|  | P1.1 | ABI system overview
Paul Griffith, ITT Space Systems Division, Fort Wayne, IN |
| | P1.2 | ABI scan scenario capabilities
David Crain, ITT Space Systems Division, Fort Wayne, IN; and P. Griffith |
| | P1.3 | Candidate approaches for the real-time generation of cloud properties from GOES-R ABI
Andrew K. Heidinger, NOAA/NESDIS, Madison, WI |
| | P1.4 | GOES-R architecture framework
John W. Linn III, Noblis, Falls Church, VA; and L. Shipley |
| | P1.5 | Development 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 |
| | P1.6 | GOES-R Downlink Services for Users 
John Schimm, Northrop Grumman, Redondo Beach, CA; and J. Castellon, L. Kincaid, and L. E. Urner |
| | P1.7 | The GOES ABI ground processing development system
Jon Ormiston, ITT Space Systems Division, Fort Wayne, IN; and J. Blume, J. Ring, and J. Yoder |
| | P1.8 | Development of the GOES-R ABI Outgoing Longwave Radiation product
Hai-Tien Lee, University of Maryland, College Park, MD; and I. Laszlo and A. Gruber |
| | P1.9 | Applying 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 |
| | P1.10 | Development and validation of a BRDF model for ice mapping for the future GOES-R Advanced Baseline Imager (ABI) using Artificial Neural Network
Hosni Ghedira, NOAA-CREST, New York, NY; and M. Temimi, R. Nazari, P. Romanov, and R. Khanbilvardi |
| | P1.11 | GOES-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 |
| | P1.12 | Validation of a GOES-R Broadband Shortwave Surface Transmission and TOA Albedo LUT method
Fred G. Rose, SSAI, Hampton, VA; and Q. Fu, I. Laszlo, and T. P. Charlock |
| | P1.13 | Validation 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
XingMing Liang, NOAA/NESDIS, Camp Springs, MD; and A. Ignatov, Y. Kihai, A. K. Heidinger, Y. Han, and Y. Chen |
| | P1.14 | Examining the MTSAT-1R solar channel calibration
Hyoung-wook Chun, Seoul National University, Seoul, South Korea; and B. J. Sohn |
| | P1.15 | GOES-R ABI calibration approach
David S. Smith, ITT Space Systems Division, Fort Wayne, IN |
| | P1.16 | The Global Space-based Inter-Calibration System (GSICS): A status report
Xiangqian Wu, NOAA/NESDIS, Camp Springs, MD; and M. Goldberg |
| | P1.17 | Inter-calibration of geostationary imagers with MetOP/IASI hyperspectral measurements
Likun Wang, QSS Group Inc, Camp Spring, MD; and C. Cao |
| | P1.18 | Generating synthetic infrared GOES-R ABI Images with AVHRR and GOES images
William J. Emery, Univ of Colorado, Boulder, CO; and C. Roessler |
| | P1.19 | Synthetic GOES-R Imagery Development and Uses
Lewis Grasso, CIRA/Colorado State Univ., Fort Collins, CO; and M. Sengupta and D. T. Lindsey |
| | P1.20 | Large-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 |
| | P1.21 | New 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 |
| | P1.22 | Preliminary study of lunar calibration for geostationary imagers
Seiichiro Kigawa, Japan Meteorological Agency, Kiyose-shi, Tokyo, Japan; and K. Miyaoka |
| | P1.23 | Synthesis 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 |
| | P1.24 | Use 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 |
| | P1.25 | Effect 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 |
| | P1.26 | GOES-13 End-to-End INR Performance Verification and Post Launch Testing
Christopher A. Carson, Boeing Space & Intelligence Systems, Las Cruces, NM; and J. L. Carr and C. Sayal |
| | P1.27 | The 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 |
| | P1.28 | The ABI star sensing and star selection
Ken Ellis, ITT Space Systems Division, Fort Wayne, IN; and K. Gounder, P. Griffith, E. Hoffman, D. Igli, J. Ogle, and V. Virgilio |
| | P1.29 | ABI instrument performance simulation
Ken Ellis, ITT Space Systems Division, Fort Wayne, IN; and R. D. Forkert, J. Witulski, and V. N. Virgilio |
| | P1.30 | GOES-R Proxy Data Management System
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 |
| | P1.31 | Simulation of GOES-R ABI Radiances for OSSE
Tong Zhu, NOAA/NESDIS, Camp Springs, MD; and F. Weng, M. Masutani, S. Lord, J. Woollen, Q. Liu, and S. A. Boukabara |
| | P1.32 | Multi-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 |
| | P1.33 | Improving 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 |
| | P1.34 | GOES Winter Precipitation efficiency algorithm
Robert M. Rabin, NOAA/NSSL, Norman, OK; and J. Hanna |
| | P1.35 | Proxy ABI datasets relevant for fire detection that are derived from MODIS data
Scott S. Lindstrom, CIMSS/Univ. of Wisconsin, Madison, WI; and C. C. Schmidt, E. M. Prins, J. Hoffman, J. Brunner, and T. J. Schmit |
| | P1.36 | Validating 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 |
| | P1.37 | GOES-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 |
| | P1.38 | Quantifying uncertainties in fire size and temperature measured by GOES-R ABI
Manajit Sengupta, CIRA/Colorado State Univ., Fort Collins, CO; and L. Grasso, D. W. Hillger, R. Brummer, and M. DeMaria |
| | P1.39 | Quality 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 |
| | P1.40 | Trade-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 |
| | P1.41 | Sounder options in the GOES-R era
David Crain, ITT Space Systems Division, Fort Wayne, IN |
| | P1.42 | Hyperspectral 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 |
| | P1.43 | Improved GOES water vapor products over CONUS – planning for GOES-R
Daniel Birkenheuer, NOAA/ESRL, Boulder, CO; and S. I. Gutman, S. Sahm, and K. Holub |
| | P1.44 | Aerosol size density characterization for single scattering using Artificial Neural Network
Andres Bonilla, Univ. of Puerto Rico, Mayaguez, PR; and H. Parsiani |
| | P1.45 | AER 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 |
| | P1.46 | The 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 |
| | P1.47 | Overview 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 |
| | P1.48 | GOES-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 |
| | P1.49 | Space weather products from the GOES-R magnetometer
Paul T.M. Loto'aniu, NOAA/NWS, Boulder, CO; and H. J. Singer |
| | P1.50 | Improving 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 |
| | P1.51 | GOES-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 |
| | P1.52 | GOES-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 |
| | P1.53 | Enhancing the Geostationary Lightning Mapper for improved performance
David B. Johnson, NCAR, Boulder, CO |
| | P1.54 | A microwave sounder for geostationary orbit
Bjorn H. Lambrigtsen, JPL and California Institute of Technology, Pasadena, CA |
| | P1.55 | Activities 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 |
| | P1.56 | Seasonal, 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 |
| | P1.57 | Enhanced 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 |
| | P1.58 | Comparison of GOES cloud classification algorithms employing explicit and implicit physics
Richard L. Bankert, NRL, Monterey, CA; and C. Mitrescu, S. D. Miller, and R. H. Wade |
| | P1.59 | Estimation of Sea and Lake Ice Characteristics with GOES-R ABI
Xuanji Wang, CIMSS/Univ. of Wisconsin, Madison, WI; and J. R. Key, Y. Liu, and W. Straka |
| | P1.60 | On 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 |
| | P1.61 | Operational 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 |
| | P1.62 | Overview 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 |
| | P1.63 | Validation 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 |
| | P1.64 | The 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 |
| | P1.65 | Status update from the GOES-R Hydrology Algorithm Team
Robert J. Kuligowski, NOAA/NESDIS, Camp Springs, MD |
| | P1.66 | PAPER WITHDRAWN
|
| | P1.67 | Possible 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 |
| | P1.68 | Verifying 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 |
| | P1.69 | Retrieving 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 |
| | P1.70 | Nighttime retrieval of cloud microphysical properties for GOES-R
Patrick W. Heck, CIMSS/Univ. of Wisconsin, Madison, WI; and P. Minnis, R. Palikonda, C. R. Yost, F. L. Chang, and A. K. Heidinger |
| | P1.71 | Nearcasting 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 |
| | P1.72 | Transitioning 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 |
| | P1.73 | Nowcasting of Thunderstorms from GOES Infrared and Visible Imagery
Valliappa Lakshmanan, CIMMS/Univ. of Oklahoma, NOAA/NSSL, Norman, OK; and R. M. Rabin |
| | P1.74 | Mission Availability Improvements for GOES-R
Larry E. Urner, Northrop Grumman, Redondo Beach, CA; and J. Castellon, M. Hanson, and S. Sawyer |
| | P1.75 | Determination of aircraft icing threat from satellite
William L. Smith Jr., NASA/LaRC, Hampton, VA; and P. Minnis and D. A. Spangenberg |
| | P1.76 | Cloud 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 |
| | P1.77 | Comparison 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 |
| | P1.78 | Development 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 |
| | P1.79 | Algorithm 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 |
| | P1.80 | An 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 |
| | P1.81 | An initial assessment of the GOES Microburst Windspeed Potential Index
Kenneth L. Pryor, NOAA/NESDIS, Camp Springs, MD |
| | P1.82 | GOES-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 |
| | P1.83 | Application of Multi-Spectral Data to Space Shuttle Landing Operations
Doris A. Hood, NWS Spaceflight Meteorology Group, Houston, TX; and T. Garner and T. Oram |
| | P1.84 | Weather 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 |
| | P1.85 | Development of simulated GOES products for the GFS and the NAM
Hui-ya Chuang, NOAA/NWS/NCEP, Camp Springs, MD; and B. Ferrier |
| | P1.86 | Current 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 |
| | P1.87 | GOES-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 |
| | P1.88 | GOES-R mesoscale product development
Renate Brummer, CIRA/Colorado State Univ., Fort Collins, CO; and M. DeMaria, J. A. Knaff, B. H. Connell, J. F. Dostalek, and D. Zupanski |
| | P1.89 | GOES-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 |
| | P1.90 | High 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 |
| | P1.91 | Real-time display of simulated GOES-R experimental products
Donald W. Hillger, NOAA/NEDSIS/StAR/RAMM Branch, Fort Collins, CO CO |
| | P1.92 | Recasting 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 |
| | P1.93 | Looking Ahead to GOES-R Space Weather Data Archive, Access, and User Services
Daniel C. Wilkinson, NOAA/NESDIS, Boulder, CO; and W. F. Denig |
| | P1.94 | Geostationary Operational Environmental Satellites (GOES) in support of NOAA's Climate Reference Network (CRN)
Debra Braun, NOAA/NESDIS/NCDC, Asheville, NC |
| | P1.95 | Remapping GOES Imager Instrument Data for South American Operations, Implementing the XGOHI System
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 |
| | P1.96 | GOES-10 @ 60 West – a Wisconsin perspective
Timothy J. Schmit, NOAA/NESDIS/ORA, Madison, WI; and J. Li, J. P. Nelson, A. J. Schreiner, G. S. Wade, and Z. Li |
| | P1.97 | Deep convection defined by split window
Toshiro Inoue, MRI, Tsukuba, Ibaraki, Japan |
| | P1.98 | GOES-R 2008 User Conference Poster Abstract for the NOAA CLASS Project
Robert Rank, NOAA/NESDIS, Suitland, MD; and F. Vizbulis |