Poster Session - GOES-R

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Wednesday, 20 January 2010: 2:30 PM-4:00 PM
Host: 6th Annual Symposium on Future National Operational Environmental Satellite Systems-NPOESS and GOES-R
Chair:  Dick Reynolds, Short and Associates, Annapolis, MD

Papers:
 
301
GOES-R AWG product processing system framework: implementing algorithms
Walter W. Wolf, NOAA/NESDIS/STAR, Camp Springs, MD; and S. Sampson, Z. Cheng, P. Keehn, Q. Guo, S. Qiu, and M. Goldberg

 
303
Convective Initiation Algorithm for GOES-R
Wayne M. MacKenzie Jr., University of Alabama in Huntsville, Huntsville, AL; and J. R. Walker and J. R. Mecikalski

 
304
An algorithm for deriving absorbed solar radiation at the surface from GOES-R
Hye-Yun Kim, IMSG at NOAA/NESDIS, Camp Springs, MD; and I. Laszlo and H. Liu

 
305
GOES-R ABI Fire Detection and Characterization Algorithm Assessment Using MODIS and ASTER Data
Wilfrid Schroeder, University of Maryland, College Park, MD; and C. C. Schmidt, S. S. Lindstrom, I. Csiszar, and J. P. Hoffman

 
306
Integrated cloud mask and quality control for GOES-R ABI SST: prototyping with MSG/SEVIRI
Nikolay Shabanov, NOAA/NESDIS, IMSG Inc, Camp Springs, MD; and A. Ignatov, B. Petrenko, Y. Kihai, and A. Heidinger

Handout (2.1 MB)

 
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

 
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

Handout (75.1 kB)

 
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

Handout (2.9 MB)

 
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

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