GC034
Earth Observations from Geostationary Satellites: Applied Research and Applications

Session ID#: 162867

Session Description:
Instrumentation aboard the newest generation geostationary satellites has allowed Earth observations that were previously not possible. The Advanced Baseline Imager (ABI) aboard NOAA’s GOES-R series, and similar instruments on satellites launched by other countries, is a MODIS-like instrument spectrally but can provide data up to every 30 seconds of a given scene, allowing for feature tracking and broad applications in weather forecasts, atmospheric physics/chemistry as well as ocean/land (including Land Cover/Land Use Change) monitoring. Additionally, the Geostationary Lightning Mapper (GLM) provides constant, near hemispheric monitoring of lightning activity.  This section solicits work on advanced research and practical applications using data derived from instruments aboard U.S. and international geostationary satellites. We are especially interested in papers that support the missions of either NOAA or NASA Earth Sciences.
Co-Organized:
  • A - Atmospheric Sciences
  • H - Hydrology
Index Terms:

0480 Remote sensing [BIOGEOSCIENCES]
1632 Land cover change [GLOBAL CHANGE]
3315 Data assimilation [ATMOSPHERIC PROCESSES]
3322 Land/atmosphere interactions [ATMOSPHERIC PROCESSES]


Primary Convener:  Paul C Stoy, University of Wisconsin Madison, Biological Systems Engineering, Madison, WI, United States
Conveners:  Beatriz Martinez, University of Valencia, Department of Earth Physics and Thermodinamics, Burjassot, Spain, Joel McCorkel, NASA Goddard Space Flight Center, Greenbelt, United States and Andrew Heidinger, NOAA/NESDIS, Greenbelt, MD, United States
 
Impacts of the GLM measurements aboard the GOES-R series satellites on severe convective precipitation detection and retrievals (1041113)
Haonan Chen1, Yifan Yang2, Kyle Hilburn3 and Mahmood Azimi-Sadjadi2, (1)Colorado State University, Fort Collins, CO, United States, (2)Colorado State University, Fort Collins, United States, (3)Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
 
A Lagrangian View Of The Liquid Water Path Response To Aerosols Using Bias-corrected GOES-16 Observations (1050764)
Kevin Mitchell Smalley, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States and Matthew D Lebsock, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
 
Parameterization of long-continuing-current lightning for chemistry-climate models (1052857)
Francisco J. Perez-Invernon, Instituto de Astrofísica de Andalucía (IAA - CSIC), Granada, Spain, Heidi Huntrieser, German Aerospace Center Oberpfaffenhofen, Oberpfaffenhofen, Germany, Patrick Joeckel, German Aerospace Center DLR Oberpfaffenhofen, Institute of Atmospheric Physics, Oberpfaffenhofen, Germany and Francisco J. Gordillo-Vazquez, Instituto de Astrofísica de Andalucía (IAA)-CSIC, Granada, Spain
 
Fusing GeoNEX and VIIRS Surface BRDF Retrievals: Exploring a GEO-LEO Synergy (1068094)
Weile Wang1, Hirofumi Hashimoto1, Taejin Park2, Yujie Wang3, Alexei Lyapustin4 and Ian G Brosnan5, (1)NASA Ames Research Center, Moffett Field, CA, United States, (2)NASA Ames Research Center/Bay Area Environmental Research Institute, Moffett Field, United States, (3)University of Maryland Baltimore County, Baltimore, United States, (4)NASA Goddard Space Flight Center, Greenbelt, United States, (5)NASA Ames Research Center, Earth Science Division, Moffett Field, CA, United States
 
Challenges of the Coarse-satellite GPP Product from MSG/SEVIRI Data (MGPP) (1071261)
Beatriz Martinez, University of Valencia, Department of Earth Physics and Thermodinamics, Burjassot, Spain, Sergio Sánchez-Ruiz, University of Valencia, Department of Physics and Thermodinamics, Burjassot, Spain, Manuel Campos-Taberner, University of Valencia, Department of Earth Physics and Thermodynamics, València, Spain, Javier Garcia-Haro, University of Valencia, Valencia, Spain and Maria-Amparo Gilabert, University of Valencia, Burjassot, Spain
 
GEO-SIF: A continental-scale, hourly reconstructed solar-induced fluorescence product derived from OCO-3 and GK-2A over Eastern Asia and Oceania (1084497)
Sungchan Jeong, Seoul National University, Interdisciplinary Program in Landscape Architecture, Seoul, South Korea, Youngryel Ryu, Seoul National University, Department of Landscape Architecture and Rural Systems Engineering, Seoul, South Korea, Xing Li, Seoul National University, Research Institute of Agriculture and Life Sciences, Seoul, South Korea, Benjamin Dechant, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany, Juwon Kong, Interdisciplinary Program in Landscape Architecture, Seoul National University, Seoul, South Korea and Wonseok Choi, Interdisciplinary Program in Landscape Architecture, Seoul, South Korea
 
An Automated Detection Pipeline and Statistical Analysis of Meteors Detected by GOES GLM (1084660)
Jeffrey Claiborne Smith1, Robert Livingston Morris1, Randolph Longenbaugh2, Nina McCurdy3, Anthony Ozerov4, Tasan Smith-Gandy5 and Jessie Dotson6, (1)SETI Institute Mountain View, Mountain View, CA, United States, (2)Sandia National Laboratories, Albuquerque, NM, United States, (3)NASA Ames Research Center, Moffett Field, United States, (4)Columbia University, New York, United States, (5)Williams College, Williamstown, MA, United States, (6)NASA Ames Research Center, Astrophysics Branch, Moffett Field, CA, United States
 
Planning for Future Earth Observations: How GeoXO Will Expand Geostationary Measurements (1087922)
Daniel Lindsey1, Andrew Heidinger2, Joel McCorkel3 and Pamela Sullivan2, (1)NOAA National Environmental Satellite, Data, and Information Service, Silver Spring, MD, United States, (2)NOAA/NESDIS, Greenbelt, MD, United States, (3)NASA Goddard Space Flight Center, Greenbelt, United States
 
Generation of Bidirectional Reflectance Distribution Function (BRDF) Adjusted Advanced Baseline Imager (ABI) EVI2 Product for Land Surface Phenology (LSP) Detection (1091162)
Shuai Gao, Xiaoyang Zhang, Hankui Zhang and Yu Shen, South Dakota State University, Department of Geography and Geospatial Sciences, and Geospatial Sciences Center of Excellence (GSCE), Brookings, United States
 
Characterizing Precursory Volcanic Activity Using Geostationary Thermal Infrared Data (1091648)
James Oliver Thompson1,2, Michael S Ramsey3, Daniel Williams3 and Vincent J Realmuto4, (1)University of Pittsburgh, Department of Geology and Environmental Science, Pittsburgh, United States, (2)Baylor University, Department of Geosciences, Waco, United States, (3)University of Pittsburgh, Department of Geology and Environmental Science, Pittsburgh, PA, United States, (4)JPL, Pasadena, United States
 
Synergistic geostationary retrievals of aerosol properties using a combined implementation of the Dark Target and GRASP retrievals (1092634)
Reed Espinosa, NASA Goddard Space Flight Center, Greenbelt, United States, Yingxi Rona Shi, University of North Dakota, Grand Forks, ND, United States, Robert C Levy, NASA/Goddard Space Flight Ctr, Greenbelt, United States, Anin Puthukkudy, University of Maryland Baltimore County, Department of Physics, Earth and Space Institute, GESTAR-II, Baltimore, United States and Oleg Dubovik, Laboratoire d'Optique Atmosphérique, CNRS/University of Lille, Lille, France
 
Geostationary satellite observations reveal the impact of heat waves on diurnal dynamics of ecosystem productivity (1101393)
Xing Li, Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea, Youngryel Ryu, Seoul National University, Department of Landscape Architecture and Rural Systems Engineering, Seoul, South Korea, Jingfeng Xiao, University of New Hampshire, Durham, United States, Jiangong Liu, Columbia University, New York, United States, Benjamin Dechant, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany, Bolun Li, School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing, China, Sungchan Jeong, Seoul National University, Interdisciplinary Program in Landscape Architecture, Seoul, South Korea and Hang Xu, Beijing Forestry University, College of Soil and Water Conservation, Beijing, China
 
The Dark Target Aerosol Project: GEO retrieval and GEO-LEO fusion (1110289)
Robert Holz1, Bhaskar Ramachandran2, Min M Oo3, Virginia R Sawyer4, Jennifer C Wei5, Lorraine Remer6, Pawan Gupta7, Yingxi Rona Shi8,9, Zhaohui Zhang5, Shana Mattoo8,10 and Robert C Levy2, (1)UW SSEC, Madison, WI, United States, (2)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (3)University of Wisconsin - Madison, Madison, WI, United States, (4)Science Systems and Applications, Inc., NASA GSFC Climate and Radiation Laboratory, Lanham, United States, (5)NASA GES DISC, Greenbelt, United States, (6)Joint Center for Earth Systems Technology, University of Maryland, Baltimore, MD, United States, (7)Universities Space Research Association, Huntsville, AL, United States, (8)NASA Goddard Space Flight Center, Greenbelt, United States, (9)Joint Center for Earth Systems Technology, Baltimore, United States, (10)Science Systems and Applications, Inc., Lanham, United States
 
MAGARA: A Multi-Angle Geostationary Aerosol Retrieval Algorithm. (1120735)
James Limbacher, Science Systems and Applications, Inc., Lanham, MD, United States and Ralph Kahn, NASA Goddard Space Flight Center, Greenbelt, MD, United States
 
Combining Geostationary and Polar-Orbiting Observations of Volcanic SO2 Plumes: A Case Study from the June 2019 Eruption of Raikoke Volcano (1125638)
Vincent J Realmuto, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, Andrew Prata, Clarendon Laboratory, Department of Physics, Oxford University, Oxford, United Kingdom and Michael S Ramsey, University of Pittsburgh, Department of Geology and Environmental Science, Pittsburgh, PA, United States
 
GOES-R PM2.5 Evaluation and Bias Correction - A Deep Learning Approach (1126510)
Alqamah Sayeed1,2, Pawan Gupta1,3, Hai Zhang4, Shobha Kondragunta5,6, Barron H. Henderson7, Yang Liu8, Dimple Pruthi9, Jingqiu Mao10, Sundar A Christopher11, Robert C Levy12 and Phillip G. Dickerson13, (1)NASA Marshall Space Flight Center, Huntsville, United States, (2)Universities Space Research Association Huntsville, Huntsville, AL, United States, (3)Universities Space Research Association, Huntsville, AL, United States, (4)IMSG at NOAA/NESDIS/STAR, College Park, MD, United States, (5)NOAA College Park, College Park, MD, United States, (6)NOAA NESDIS STAR, College Park, MD, United States, (7)U.S. Environmental Protection Agency, Research Triangle Park, United States, (8)Emory University, Gangarosa Department of Environmental Health, Atlanta, GA, United States, (9)Emory University, Gangarosa Department of Environmental Health, Rollins School of Public Health, Atlanta, Georgia, United States, (10)Department of Chemistry and Biochemistry and Geophysical Institute, University of Alaska, Fairbanks, Alaska, USA, Fairbanks, United States, (11)University of Alabama in Huntsville, Atmospheric and Earth Science, Huntsville, AL, United States, (12)NASA/Goddard Space Flight Ctr, Greenbelt, United States, (13)Environmental Protection Agency Research Triangle Park, Research Triangle Park, United States
 
Probabilistic Precipitation Estimation with the GOES16 Advanced Baseline Imager: A Machine Learning Approach (1126585)
Shruti Ashok Upadhyaya, University of Oklahoma, Advanced Radar Research Center (ARRC), Norman, OK, United States, Pierre-Emmanuel Kirstetter, University of Oklahoma, School of Meteorology and School of Civil Engineering and Environmental Science, Norman, OK, United States and Robert Joseph Kuligowski, NOAA Center for Satellite Applications and Reserch, Silver springs, United States
 
Burned area mapping in near-real time with GOES-R reflectance imagery (1131987)
Danielle Losos, Yale University, New Haven, CT, United States
 
The GeoCarb Mission – adding greenhouse gases and chlorophyll fluorescence to the suite of geostationary observations (1134045)
Peter Somkuti, University of Oklahoma Norman Campus, Department of Meteorology, Norman, United States and Sean Crowell, University of Oklahoma, Norman, OK, United States
 
Comparison of Semi-analytical Algorithms for Estimating Inherent Optical Properties in the Korean Seas (1140105)
Jiwon Kim, Korea Institute of Ocean Science & Technology, Seoul, Korea, Republic of (South), Young-Je Park, Korea Institute of Ocean Science & Technology, Pusan, South Korea and Jeong-Eon Moon, KIOST Korea Institute of Ocean Science and Technology, Korea Ocean Satellite Center, Ansan, South Korea
 
Verification of Estimated Surface Reflectance by Himawari-8 AHI Using Low Earth Orbit Satellite Data Toward Hyper-Temporal Monitoring of Vegetation (1143141)
Kazuhito Ichii1, Beichen Zhang1, Yuhei Yamamoto1, Wei Li1, Wei Yang1, Tomoaki Miura2 and Hiroki Yoshioka3, (1)Chiba University, Center for Environmental Remote Sensing, Chiba, Japan, (2)Univ Hawaii, Honolulu, HI, United States, (3)Aichi Prefectural University, Aichi, Japan
 
An improved light-use efficiency model for estimating diurnal variation in gross primary production (1146607)
Yuhei Yamamoto1, Kazuhito Ichii1, Youngryel Ryu2, Minseok Kang3, Shohei Murayama4 and Su-Jin Kim5, (1)Chiba University, Center for Environmental Remote Sensing, Chiba, Japan, (2)Seoul National University, Department of Landscape Architecture and Rural Systems Engineering, Seoul, South Korea, (3)National Center for AgroMeteorology, Seoul, South Korea, (4)National Institute of Advanced Industrial Science and Technology (AIST), Environmental Management Research Institute, Tsukuba, Japan, (5)National Institute of Forest Science, Seoul, South Korea
 
Toward Geostationary Remote Sensing of the Coupled Terrestrial Carbon and Water Cycles (1154106)
Paul Stoy1, Ankur R Desai2, Tedward Erker3, Sophie Hoffman3, Danielle Losos4, Jason Otkin5, Raia Ottenheimer6, Jonathan E Thom7, Zhou Zhang8 and Yafang Zhong9, (1)University of Wisconsin - Madison, Madison, WI, United States, (2)University of Wisconsin Madison, Atmospheric and Oceanic Sciences, Madison, WI, United States, (3)University of Wisconsin Madison, Madison, United States, (4)Yale University, New Haven, CT, United States, (5)University of Wisconsin-Madison, CIMSS/SSEC, Madison, United States, (6)University of Toronto, Toronto, Canada, (7)University of Wisconsin Madison, Madison, WI, United States, (8)University of Wisconsin-Madison, Biological Systems Engineering, Madison, United States, (9)University of Wisconsin-Madison, CIMSS/SSEC, Madison, WI, United States
 
Improved hybrid machine learning approach for California’s wildfires PM2.5 prediction using GOES-R AOD (1154969)
Dimple Pruthi, Emory University, Gangarosa Department of Environmental Health, Rollins School of Public Health, Atlanta, Georgia, United States, Wenhao Wang, Emory University, Gangarosa Department of Environmental Health, Atlanta, United States and Yang Liu, Emory University, Gangarosa Department of Environmental Health, Atlanta, GA, United States
 
Utilizing Supervised Machine Learning to Derive Water-Leaving Radiance from Existing Geostationary Satellite Imagery (1194107)
Jillian Ethridge, University of Alabama in Huntsville, Huntsville, AL, United States, Raphael Martin Kudela, University of California Santa Cruz, Santa Cruz, United States, Mariam Ayad, University of California, Santa Cruz, Department of Ocean Sciences, Santa Cruz, United States and Henry Houskeeper, UCLA, Los Angeles, United States