Forecaster “Best Practices” during Operations in the Hazardous Weather Testbed Hydrology Experiment 2014

Before any member of the public receives actionable information from the National Weather Service (NWS), a forecaster must synthesize personal knowledge, computational models, and observation products to produce an expert judgment on the current situation. In order to produce accurate and actionable forecasts, forecasters may employ a wide variety of decision support products. However, such a host of experimental and operational products may lead to information overload for forecasters, or in some cases, completely ignoring certain products due to time and energy constraints which could have provided critical information. Thus, understanding forecaster decision-making patterns and uses of information during the forecasting process are of great importance. This work presents results on forecaster decision-making behavior and decision support products during the 2014 Hazardous Weather Testbed Hydrology Experiment (HWT-Hydro). Held at the National Weather Center in the summer of 2014, HWT-Hydro brought together researchers and NWS forecasters in an effort to evaluate experimental flash flood prediction models, including products in the FLASH (Flooded Locations and Simulated Hydrographs) product suite. One particular goal of HWT-Hydro was to identify forecasting best practices in terms of information use when issuing experimental flash flood watches and warnings. Each day, as forecasters produced experimental flash flood watches and warnings using operational and experimental products, participant observation, questionnaires, and interview techniques provided insight forecast decisions.