Projects

MSU Award Number

191001-363513-4C

Current NGI File Number

19-NGI3-85

Associated MSU Award or NGI File Numbers

17-NGI3-34, 19-NGI3-85

Start Date

8/1/2017

End Date

2020-7-31 0:0:0

Project Status

Completed

Award Amount

$237,918.00

Project Title

Bayesian Merging of GLM Data with Ground-Based Networks

PI Last Name

Bitzer

PI First Name

Phillip

PI Affiliation

UAH

Research Theme

CH-CE

Funding Source

NESDIS

Project Description

Calculations for tropical cyclone intensification was sought by researchers using a product that merges Geostationary Lightning Mapper (GLM) data with ground-based observations in a Bayesian manner for a ratio of intracloud flashes to cloud to ground flashes. They trained and validated a random forest model to estimate the probability a flash is intracloud, based on optical attributes, and applied the model to tropical cyclone case studies for 2019 and 2020 to investigate its relationship to tropical cyclone intensification. An analysis of the case studies followed along with the development of a GLM beta data set with near real time capabilities that contain the probability a flash is intracloud. Their work suggests there is a signal in the cloud flash fraction that relates to tropical cyclone intensification. The cloud flash fraction (CFF) product will be developed further into the operational environment, including the exploration of suitable time steps in which to display the product to forecasters.