Start
November 13, 2020 - 3:00 pm
End
November 13, 2020 - 4:00 pm
Categories
Convective Meteorology (Mesoscale Dynamics)Convective Meteorology (Mesoscale Dynamics) Seminar
Assimilating Unmanned Aerial System (UAS) Observations into NSSL’s Warn-on-Forecast System (WoFS) to Improve Forecasts of QLCSs
Kelsey Britt
Friday, November 13th, 2020
3:00 pm
Join Google Meet:
https://meet.google.com/ksh-txvg-kni
The Warn-on-Forecast (WoF) project strives to produce accurate, short-term, probabilistic forecasting guidance for severe convective events and their associated hazards. An experimental, ensemble data assimilation and convection-allowing forecast system known as the Warn-on-Forecast System (WoFS) has shown promise in producing accurate ensemble forecasts for supercells with tornadic mesocyclones, flash flooding events, and even tropical cyclones. However, WoFS forecasts for quasi-linear convective systems (QLCSs) have yet to be holistically examined. A QLCS that will be examined in this study is the 10 August, 2020 derecho that caused widespread wind damage in Iowa and parts of Illinois. The WoFS forecasts for this event are analyzed to examine what aspects of the derecho WoFS is able to forecast well and where there may be problems.
To mitigate some of the issues associated with simulating QLCSs in WoFS, the advantages of assimilating unmanned aerial system (UAS) observations will then be explored. UASs can sample the temperature, moisture, and wind fields throughout the depth of the boundary layer, which can then be assimilated into forecast systems. When assimilating these observations, previous numerical studies have shown overall improvement in forecasts, as well as increased forecast skill. Assimilating UAS observations into WoFS may improve the dynamics associated with QLCSs, which may help in forecasting hazards such as severe winds, flooding, and tornadoes.