Schwerdtfeger Library Publications Database

Results: Found 1678 records (displaying records 151 through 175)

151. 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.

152. 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.

153. 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

154. 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

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

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

157. 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.

158. 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.

159. 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.

160. 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.

161. 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.

162. 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.

163. 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.
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164. 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

165. 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

166. 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

167. 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.

168. 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.

169. 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.

170. 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.

171. 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.
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172. 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.
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173. 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.
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174. 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

175. 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.