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

 
302
Validation of Community Radiative Transfer Model through hyperspectral Infrared brightness temperature comparison over thin cirrus cloud region
Yong-Keun Lee, CIMSS/Univ. of Wisconsin, Madison, WI; and T. Greenwald and A. Huang

 
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)

 
307
Prototyping GOES-R ABI Hybrid SST Retrieval Algorithm with MSG/SEVIRI: Combining Regression and Radiative Transfer Model Approaches

 
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

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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