Identification and Verification of Mesoscale Convective Systems in the Models of the High Resolution Ensemble Forecast System

Milne, Jeffrey

Identification and Verification of Mesoscale Convective Systems in the Models of the High Resolution Ensemble Forecast System

dc.contributor.advisor	Brooks, Harold
dc.contributor.author	Milne, Jeffrey
dc.contributor.committeeMember	Cavallo, Steven
dc.contributor.committeeMember	Hitchcock, Stacey
dc.contributor.committeeMember	Homeyer, Cameron
dc.contributor.committeeMember	Marsh, Patrick
dc.contributor.committeeMember	McPherson, Renee
dc.date.accessioned	2024-09-13T16:21:38Z
dc.date.available	2024-09-13T16:21:38Z
dc.date.issued	2024-12-13
dc.date.manuscript	2024-09-12
dc.description.abstract	To better understand the characteristics of storms produced by forecast models and those seen in observations, contiguous and nearly contiguous radar objects with reflectivity above a convective threshold were identified and their shapes analyzed. The area, aspect ratio, orientation angle and maximum reflectivity within the object were calculated. For all members of the High Resolution Ensemble Forecast system, the modeled and observed storm objects had similar distributions in area-aspect ratio space. Modeled storm objects had a preferred band of maximum reflectivity that was not seen in the observed storm objects. The modeled storm objects also had a more north-south orientation than observed. Despite these differences, the shape characteristics of the modeled storm objects were still close enough to modeled storm objects to proceed with the creation of an MCS identification and tracking algorithm. The identification algorithm was based on one developed for MCS identification and tracking of observed storms at the NOAA Storm Prediction Center. A novel tracking algorithm was developed based on continuous swaths of maximum reflectivity and tuned to match expert labeling. Together, the identification and tracking algorithm produced a one year spatial distribution of MCSs that was somewhat consistent with an observed climatology. Additional verification of the identification and tracking algorithm revealed an underforecast from all of the models. At both the diurnal and annual scale, the models generally did not match the shape of the observed distribution. Matching the forecast MCSs with observed MCSs further showed low bias, though the forecasts did have very low FAR. The tuned parameters did not necessarily improve the forecast compared to the default parameters. The positional error between the modeled and observed MCSs showed that when the model produced an MCS, it was usually close to an observed MCS and oriented the same direction as the observed MCS.	en_US
dc.identifier.uri	https://hdl.handle.net/11244/340628
dc.language	en_US	en_US
dc.rights	Attribution-NonCommercial-ShareAlike 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/4.0/	*
dc.subject	mesoscale convective system	en_US
dc.subject	forecast verification	en_US
dc.subject	forecast evaluation	en_US
dc.thesis.degree	Ph.D.	en_US
dc.title	Identification and Verification of Mesoscale Convective Systems in the Models of the High Resolution Ensemble Forecast System	en_US
ou.group	College of Atmospheric and Geographic Sciences::School of Meteorology	en_US
shareok.orcid	0000-0001-6917-4410	en_US