Research Tools: Uncrewed Aircraft @ NSSL

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Damage assessments provide insight into the occurrence, intensity, and distribution of tornadoes and other high-wind events. Current ground survey and satellite assessments, however, are restricted by available resources (e.g., personnel, time, and cost), accessibility, technological limitations, and damage indicators used to infer storm intensity. These assessments can be especially challenging in rural areas because storm damage is frequently underestimated due to the inability to detect vegetation stress, limited vegetation damage indicators, and low population density. In these sparsely populated areas, storm damage is often underreported and consequently affects severe storm climatology and our understanding of risk. Underestimating this risk can have serious implications on hazard monitoring as well as disaster preparedness and recovery in rural areas.

With the help of the NOAA Oceanic and Atmospheric Research (OAR) Uncrewed Systems Research Transition Office (USRTO), scientists from the NOAA National Severe Storms Laboratory in collaboration with the Cooperative Institute for Mesoscale Meteorological Studies are working on developing an uncrewed aircraft system (UAS)-based approach to better characterize high-wind damage to vegetation and in rural areas to improve disaster response and recovery.

The objectives of this project are to:

  1. Better characterize high-wind damage to vegetation and in rural areas using a system that integrates UASs, multispectral imagery, and geospatial methods,
  2. Correlate storm processes to UAS-based damage information and radar data (e.g., WSR-88D),
  3. Rapidly distribute damage information to improve disaster response and recovery.

The very high resolution imagery collected by the UAS allows for centimeter scale resolution, which can capture information that is frequently missed with current traditional approaches. Combining this information with meteorological observational datasets will lead to a better understanding of the relationship of identifiable storm structures and storm hazards and may lead to new discoveries in local extreme wind production phenomena. This is particularly important in the Southeast US where storm mechanisms involved in tornadogenesis remain poorly understood.

This work has the potential to improve severe weather forecasts and warnings through better documentation of severe weather events and better assignment of damage ratings in sparsely populated rural locations. This detailed UAS information will likely improve the accuracy of severe storm report database and tornado climatology. Additionally, more accurate damage information will also improve disaster loss estimates for FEMA, insurance agencies, and the affected public.