2016 and 2017 Participants, Projects/Proposals, and Reports

 

ParticipantsContactsProject NumbersProposal Titles 2016 and 2017July-December 2016 ReportsJanuary-June 2017 ReportsJuly-December 2017 Reports
Cooperative Institutes2016 2017
CIMSS STARMike Pavolonis
Mike.Pavolonis@noaa.gov
301SO2 DetectionReportReport
Mike Pavolonis
Mike.Pavolonis@noaa.gov
302Fog and Low StratusReportReportReport
Tony Wimmers
Wimmers@ssec.wisc.edu
303Turbulence Detection
Brad Pierce
brad.pierce@noaa.gov
308CIMSS Support to GOES-R High Impact Weather Risk ReductionReportReport
Satya Kalluri
Satya.Kalluri@noaa.gov
406Assessment of GOES-R ABI Level 1B Radiances for NWP Applications
Mike Pavolonis
Mike.Pavolonis@noaa.gov
421ProbSevere: Upgrades and Adaptation to Offshore Thunderstorms
CIMSS Report CIRA Report
Jun Li
Jun.Li@ssec.wisc.edu
439Improving the Assimilation of High-Resolution GOES-16 Water Vapor Variables and Atmospheric Motion VectorsReport
Mark Kulie
mskulie@wisc.edu
480An Enhanced Lake Effect Nowcasting Tool Using Synergistic GOES-R, NEXRAD, and Ground-Based Snowfall Microphysics Observations
Walter Wolf
Walter.Wolf@noaa.gov
486Development of GOES-R IR Clear-Sky and All-Sky Radiance Products for NCEPReport
CIRA STARChris Kummerow christian.kummerow @colostate.edu Steve Miller Steven.Miller @colostate.edu Dan Lindsey Dan.Lindsey@noaa.gov307Connecting GOES-R High Resolution Temporal Information with Rapid Updating ModelsReportReportReport
Milija.Zupanski Milija.Zupanski @colostate.edu410Data assimilation of GLM observations in HWRF/GSI systemReport
Lewis Grasso Lewis.Grasso @colostate.edu420GOES-R ABI channel differencing used to reveal cloud-free zones of ‘precursors of convective initiation’Report
John Forsythe John.Forsythe @colostate.edu444Using the New Capabilities of GOES-R to Improve Blended, Multisensor Water Vapor Products for ForecastersReport
Steve Miller Steven.Miller @colostate.edu476Developing an Environmental Awareness Repertoire of ABI Imagery (‘DEAR-ABII’) to Advise the Operational Weather ForecasterReport
John Haynes John.Haynes @colostate.edu479Improving the ABI Cloud Layers Product for Multiple Layer Cloud Systems and Aviation Forecast ApplicationsReport
CIRA CIMMSKristin Calhoun Kristin.Kuhlman @noaa.gov477Integration of the Geostationary Lightning Mapper with ground-based lightning detection systems for National Weather Service OperationsReport
CICS STARRalph Ferraro ralph.r.ferraro @noaa.gov309GOES-R Water Cycle Products and Services to Support the NWSReportReportReport
Other
University of Wisconsin MadisonPao Wang pwang1@wisc.edu304Modeling of Cloud Top Features
George Mason UniversitySanmei Li slia@masonlive.gmu.edu402Integration of GOES-R/ABI data in Flood Mapping Software for Flood Monitoring and ForecastingReport
University of OklahomaPierre Kirstetter pierre.kirstetter @noaa.gov424Probabilistic precipitation rate estimates from GOES-R for hydrologic applicationsReport
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 forecastReport
University of Alabama-HuntsvillePhillip Bitzer pm.bitzer@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 Poster Abstract
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 PredictionsReport
University of Alaska FairbanksMartin Stuefer stuefer@gi.alaska.edu487GOES-R Volcanic Ash Risk Reduction (R3): New operational GOES-R decision support within NOAA’s High Resolution Rapid RefreshReport

 

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