Recent Advancements of the Research-to-Operations (R2O) Process at HMT-WPC

The Weather Prediction Center (WPC) is the national center responsible for providing the nation's precipitation forecasts; therefore its ability to implement a successful research-to-operations (R2O) process is critical to moving the science of prediction forward. The main responsibility for this transition is given to the WPC's Hydrometeorological Testbed (HMT-WPC), which has developed a methodology for systematically testing and evaluating new developments from the research and operational numerical modeling communities and implementing them into WPC operations. The methodology consists of a three-step process consisting of 1) developing new forecasting tools and testing new data sets in both real-time and retrospective forecasting experiments, 2) subjective and objective evaluation of the experimental products, and 3) operational training and implementation.

This presentation will illustrate HMT-WPC's recent R2O advancements by highlighting the transition of three recent innovations: the Earth System's Research Laboratory Physical Science Division's (ESRL/PSD) 2nd Generation Reforecast dataset, the ESRL Global Systems Division's (GSD) Experimental Regional Ensemble Forecasting (ExREF) system, and the Environmental Modeling Center's (EMC) rime-factor snowfall product derived from the Ferrier microphysics used in North American Mesoscale Model (NAM). The reforecast dataset and an earlier version of the ExREF were featured in HMT-WPC's 2012 Atmospheric River Retrospective Forecasting Experiment (ARRFEX), while the current version of the ExREF was highlighted in the HMT-WPC/NSSL's 2013 Flash Flood and Intense Rainfall (FFaIR) experiment. EMC's rime-factor snowfall product involved a close collaboration between EMC and HMT-WPC staff; this product was featured and evaluated in HMT-WPC's 2013 Winter Weather Experiment as a potential tool to advance snowfall forecast guidance. The evaluation process and subsequent results of the datasets' performance in the experiments will be highlighted, and the processes of ingesting promising data, developing forecasting tools, and displaying it on the operations floor will be discussed.