Deriving Operationally Relevant Tornado Probabilities from Convection-Allowing Ensembles

Gallo, Burkely

Deriving Operationally Relevant Tornado Probabilities from Convection-Allowing Ensembles

dc.contributor.advisor	Clark, Adam
dc.contributor.advisor	Wang, Xuguang
dc.contributor.author	Gallo, Burkely
dc.contributor.committeeMember	Brooks, Harold
dc.contributor.committeeMember	Cavallo, Steven
dc.contributor.committeeMember	Richman, Michael
dc.contributor.committeeMember	Trytten, Deborah
dc.date.accessioned	2017-12-08T14:45:07Z
dc.date.available	2017-12-08T14:45:07Z
dc.date.issued	2017-12
dc.date.manuscript	2017-12
dc.description.abstract	Hourly maximum fields of simulated storm diagnostics from experimental versions of convection-allowing models (CAMs) provide valuable information regarding severe weather potential. The focus of this work is to extract operationally relevant tornado probabilities from the CAM-based Weather Research and Forecasting (WRF) ensemble initialized daily at the National Severe Storms Laboratory (NSSL-WRF). Probabilities are derived in three main ways: by using updraft helicity (UH), UH filtered by model-derived environmental parameters, and through combining UH and model-derived environmental parameters with observed climatological tornado frequencies. Contrasting these methods compares a binary threshold exceedance approach and a probabilistic paradigm. Rather than using a specific threshold of UH as a proxy for tornadogenesis and relying on the ensemble to generate probabilities, the probabilistic approach treats each point as having a certain probability of producing a tornado, depending on the surrounding environmental conditions. Additionally, the ensemble-generated forecasts using both approaches are compared with the 0600 UTC Storm Prediction Center (SPC)’s tornado probabilities, to determine whether ensemble forecasts approach the skill of expert forecasters. While the methods derived using the threshold approach overforecast tornado probability magnitude, the probabilities that incorporate climatological frequency information perform much more reliably, particularly when the storm timing was considered. For the probabilistic forecasts to be operationally relevant, cooperation with forecasters is critical in their development. A database of right-moving supercells developed by SPC forecasters was used to generate the climatological frequencies on which three sets of probabilities are based. Through NOAA’s Hazardous Weather Testbed Spring Forecasting Experiment (SFE), subjective daily evaluation of the probabilistic forecasts provided feedback during SFE 2015 that led to the development of the climatological frequency probabilities. When the climatological frequency probabilities were evaluated in SFE 2017, the prevalence of false alarm from nocturnal mesoscale convective systems led to the incorporation of timing information which reduces that false alarm. Therefore, the forecast probabilities are targeting the right-moving supercells, reflecting the underlying climatological frequencies.	en_US
dc.identifier.uri	https://hdl.handle.net/11244/52733
dc.language	en_US	en_US
dc.subject	Forecasting	en_US
dc.subject	Tornadoes	en_US
dc.subject	Convection-Allowing Ensembles	en_US
dc.subject	Numerical Weather Prediction	en_US
dc.thesis.degree	Ph.D.	en_US
dc.title	Deriving Operationally Relevant Tornado Probabilities from Convection-Allowing Ensembles	en_US
ou.group	College of Atmospheric & Geographic Sciences::School of Meteorology	en_US