|  | 307 | Prototyping GOES-R ABI Hybrid SST Retrieval Algorithm with MSG/SEVIRI: Combining Regression and Radiative Transfer Model Approaches
Boris Petrenko, NOAA/NESDIS/STAR, IMSG Inc, Camp Springs, MD; and A. Ignatov, N. Shabanov, Y. Kihai, and F. Xu |
| | 308 | Model-derived proxy ABI radiance datasets used for GOES-R research and demonstration activities
Jason A. Otkin, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Sieglaff, T. Greenwald, and A. Huang |
| | 309 | Merits of the GOES-R ABI 13.3-μm Data for Inferring Upper-Troposphere Cloud Top Locations in the Presence of Multilayered Clouds
Fu-Lung Chang, SSAI, Hampton, VA; and P. Minnis, J. K. Ayers, M. Khaiyer, L. Nguyen, R. Palikonda, and D. A. Spangenberg |
| | 310 | A Weather Event Simulator (WES) for the GOES-R Advanced Baseline Imager (ABI)
Timothy J. Schmit, NOAA/NESDIS/STAR, Madison, WI; and K. Bah, J. Gerth, M. Cronce, J. Otkin, and J. Sieglaff |
| | 311 | A novel approach for improving the lightning detection efficiency of the GOES-R Geostationary Lightning Mapper
Yuanming Suo, University of Alabama in Huntsville, Huntsville, AL; and L. D. Carey |
| | 312 | Hyperspectral microwave atmospheric sounding from geostationary orbit: The GeoMAS concept
William J. Blackwell, MIT Lincoln Laboratory, Lexington, MA; and L. J. Bickmeier, R. V. Leslie, C. A. Upham, and C. Surussavadee |
| | 313 | GeoSTAR - A hurricane observatory
Bjorn H. Lambrigtsen, JPL and California Institute of Technology, Pasadena, CA |
| | 314 | Application of GOES and MSG data in NWP models
Tong Zhu, CIRA/NOAA/NESDIS/STAR/Joint Center for Satellite Data Assimilation, College Park, MD; and F. Weng, J. Derber, R. L. Vogel, G. Krasowski, and M. Goldberg |
| | 315 | GOES-R mesoscale product development at CIRA and STAR/RAMMB
Renate Brummer, CIRA/Colorado State Univ., Fort Collins, CO; and C. Combs, B. H. Connell, M. DeMaria, R. T. DeMaria, J. F. Dostalek, L. Grasso, D. W. Hillger, J. Knaff, D. Zupanski, and D. T. Lindsey |
| | 316 | Development of a statistical hail prediction product for the GOES-R proving ground
Daniel T. Lindsey, NOAA/NESDIS, Fort Collins, CO; and C. W. Siewert |
| | 317 | Forward morphing of passive microwave derived precipitation field with adjusted intensity from GOES information
Ali Behrangi, University of California, Irvine, Irvine, CA; and K. Hsu, B. Imam, and S. Sorooshian |
| | 318 | A Nested Tracking Approach for Reducing the Slow Speed Bias Associated with Atmospheric Motion Vectors (AMVs)
Jaime M. Daniels, NOAA/NESDIS, Camp Springs, MD; and W. Bresky |
| | 319 | Mountain wave detection as an aviation hazard awareness tool for GOES-R
Anthony Wimmers, CIMSS/Univ. of Wisconsin, Madison, WI; and W. F. Feltz |
| | 320 | High impact weather study using advanced IR sounding data
Jinlong Li, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Li, H. Liu, and T. J. Schmit |
| | 321 | A new ultra high resolution sea surface temperature analysis from GOES-R ABI and NPOESS VIIRS 
Eileen Maria Maturi, NOAA/NESDIS/STAR, Camp Springs, MD; and A. Harris and J. Mittaz |
| | 322 | Quality Assurance (QA) in the GOES-R AWG Product Processing System
Zhaohui Cheng, NOAA/NESDIS, Camp Springs, MD; and W. W. Wolf, S. Qiu, S. Sampson, X. Liu, and M. Goldberg |
| | 323 | Intercalibration activities at CIMSS in preparation for the GOES-R era
Mathew M. Gunshor, CIMSS/Univ. of Wisconsin, Madison, WI; and D. Tobin, T. J. Schmit, and W. P. Menzel |
| | 324 | Using McIDAS-V in preparation for the GOES-R ABI
Kaba Bah, CIMSS/Univ. of Wisconsin, Madison, WI; and T. J. Schmit, T. Achtor, T. Rink, W. Wolf, J. Otkin, J. Sieglaff, and J. Feltz |
| | 325 | McIDAS-V – data analysis and visualization development for the NPP/NPOESS and GOES-R programs
Thomas H. Achtor, CIMSS/Univ. of Wisconsin, Madison, WI; and T. D. Rink and T. M. Whittaker |
| | 380 | Performance modeling of the GOES R-series ground segment product generation function
Julie McNeil, NOAA/NESDIS, Greenbelt, MD; and A. J. Ryberg Jr. and J. Gurka |