upon using object-based tracking metrics. A significant portion of this project is to improve the communication abilities of these tools. This will be accomplished through the development of a new web interface that will allow users to more effectively interrogate the data and products.