The Evolving Role of the Mesoanalyst in Collaborative Severe Weather Forecasting and Communication

The near real-time availability of diverse high-resolution data sets is both advantageous and problematic for operational forecasters. Tools such as GOES-16 satellite imagery, hourly output from convection-allowing mesoscale models, probabilistic decision aids such as the NOAA/CIMSS ProbSevere Model, and Multi-Radar/Multi-Sensor System data present unprecedented opportunity to improve situational awareness during convective events. The essential challenge lies in determining which data are of primary importance and knowing how to mine those data to improve warning and forecast decisions. National Weather Service (NWS) forecasters participating in various evaluations at the NWS Operations Proving Ground (OPG) have suggested this challenge is best addressed by elevating the importance of expert mesoanalysis on the convective warning team. This is especially true in complex environments and scenarios characterized by rapidly evolving convective modes. In addition to enhancing warning performance, expert mesoanalysis could form the foundation for innovative services in the temporal gap between watches and warnings. By effectively synthesizing knowledge of the evolving mesoscale environment, along with understanding of core partner decision thresholds, it is possible for the warning team to communicate precise, timely, and actionable information to risk management professionals – in some cases, before convection even develops. Noted experts from the Storm Prediction Center, NWS Weather Forecast Offices (WFOs), and the NWS Warning Decision Training Division have been collaborating with the OPG for the past year to develop a week-long immersive experience that will assess forecaster capabilities to integrate these duties into their severe weather operation plans. In 2019, the OPG will host proof-of-concept evaluations to assess the viability of incorporating those practices into the WFO environment. Lessons learned will then be examined for potential application to Winter Storms, Fire Weather, and other service sectors.