We are working to migrate this publications database, and the current listing does not reflect the most recent publications available. Thank you for your patience, and please reach out to library@ssec.wisc.edu with any questions.


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Results: Found 839 records (displaying records 76 through 100)

76. Calvert, C. G. and Pavolonis, M. J.. Introduction of a day/night, object-based quantitative fog/low cloud detection and thickness algorithm for GOES-R. Washington, DC, American Geophysical Union, 2010, Abstract A13A-0186. 

77. Calvert, Corey and Pavolonis, Mchael. Introduction of a day/night, object-based, quantitative fog/low cloud detection algorithm for GOES-R. Munich, Germany, European Geosciences Union (EGU), 2011, Abstract 3718. 
Abstract Document Link to Abstract

78. Calvert, Corey and Pavolonis, Michael. A quantitative fog/low stratus detection algorithm for GOES-R. Raleigh, NC, National Weather Association, 2012, Abstract F17.3. 

79. Calvert, Corey G. and Pavolonis, M. J.. The introduction and evaluation of a prototype GOES-R gob/low stratus algorithm using SEVIRI, CALIPSO and surface observations. Boston, MA, American Meteorological Society, 2009, Abstract JP2.12. 

80. Calvert, Corey G. and Pavolonis, M. J.. A quantitative fog/low stratus detection algorithm for GOES-R. Boston, MA, American Meteorological Society, 2012, Abstract 310. 

81. Calvert, Corey G.; Pavolonis, M. J.; Hubbard, S.; Gravelle, C. M. and Lindstrom, S. S.. The GOES-R/JPSS approach for identifying hazardous low clouds: Overview and operational impacts. Boston, MA, American Meteorological Society, 2016, Abstract 8.4. 

82. Calvert, Corey G.; Pavolonis, Michael J. and Heidinger, Andrew K.. Evaluation of the GOES-R cloud algorithms using SEVIRI and CALIPSO data. Darmstadt, Germany, European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), 2007, poster presentation. 
PDF Document Link to PDF

83. Calvert, Corey; Pavolonis, Michael; Lindstrom, Scott; Gravelle, Chad and Terborg, Amanda. The GOES-R/JPSS approach for identifying hazardous low clouds: Overview and operational impacts. Munich, Germany, European Geosciences Union (EGU), 2017, Abstract 19378. 
Abstract Document Link to Abstract

84. Cao, Changyong; Shirley, E.; Datla, R.; Rice, J.; Johnson, C.; Brown, S.; Lykke, K.; Fraser, J.; Weinreb, M.; Clarke, J.; Young, D. F.; Wielicki, B. A.; Xiong, J.; Thome, K. J.; Tobin, D.; Chesters, D.; Pfarr, B. B.; Goldberg, M. and Goodman, S.. Ensuring the SI traceability of satellite measurements from the next generation geostationary imager GOES-R/ABI. Boston, MA, American Meteorological Society (AMS), 2011, Abstract 601. 

85. Carey, Lawrence; Feltz, Wayne; Bedka, Kristopher and Petersen, Walter. Integrated GOES-R GLM/ABI approached for the detection and forecasting of Convectively Induced Turbulence (CIT). US Department of Commerce, National Oceanic And Atmospheric Administration (NOAA), 2011, PowerPoint presentation. 

86. Chahine, Moustafa T.; Pagano, Thomas S.; Aumann, Hartmut H.; Atlas, Robert; Barnet, Christopher; Blaisdell, John; Chen, Luke; Divakarla, Murty; Fetzer, Eric J.; Goldberg, Mitch; Gautier, Catherine; Granger, Stephanie; Hannon, Scott; Irion, Fredrick W.; Kaker, Ramesh; Kalnay, Eugenia; Lambrigtsen, Bjorn H.; Lee, Sung-Yung; Le Marshall, John; McMillan, W. Wallace; McMillin, Larry; Olsen, Edward T.; Revercomb, Henry; Rosenkranz, Philip; Smith, William L.; Staelin, David; Strow, L. Larrabee; Susskin, Joel; Tobin, David; Wolf, Walter and Zhou, Lihang. AIRS: Improving weather forecasting and providing new data on greenhouse gases. Bulletin of the American Meteorological Society, Volume: 87, Issue: 7, 2006, pp.911-926. Reprint # 5194. 
PDF Document Link to PDF

87. Chandramouli, Krishnamoorthy; Wang, Xuguang; Johnson, Aaron and Otkin, Jason. Online nonlinear bias correction in ensemble Kalman filter to assimilate GOES-R all-sky radiances for the analysis and prediction of rapidly developing supercells. Journal of Advances in Modeling Earth Systems, Volume: 14, Issue: 3, 2022, e2021MS002711. Reprint # 8794. 
PDF Document Link to PDF

88. Cintineo, Rebecca M.; Otkin, J. A.; Jones, T. A.; Koch, S.; Wicker, L. J. and Stensrud, D. J.. Assimilation of satellite and radar observations in a convection-resolving Observing System Simulation Experiment. Boston, MA, American Meteorological Society, 2014, Abstract 603. 

89. Cintineo, Rebecca M.; Otkin, J. A.; Jones, T. A.; Koch, S.; Wicker, L. J. and Stensrud, D. J.. Assimilation of GOES-R ABI satellite and WSR-880 radar observations during a convection-resolving OSSE. Boston, MA, American Meteorological Society, 2015, Abstract 6. 

90. Cintineo, Rebecca M.; Otkin, J. A.; Jones, T. A.; Koch, S.; Wicker, L. J. and Stensrud, D. J.. Assimilation of satellite and radar observations during a convection-resolving observing system simulation experiment. Boston, MA, American Meteorological Society, 2014, Abstract 7A. 

91. Cintineo, Rebecca M.; Otkin, J.; Jones, T. A.; Koch, S.; Wicker, L. J. and Stensrud, D. J.. Assimilation of GOES-R ABI satellite and WSR-88D radar observations during a convection-resolving OSSE. Boston, MA, American Meteorological Society, 2016, Abstract J6.5. 

92. Cintineo, Rebecca M.; Otkin, J.; Jones, T. A.; Koch, S.; Wicker, L. J. and Stensrud, D. J.. Assimilation of GOES-R ABI satellite and WSR-88D radar observations during a convection-resolving Observing System Simulation Experiment. Boston, MA, American Meteorological Society, 2015, Abstract 235. 

93. Cintineo, Rebecca M.; Otkin, Jason A.; Jones, Thomas A.; Koch, Steven and Stensrud, David J.. Assimilation of synthetic GOES-R ABI infrared brightness temperatures and WSR-88D radar observations in a high-resolution OSSE. Monthly Weather Review, Volume: 144, Issue: 9, 2016, pp.3159-3180. Reprint # 7698. 
PDF Document Link to PDF

94. Cintineo, Rebecca; Otkin, Jason A.; Xue, Ming and Kong, Fanyou. Evaluating the accuracy of model parameterization schemes in convection-permitting ensemble forecasts using synthetic GOES-13 satellite observations. National Oceanic and Atmospheric Administration (NOAA), 2013, abstract and PowerPoint presentation. 

95. Ciren, Pubu; Kondragunta, Shobha; Zhao, Xuegeng (Tom); Ackerman, Steve and Frey, Rich. GOES-R ABI smoke/dust detection product. Madison, WI, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2008, Abstract 37. 
Abstract Document Link to Abstract

96. Cobb, Hugh; Beven, J.; Brennan, M.; DeMaria, M.; Knaff, J.; Velden, C.; Dunion, J.; Jedlovec, G.; Fuell, K. and Folmer, M.. The 2012 Satellite Proving Ground at the National Hurricane Center. US Department of Commerce, National Oceanic And Atmospheric Administration (NOAA), 2013, PowerPoint presentation. 

97. Connell, B.; Braun, J.; Bikos, D.; Van Til, R.; Lindstrom, S.; Bachmeier, S.; Mostek, T. and DeMaria, M.. New course: Satellite hydrology and meteorology for forecasters. Madison, WI, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2009, Abstract 32. 
Abstract Document Link to Abstract

98. Connell, B.; Schmit, T.; Gurka, J.; Goodman, S.; Hillger, D. and Hill, S.. New training: GOES-R 101. Madison, WI, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2009, Abstract 33. 
Abstract Document Link to Abstract

99. Connell, Bernadette H.; Bikos, D.; Braun, J.; Bachmeier, A. S.; Lindstrom, S. S.; Mostek, A.; DeMaria, M. and Schmit, T. J.. Training for GOES-R directed toward forecasters. Boston, MA, American Meteorological Society (AMS), 2011, Abstract 626. 

100. Craven, Jeffrey P.; Cronce, Marcia R.; Davis, Steve; Feltz, Wayne F. and Gerth, Jordan J.. GOES R Proving Ground: CIMSS/NWS Sullivan 2012. Raleigh, NC, National Weather Association, 2012, Abstract P1.12. 

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