The GOESR Risk Reduction Project (GOES-R3)

2017 through 2020 Participants, Projects/Proposals, and Reports

ParticipantsContactsProjectsProject Titles 2016-2019January-June 2017 ReportJuly-December 2017 ReportJanuary-June 2018 ReportJuly-December 2018 ReportJanuary-June 2019 ReportJuly-December 2019 ReportJanuary-June 2020 Report
CoRP2016
2017
CIMSS StAR
Mike Pavolonis Mike.Pavolonis@noaa.gov301VOLCAT Development for GOES-R: Volcanic Ash and SO2ReportReportReportReportReport
Mike Pavolonis Mike.Pavolonis@noaa.gov302Fog and Low StratusReportReportFinalReport
Tony Wimmers Wimmers@ssec.wisc.edu303Evaluation of Turbulence-Detection Methods on Himawari-8ReportReportFinalReport
Brad Pierce Brad.Pierce@noaa.gov Chris Velden chrisv@ssec.wisc.edu Megan Bela megan.bela@noaa.gov308CIMSS Support to GOES-R High Impact Weather Risk ReductionReportReportReportReportReportReport
Mike Pavolonis Mike.Pavolonis@noaa.gov421ProbSevere: Upgrades and Adaptation to Offshore ThunderstormsCIMSS Report
CIRA Report
ReportReportReportReport
Jun Li Jun.Li@ssec.wisc.edu439Improving the Assimilation of High-Resolution GOES-16 Water Vapor Variables and Atmospheric Motion Vectors in the HWRF ModelReportReportReportReportReportFinalReport
Claire Pettersen Claire.Pettersen@ssec.wisc.edu Mark Kulie Mskulie@wisc.edu480An Enhanced Lake Effect Nowcasting Tool Using Synergistic GOES-R, NEXRAD, and Ground-Based Snowfall Microphysics ObservationsReportReportReportFinalReport
Satya Kalluri Satya.Kalluri@noaa.gov488Upgrading the GOES ET and Drought (GET-D) Product System for GOES-16 and 17ReportReport
CIRA StAR
Chris Kummerow Christian.Kummerow@colostate.edu Steve Miller Steven.Miller@colostate.edu Kyle Hilburn Kyle.Hilburn@colostate.edu307Connecting GOES-R High Resolution Temporal Information with Rapid Updating ModelsReportReportReportReportReportReportFinalReport
Milija.Zupanski Milija.Zupanski@colostate.edu410Data assimilation of GLM observations in HWRF/GSI systemReportReportReportReportFinalReport
Lewis Grasso Lewis.Grasso@colostate.edu420GOES-R ABI channel differencing used to reveal cloud-free zones of ‘precursors of convective initiation’ReportReportReportReportReportFinalReport
John Forsythe John.Forsythe@colostate.edu444Using the New Capabilities of GOES-R to Improve Blended, Multisensor Water Vapor Products for ForecastersReportReportReportReportReportReport
Steve Miller Steven.Miller@colostate.edu476Developing an Environmental Awareness Repertoire of ABI Imagery (‘DEAR-ABII’) to Advise the Operational Weather ForecasterReportReportReportReportReportFinal Report
John Haynes John.Haynes@colostate.edu479Improving the ABI Cloud Layers Product for Multiple Layer Cloud Systems and Aviation Forecast ApplicationsReportReportReportReportReportReport
CIRA CIMMS
Kristin Calhoun Kristin.Kuhlman@noaa.gov477Integration of the Geostationary Lightning Mapper with ground-based lightning detection systems for National Weather Service OperationsReportReportReportFinalReport
Other
George Mason UniversitySanmei Li Slia@masonlive.gmu.edu402Integration of GOES-R/ABI data in Flood Mapping Software for Flood Monitoring and ForecastingReportReportReportReportReportFinalReport
University of OklahomaPierre Kirstetter Pierre.Kirstetter@noaa.gov424Probabilistic precipitation rate estimates from GOES-R for hydrologic applicationsReportReportReportReportReport
University of OklahomaXuguang Wang Xuguang.Wang@ou.edu449Assimilation of high resolution GOES-R ABI infrared water vapor and cloud sensitive radiances using the GSI-based hybrid ensemble-variational data assimilation system to improve convection initiation forecastReportReportReportReportReport
University of Alabama-HuntsvillePhillip Bitzer phillip.bitzer@nsstc.uah.edu450Bayesian Merging of GLM data with Ground-Based Networks
NASA MSFCChristopher Schultz Christopher.J.Schultz@nasa.gov460Utilizing Sub-Flash Properties of GLM to Monitor Convective Intensity with Probabilistic GuidanceReport PosterReport PosterReportReportFinalReport
CAPS University of OklahomaMing Xue Mxue@ou.edu473Assimilation of High-Frequency GOES-R Geostationary Lightning Mapper (GLM) Flash Extent Density Data in GSI-Based EnKF and Hybrid for Improving Convective Scale Weather PredictionsReportReportReportReportReport

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