5th GOES Users' Conference
    

Poster Session 1

 Fifth GOES Users' Confererence Poster Session
P1.1ABI system overview  
Paul Griffith, ITT Space Systems Division, Fort Wayne, IN
 P1.2ABI scan scenario capabilities  
David Crain, ITT Space Systems Division, Fort Wayne, IN; and P. Griffith
 P1.3Candidate approaches for the real-time generation of cloud properties from GOES-R ABI  
Andrew K. Heidinger, NOAA/NESDIS, Madison, WI
 P1.4GOES-R architecture framework  
John W. Linn III, Noblis, Falls Church, VA; and L. Shipley
 P1.5Development of the GOES-R AWG product processing system framework  
Walter Wolf, NOAA/NESDIS/STAR, Camp Springs, MD; and L. Zhou, P. Keehn, Q. Guo, S. Sampson, S. Qiu, and M. D. Goldberg
 P1.6GOES-R Downlink Services for Users  extended abstract
John Schimm, Northrop Grumman, Redondo Beach, CA; and J. Castellon, L. Kincaid, and L. E. Urner
 P1.7The GOES ABI ground processing development system  
Jon Ormiston, ITT Space Systems Division, Fort Wayne, IN; and J. Blume, J. Ring, and J. Yoder
 P1.8Development of the GOES-R ABI Outgoing Longwave Radiation product  extended abstract
Hai-Tien Lee, University of Maryland, College Park, MD; and I. Laszlo and A. Gruber
 P1.9Applying split window technique for land surface temperature measurement from GOES-R advanced baseline imager  
Yunyue Yu, NOAA/NESDIS, Camp Springs, MD; and D. Tarpley, M. K. Rama Varma Raja, H. Xu, and K. Y. Vinnikov
 P1.10Development and validation of a BRDF model for ice mapping for the future GOES-R Advanced Baseline Imager (ABI) using Artificial Neural Network  extended abstract
Hosni Ghedira, NOAA-CREST, New York, NY; and M. Temimi, R. Nazari, P. Romanov, and R. Khanbilvardi
 P1.11GOES-R wind retrieval algorithm development  
Iliana Genkova, CIMSS/Univ. of Wisconsin, Madison, WI; and S. Wanzong, C. S. Velden, D. A. Santek, J. Li, E. R. Olson, and J. A. Otkin
 P1.12Validation of a GOES-R Broadband Shortwave Surface Transmission and TOA Albedo LUT method  extended abstract
Fred G. Rose, SSAI, Hampton, VA; and Q. Fu, I. Laszlo, and T. P. Charlock
 P1.13Validation of the Community Radiative Transfer Model (CRTM) against AVHRR Clear-Sky Processor for Oceans (ACSPO) Nighttime Radiances for improved cloud detection and physical SST retrievals  extended abstract
XingMing Liang, NOAA/NESDIS, Camp Springs, MD; and A. Ignatov, Y. Kihai, A. K. Heidinger, Y. Han, and Y. Chen
 P1.14Examining the MTSAT-1R solar channel calibration  extended abstract
Hyoung-wook Chun, Seoul National University, Seoul, South Korea; and B. J. Sohn
 P1.15GOES-R ABI calibration approach  
David S. Smith, ITT Space Systems Division, Fort Wayne, IN
 P1.16The Global Space-based Inter-Calibration System (GSICS): A status report  
Xiangqian Wu, NOAA/NESDIS, Camp Springs, MD; and M. Goldberg
 P1.17Inter-calibration of geostationary imagers with MetOP/IASI hyperspectral measurements  
Likun Wang, QSS Group Inc, Camp Spring, MD; and C. Cao
 P1.18Generating synthetic infrared GOES-R ABI Images with AVHRR and GOES images  
William J. Emery, Univ of Colorado, Boulder, CO; and C. Roessler
 P1.19Synthetic GOES-R Imagery Development and Uses  
Lewis Grasso, CIRA/Colorado State Univ., Fort Collins, CO; and M. Sengupta and D. T. Lindsey
 P1.20Large-scale WRF model simulations used for GOES-R research activities  
Jason A. Otkin, CIMSS/Univ. of Wisconsin, Madison, WI; and A. Huang, T. Greenwald, E. R. Olson, and J. Seiglaff
 P1.21New instrumentation for characterizing the Moon as a standard for space-based radiometry  
Allan Smith, National Institute of Standards and Technology, Gaithersburg, MD; and S. Lorentz, H. Yoon, R. Datla, D. Pollock, T. C. Stone, and J. Tansock
 P1.22Preliminary study of lunar calibration for geostationary imagers  
Seiichiro Kigawa, Japan Meteorological Agency, Kiyose-shi, Tokyo, Japan; and K. Miyaoka
 P1.23Synthesis of Angular Distribution Models (ADMs) for use in Radiative Flux Estimates from the Advanced Baseline Imager (ABI)  
Xiaolei Niu, University of Maryland, College Park, MD; and R. Pinker
 P1.24Use of SEVIRI cloud properties to simulate radiative fluxes from GOES-R ABI  
R. T. Pinker, University of Maryland, College Park, MD; and R. Hollmann and H. Wang
 P1.25Effect of GOES-R image navigation and registration errors on atmospheric motion vectors  
Gary J. Jedlovec, NASA/MSFC/Short-Term Prediction Research and Transition (SPoRT) Center, Huntsville, AL
 P1.26GOES-13 End-to-End INR Performance Verification and Post Launch Testing  extended abstract
Christopher A. Carson, Boeing Space & Intelligence Systems, Las Cruces, NM; and J. L. Carr and C. Sayal
 P1.27The ABI Image and Navigation Registration  
Ken Ellis, ITT Space Systems Division, Fort Wayne, IN; and K. Gounder, P. Griffith, D. Igli, A. Kamel, J. Ogle, and V. Virgilio
 P1.28The ABI star sensing and star selection  extended abstract
Ken Ellis, ITT Space Systems Division, Fort Wayne, IN; and K. Gounder, P. Griffith, E. Hoffman, D. Igli, J. Ogle, and V. Virgilio
 P1.29ABI instrument performance simulation  
Ken Ellis, ITT Space Systems Division, Fort Wayne, IN; and R. D. Forkert, J. Witulski, and V. N. Virgilio
 P1.30GOES-R Proxy Data Management System  extended abstract
Tong Zhu, NOAA/NESDIS, Camp Springs, MD; and M. J. Kim, F. Weng, M. Goldberg, A. Huang, M. Sengupta, D. K. Zhou, and B. Ruston
 P1.31Simulation of GOES-R ABI Radiances for OSSE  extended abstract
Tong Zhu, NOAA/NESDIS, Camp Springs, MD; and F. Weng, M. Masutani, S. Lord, J. Woollen, Q. Liu, and S. A. Boukabara
 P1.32Multi-spectral precipitation estimation using Artificial Neural Networks  
Ali Behrangi, Center for Hydrometeorology and Remote Sensing (CHRS), Irvine, CA; and K. L. Hsu, S. Sorooshian, and R. Kuligowski
 P1.33Improving Nowcasting of convective storm development using MSG SEVIRI, MODIS, and GOES-12 imagery as risk reduction for GOES-R ABI  
Kristopher M. Bedka, CIMSS/Univ. of Wisconsin, Madison, WI; and W. F. Feltz, J. Sieglaff, and J. R. Mecikalski
 P1.34GOES Winter Precipitation efficiency algorithm  
Robert M. Rabin, NOAA/NSSL, Norman, OK; and J. Hanna
 P1.35Proxy ABI datasets relevant for fire detection that are derived from MODIS data  extended abstract
Scott S. Lindstrom, CIMSS/Univ. of Wisconsin, Madison, WI; and C. C. Schmidt, E. M. Prins, J. Hoffman, J. Brunner, and T. J. Schmit
 P1.36Validating GOES active fire detection product using ASTER and ETM+  
Wilfrid Schroeder, University of Maryland, College Park, MD; and I. Csiszar, E. M. Prins, C. C. Schmidt, and M. G. Ruminski
 P1.37GOES-R ABI fire detection and monitoring development activities  
Christopher C. Schmidt, CIMSS/Univ. of Wisconsin, Madison, WI; and S. Lindstrom, J. Hoffman, J. Brunner, and E. M. Prins
 P1.38Quantifying uncertainties in fire size and temperature measured by GOES-R ABI  extended abstract
Manajit Sengupta, CIRA/Colorado State Univ., Fort Collins, CO; and L. Grasso, D. W. Hillger, R. Brummer, and M. DeMaria
 P1.39Quality Assessment of the GOES-R AWG Level 2 Product Processing System  
Lihang Zhou, Perot System, Fairfax, VA; and W. W. Wolf, S. Qu, P. Keehn, Q. Guo, S. Sampson, and M. D. Goldberg
 P1.40Trade-off studies on future GOES hyperspectral infrared sounding instrument  
Jinlong Li, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Li, T. J. Schmit, and J. J. Gurka
 P1.41Sounder options in the GOES-R era  
David Crain, ITT Space Systems Division, Fort Wayne, IN
 P1.42Hyperspectral infrared alone cloudy sounding algorithm development  
Elisabeth Weisz, Univ. of Wisconsin/CIMSS, Madison, WI; and J. Li, C. Y. Liu, D. K. Zhou, H. L. Huang, and M. Goldberg
 P1.43Improved GOES water vapor products over CONUS planning for GOES-R  extended abstract
Daniel Birkenheuer, NOAA/ESRL, Boulder, CO; and S. I. Gutman, S. Sahm, and K. Holub
 P1.44Aerosol size density characterization for single scattering using Artificial Neural Network  extended abstract
Andres Bonilla, Univ. of Puerto Rico, Mayaguez, PR; and H. Parsiani
 P1.45AER general 1D-Var retrieval infrastructure: transition from research to operations  
Richard J. Lynch, AER, Inc., Lexington, MA; and J. L. Moncet, A. Lipton, D. Hogan, R. d'Entremont, and H. Snell
 P1.46The GOES-R User Readiness Group, engaging and preparing the users for GOES-R data  
Kenneth H. Lowe, Noblis, Falls Church, VA; and M. Goldberg and J. Daniels
 P1.47Overview of GOES-R Analysis Facility for Instrument Impacts on Requirements (GRAFIIR) Planned Activities and Recent Progress  
Allen Huang, CIMSS/Univ. of Wisconsin, Madison, WI; and M. Goldberg
 P1.48GOES-R Algorithm Working Group: Space weather team update  
S. Hill, NOAA/NWS, Boulder, CO; and H. J. Singer, T. Onsager, R. Viereck, D. Biesecker, C. C. Balch, D. C. Wilkinson, M. Shouldis, P. Loto'aniu, J. Gannon, and L. Mayer
 P1.49Space weather products from the GOES-R magnetometer  
Paul T.M. Loto'aniu, NOAA/NWS, Boulder, CO; and H. J. Singer
 P1.50Improving space weather forecasts using solar coronagraph data  
Simon P. Plunkett, NRL, Washington, DC; and A. Vourlidas, D. R. McMullin, K. Battams, and R. C. Colaninno
 P1.51GOES-N EUVS observations during post-launch testing  
Douglas J. Strickland, Computational Physics, Inc., Springfield, VA; and J. S. Evans, W. K. Woo, D. R. McMullin, S. P. Plunkett, and R. Viereck
 P1.52GOES-N EUVS field of view sensitivities and modeling  
Donald R. McMullin, Praxis, Inc., Alexandria, VA; and D. J. Strickland, J. S. Evans, W. K. Woo, S. P. Plunkett, and R. Viereck
 P1.53Enhancing the Geostationary Lightning Mapper for improved performance  extended abstract
David B. Johnson, NCAR, Boulder, CO
 P1.54A microwave sounder for geostationary orbit  
Bjorn H. Lambrigtsen, JPL and California Institute of Technology, Pasadena, CA
 P1.55Activities of GOES-R land applications working group team  
Dan Tarpley, NOAA/NESDIS, Camp Springs, MD; and Y. Yu, P. Romanov, E. Prins, K. Gallo, F. Kogan, H. Xu, M. K. RamaVarma Raja, K. Y. Vinnikov, M. Goldberg, S. Qiu, and J. L. Privette
 P1.56Seasonal, Diurnal, and Weather Related Variations of Clear Sky Land Surface Temperature: A Statistical Assessment  
Konstantin Y. Vinnikov, University of Maryland, College Park, MD; and Y. Yu, M. K. Rama Varma Raja, J. D. Tarpley, and M. D. Goldberg
 P1.57Enhanced Observation Capability of the New Generation Geostationary Satellites for Better Vegetation Monitoring  
Peter Romanov, University of Maryland and NOAA/NESDIS, Camp Springs, MD; and H. Xu and D. Tarpley
 P1.58Comparison of GOES cloud classification algorithms employing explicit and implicit physics  extended abstract
Richard L. Bankert, NRL, Monterey, CA; and C. Mitrescu, S. D. Miller, and R. H. Wade
 P1.59Estimation of Sea and Lake Ice Characteristics with GOES-R ABI  extended abstract
Xuanji Wang, CIMSS/Univ. of Wisconsin, Madison, WI; and J. R. Key, Y. Liu, and W. Straka
 P1.60On the use of geostationary satellites for remote sensing in the high latitudes  
Yinghui Liu, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Key and X. Wang
 P1.61Operational GOES-SST and MSG-SEVIRI-SST products for GOES-R risk reduction  
Eileen Maria Maturi, NOAA/NESDIS, Camp Springs, MD; and A. Harris, J. Mittaz, and J. Sapper
 P1.62Overview of the NESDIS heritage AVHRR Sea Surface Temperature Calibration/Validation system  
Dilkushi De Alwis, NOAA/NESDIS and CIRA/Colorado State Univ., Camp Springs, MD; and A. Ignatov, J. Sapper, P. Dash, W. G. Pichel, Y. Kihai, and X. Li
 P1.63Validation of Real-Time GOES Products Using GLAS and CALIPSO Data  
Louis Nguyen, NASA/LaRC, Hampton, VA; and P. Minnis, D. A. Spangenberg, J. K. Ayers, R. Palikonda, M. L. Nordeen, and T. L. Chee
 P1.64The Manual Cloud Filtering of GOES-satellite data through combined use of satellite and ground measurements  
M. K. Rama Varma Raja, I. M. Systems Group, Inc. and NOAA/NESDIS/STAR, Camp Springs, MD; and Y. Yu, D. Tarpley, H. Xu, and K. Y. Vinnikov
 P1.65Status update from the GOES-R Hydrology Algorithm Team  
Robert J. Kuligowski, NOAA/NESDIS, Camp Springs, MD
P1.66PAPER WITHDRAWN  
 P1.67Possible impacts of GOES-R temporal resolution on tropical cyclone intensity estimates  
John L. Beven II, NOAA/AOML/NHC/TPC, Miami, FL; and C. S. Velden and T. L. Olander
 P1.68Verifying large-scale, high-resolution simulations of clouds for GOES-R activities  
Thomas Greenwald, Univ. of Wisconsin, Madison, WI; and J. Sieglaff, Y. K. Lee, H. L. Huang, J. Otkin, E. Olson, and M. Gunshor
 P1.69Retrieving cloud properties for multilayered clouds using simulated GOES-R data  
Fu-Lung Chang, National Institute of Aerospace, Hampton, VA; and P. Minnis, B. Lin, R. Palikonda, M. Khaiyer, S. Sun-Mack, and P. Yang
 P1.70Nighttime retrieval of cloud microphysical properties for GOES-R  extended abstract
Patrick W. Heck, CIMSS/Univ. of Wisconsin, Madison, WI; and P. Minnis, R. Palikonda, C. R. Yost, F. L. Chang, and A. K. Heidinger
 P1.71Nearcasting convective destabilization using objective tools which optimize the impact of sequences of GOES moisture products  
Ralph A. Petersen, CIMSS/University of Wisconsin, Madison, WI; and R. M. Aune
 P1.72Transitioning GOES-based nowcasting capability into the GOES-R era  
Brian L. Vant-Hull, NOAA/CREST CCNY, New York, NY; and M. Ba, R. Rabin, D. S. Mahani, R. J. Kuligowski, A. Gruber, and S. B. Smith
 P1.73Nowcasting of Thunderstorms from GOES Infrared and Visible Imagery  extended abstract
Valliappa Lakshmanan, CIMMS/Univ. of Oklahoma, NOAA/NSSL, Norman, OK; and R. M. Rabin
 P1.74Mission Availability Improvements for GOES-R  extended abstract
Larry E. Urner, Northrop Grumman, Redondo Beach, CA; and J. Castellon, M. Hanson, and S. Sawyer
 P1.75Determination of aircraft icing threat from satellite  
William L. Smith Jr., NASA/LaRC, Hampton, VA; and P. Minnis and D. A. Spangenberg
 P1.76Cloud statistics over agricultural and mixed forest areas  
Valentine Anantharaj, Mississippi State University, Mississippi State, MS; and U. S. Nair, D. Berendes, S. Asefi, and J. G. Fairman
 P1.77Comparison of atmospheric profiles from hyperspectral and multispectral IR radiances on depicting hurricane thermodynamic structures  
Hong Qiu, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Li, E. Weisz, and C. Y. Liu
 P1.78Development of severe weather products for the GOES-R Advanced Baseline Imager  
Daniel T. Lindsey, NOAA/NESDIS, Fort Collins, CO; and D. W. Hillger and L. Grasso
 P1.79Algorithm and Software Development of Atmospheric Motion Vector Products for the GOES-R ABI  
Jaime M. Daniels, NOAA/NESDIS, Camp Springs, MD; and W. Bresky, C. Velden, I. Genkova, S. Wanzong, and D. Santek
 P1.80An enhanced IDEA product with GOES AOD  
Hai Zhang, JCET/Univ. of Maryland, Baltimore, MD; and R. M. Hoff, S. Kondragunta, I. Laszlo, and A. Wimmers
 P1.81An initial assessment of the GOES Microburst Windspeed Potential Index  extended abstract
Kenneth L. Pryor, NOAA/NESDIS, Camp Springs, MD
 P1.82GOES-R Applications for the Assessment of Aviation Hazards  
Kenneth L. Pryor, NOAA/NESDIS, Camp Springs, MD; and W. Feltz, J. R. Mecikalski, M. Pavolonis, and W. L. Smith
 P1.83Application of Multi-Spectral Data to Space Shuttle Landing Operations  
Doris A. Hood, NWS Spaceflight Meteorology Group, Houston, TX; and T. Garner and T. Oram
 P1.84Weather Information and Decision Systems (WxIDS): Looking to the future of data processing and decision support systems  
Dylan Powell, Lockheed Martin, Greenbelt, MD; and J. A. Dutton, J. Ross, J. Sroga, C. F. Chang, R. Pickens, S. Pitter, K. Leesman, G. Young, P. G. Knight, N. L. Seaman, J. Nese, G. Haselfeld, R. Wessels, and M. Dhondt
 P1.85Development of simulated GOES products for the GFS and the NAM  
Hui-ya Chuang, NOAA/NWS/NCEP, Camp Springs, MD; and B. Ferrier
 P1.86Current GOES Sounder applications and future needs  
Jun Li, Univ. of Wisconsin, Madison, WI; and T. J. Schmit, J. J. Gurka, J. Daniels, M. D. Goldberg, and P. Menzel
 P1.87GOES-R ABI proxy data set generation at CIMSS  
Mathew M. Gunshor, CIMSS/Univ. of Wisconsin, Madison, WI; and E. Olson, J. Sieglaff, T. Greenwald, A. Huang, and J. A. Otkin
 P1.88GOES-R mesoscale product development  extended abstract
Renate Brummer, CIRA/Colorado State Univ., Fort Collins, CO; and M. DeMaria, J. A. Knaff, B. H. Connell, J. F. Dostalek, and D. Zupanski
 P1.89GOES-R/ABI legacy profile algorithm evaluation with MSG/SEVIRI  
Xin Jin, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Li, T. J. Schmit, J. Li, E. Weisz, and Z. Li
 P1.90High spatial and temporal resolution retrievals obtained from the combination of GOES-R multispectral ABI and joint polar satellite ultraspectral radiances  
William Smith Sr., Hampton Univ., Hampton, VA; and S. Kireev, D. Zhou, A. M. Larar, X. Liu, M. D. Goldberg, and E. M. Maturi
 P1.91Real-time display of simulated GOES-R experimental products  
Donald W. Hillger, NOAA/NEDSIS/StAR/RAMM Branch, Fort Collins, CO CO
 P1.92Recasting HYDRA into the next generation of McIDAS  
Thomas D. Rink, CIMSS/Univ. of Wisconsin, Madison, WI; and T. Whittaker, T. H. Achtor, B. Flynn, G. Dengel, and K. Baggett
 P1.93Looking Ahead to GOES-R Space Weather Data Archive, Access, and User Services  
Daniel C. Wilkinson, NOAA/NESDIS, Boulder, CO; and W. F. Denig
 P1.94Geostationary Operational Environmental Satellites (GOES) in support of NOAA's Climate Reference Network (CRN)  extended abstract
Debra Braun, NOAA/NESDIS/NCDC, Asheville, NC
 P1.95Remapping GOES Imager Instrument Data for South American Operations, Implementing the XGOHI System  extended abstract
Shahram Tehranian, Nortel Government Solutions, Lanham, MD; and J. L. Carr, S. Yang, H. Madani, S. Vasanth, K. Mckenzie, T. J. Schmit, A. Swaroop, and R. DiRosario
 P1.96GOES-10 @ 60 West a Wisconsin perspective  extended abstract
Timothy J. Schmit, NOAA/NESDIS/ORA, Madison, WI; and J. Li, J. P. Nelson, A. J. Schreiner, G. S. Wade, and Z. Li
 P1.97Deep convection defined by split window  
Toshiro Inoue, MRI, Tsukuba, Ibaraki, Japan
 P1.98GOES-R 2008 User Conference Poster Abstract for the NOAA CLASS Project  
Robert Rank, NOAA/NESDIS, Suitland, MD; and F. Vizbulis

Wednesday, 23 January 2008: 2:30 PM-4:00 PM, Exhibit Hall B

* - Indicates paper has been withdrawn from meeting

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