| | Cochairs: James Gurka, NESDIS GOES-R Program Office, Greenbelt, MD; Timothy J. Schmit, NOAA/NESDIS/ORA, Madison, WI; Frank Hinnant, NPOESS/IPO, Silver Spring, MD; Jane Whitcomb, NPOESS Integrated Program Office, Silver Spring, MD
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|  | JP2.7 | Simulated GOES-R vegetation health product system
Wei Guo, IMSG, Camp Springs, MD; and F. Kogan, Y. Yu, Y. Tian, D. Tarpley, L. Jiang, and P. Romanov |
| | JP2.8 | Synthetic GOES-R imagery of fires at 3.9 µm
Louie Grasso, CIRA/Colorado State Univ., Fort Collins, CO; and M. Sengupta, R. Brummer, R. DeMaria, and D. W. Hillger |
| | JP2.9 | Improving fire detection: Current GOES to GOES-R 
Manajit Sengupta, CIRA/Colorado State Univ., Fort Collins, CO; and L. Grasso, R. Brummer, and D. W. Hillger |
| | JP2.10 | Retrieving Upper and Lower Cloud Layer Properties Using the GOES-12 Imagery Data: Addressing Problems in Satellite Retrievals of Cloud Layers
Fu-Lung Chang, National Institute of Aerospace, Hampton, VA; and P. Minnis, B. Lin, R. Palikonda, and D. A. Spangenberg |
| | JP2.11 | Comparison of the GOES-R cloud Algorithm Working Group's daytime cloud optical property products to those from MODIS, AVHRR and VIIRS
William Straka III, CIMSS/Univ. of Wisconsin, Madison, WI; and A. Walther and A. K. Heidinger |
| | JP2.12 | The introduction and evaluation of a prototype GOES-R fog/low stratus algorithm using SEVIRI, CALIPSO and surface observations
Corey G. Calvert, CIMSS/Univ. of Wisconsin, Madison, WI; and M. J. Pavolonis |
| | JP2.13 | An analysis of the seasonal and diurnal variation of total precipitable water (TPW) from satellite and ground-based instruments over the ARM-SGP site
Sarah Bedka, CIMSS/Univ. of Wisconsin, Madison, WI; and J. Cychosz, M. Evansen, R. Knuteson, H. E. Revercomb, D. Tobin, and D. D. Turner |
| | JP2.14 | Status update from the GOES-R Hydrology Algorithm Team
Robert J. Kuligowski, NOAA / NESDIS, Camp Springs, MD |
| | JP2.15 | Prototyping SST Retrievals from GOES-R ABI with MSG SEVIRI data
Nikolay Shabanov, NOAA/NESDIS, IMSG Inc, Camp Springs, MD; and A. Ignatov, B. Petrenko, Y. Kihai, X. Liang, W. Guo, F. Xu, P. Dash, M. Goldberg, and J. Sapper |
| | JP2.16 | Sea and lake ice characteristics from GOES-R ABI
Xuanji Wang, CIMSS/Univ. of Wisconsin, Madison, WI; and Y. Liu and J. Key |
| | JP2.17 | An automated approach for determining sea ice concentration for the future GOES-R ABI sensor
Marouane Temimi, NOAA-CREST, New York, NY; and H. Ghedira, R. Khanbilvardi, and P. Romanov |
| | JP2.18 | Snow cover mapping technique for GOES-R ABI
Peter Romanov, Cooperative Institute for Climate Studies, College Park, MD; and C. Kongoli |
| | JP2.19 | Implementation of the GOES-R AWG product processing system framework
Walter Wolf, NOAA/NESDIS, Camp Springs, MD; and L. Zhou, P. Keehn, Q. Guo, S. Sampson, S. Qiu, and M. Goldberg |
| | JP2.20 | Quality Assessment of the GOES-R AWG Level 2 Product Processing System
Lihang Zhou, Perot System, Fairfax, VA; and W. Wolf, Q. Shuang, W. Wang, P. Keehn, Q. Guo, S. Sampson, and M. D. Goldberg |
| | JP2.21 | GeoSTAR—A “Geostationary AMSU”
Bjorn H. Lambrigtsen, JPL and California Institute of Technology, Pasadena, CA; and T. Gaier and L. Herrell |
| | JP2.22 | Mesoscale sounding capabilities with GOES-R and beyond
William Smith Sr., Hampton Univ., Hampton, VA; and H. Revercomb and J. Tian |
| | JP2.23 | Evaluation of GOES-R and NPOESS instrument in Joint OSSEs
Lars Peter Riishojgaard, JCSDA, Greenbelt, MD; and F. Weng, M. Masutani, T. Zhu, H. Sun, C. M. Hill, V. Anantharaj, P. J. Fitzpatrick, R. M. Errico, S. J. Lord, Y. Han, J. Woollen, D. Groff, and T. J. Kleespies |