Downburst Potential Monitoring

1. Downburst Potential Monitoring Presented by Ken Pryor

2. Requirement, Science, and Benefit Requirement/Objective • Commerce & Transportation: • Enhance navigational safety and efficiency by improving information products and services. • Reduce weather-related transportation crashes and delays. • Weather & Water: • Increase lead time and accuracy for weather and water warnings and forecasts • Improve predictability of the onset, duration, and impact of hazardous and severe weather and water events. Science • How can predictability of severe convective storm winds, and lead time and accuracy of severe weather warnings be improved? Benefit • The GOES microburst products provide real-time guidance to operational weather forecasters, emergency planners, aviators, mariners, and the general public. This guidance will be effective in the severe weather warning process, severe convective wind hazard mitigation, and the avoidance of downburst-related transportation accidents.

3. Challenges and Path Forward Science challenges • Detection of cold-season downburst environments. • Sources of ground truth for product validation and algorithm training. Next steps • Refinement and validation of GOES sounder and imager microburst products: • Focus over eastern U.S. using National Ocean Service (NOS) surface observation data from Physical Oceanographic Real-Time System (PORTS). • Develop nowcasting technique that employs Rapid Update Cycle (RUC) model data and radar reflectivity imagery. Transition Path • Experimental Microburst Windspeed Potential Index (MWPI) product will be implemented in the GOES-R framework and then provided to National Weather Service (NWS), Dept. of Defense (DOD), and private sector meteorologists.

4. Basics of Downburst Potential Monitoring Two ways to monitor downburst potential: • GOES Imager: relate brightness temperature differences from IR bands (3, 4, 5) to vertical thermodynamic profile and resulting microburst potential. • Strengths: High temporal (15 min., CONUS) and spatial (4km) resolution. • Weaknesses: Poor vertical resolution, underestimates microburst risk in humid environments, vulnerable to cloud contamination. • GOES Sounder: relate vertical temperature and moisture differences and stability parameters (i.e. CAPE) to thermodynamic profile and resulting microburst wind speed potential. • Strengths: High vertical resolution, explicit quantification of sounding parameters (i.e. T, TD, CAPE). • Weaknesses: Poor temporal (60 min.) and spatial (10km) resolution, dependent on availability of clear-sky retrievals

5. Multispectral GOES Imager Product • Developed by STAR in 2008 • Split-window channel (band 5, 12μm) allows for the inference of boundary layer moisture content. • Strong negative correlation between 6.7μm brightness temperature (Tb) and layer-averaged relative humidity (RH) between the 200 and 500-mb levels. • Output brightness temperature difference (BTD) is proportional to microburst potential: • BTD = {T5 – T3} – {T4 – T5} • Best suited for assessment of dry/hybrid microburst potential • Experimental product available in real-time on STAR web page: http://www.star.nesdis.noaa.gov/ smcd/opdb/kpryor/mburst/mbimg.html McIDAS-V visualization

6. Challenges and Path Forward Science challenges • Detection of cold-season downburst environments. • Sources of ground truth for product validation and algorithm training. Next steps • Refinement and validation of GOES sounder and imager microburst products: • Focus over eastern U.S. using National Ocean Service (NOS) surface observation data from Physical Oceanographic Real-Time System (PORTS). • Develop nowcasting technique that employs Rapid Update Cycle (RUC) model data and radar reflectivity imagery. Transition Path • Experimental Microburst Windspeed Potential Index (MWPI) product will be implemented in the GOES-R framework and then provided to National Weather Service (NWS), Dept. of Defense (DOD), and private sector meteorologists.