GC113
Deep Learning for Climate Science and Extreme Weather Prediction II Posters

Wednesday, 16 December 2020: 04:00-20:59
Poster
Primary Convener:  Gemma Jayne Anderson, Lawrence Livermore National Laboratory, Livermore, CA, United States
Conveners:  Antonia Sebastian, University of North Carolina at Chapel Hill, Department of Geological Sciences, Chapel Hill, NC, United States, Brian L White, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States and Vipin Kumar, University of Minnesota Twin Cities, Department of Computer Science/Engineering, Minneapolis, MN, United States
Primary Liaison:  Gemma Jayne Anderson, Lawrence Livermore National Laboratory, Livermore, CA, United States
Chairs:  Brian L White, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States and Donald D Lucas, Lawrence Livermore National Laboratory, Livermore, CA, United States
OSPA Liaison:  Antonia Sebastian, Texas A&M University at Galveston, Marine Sciences, Galveston, TX, United States
 
A Machine Learning Approach to Forecasting California Wildfire Risk (774355)
Brian L White1, Jing Li2, Mayur Mudigonda2 and Adrian Albert3, (1)University of North Carolina at Chapel Hill, Marine Sciences, Chapel Hill, NC, United States, (2)Terrafuse.AI, Berkeley, CA, United States, (3)Lawrence Berkeley National Laboratory, Berkeley, CA, United States
 
A deep learning based physically-consistent super-resolution approach to climate downscaling (707056)
Michelle Yu1, Karthik Kashinath2 and Mustafa Mustafa2, (1)University of California - Berkeley, Berkeley, CA, United States, (2)Lawrence Berkeley National Laboratory, Berkeley, CA, United States
 
A Machine Learning Model of Arctic Sea Ice Motions (670612)
Jun Zhai, University of Washington, Dept. of Atmospheric Sciences, Seattle, WA, United States and Cecilia M Bitz, University of Washington, Atmospheric Sciences, Seattle, WA, United States
 
Checking the Reliability of Deep Learning Climate Predictive Model (671517)
Cunyong Sun and Xiangjun Shi, NUIST Nanjing University of Information Science and Technology, Nanjing, China
 
Development of super-resolution based downscaling for wildfire risk (719257)
Rackhun Son and JinHo Yoon, GIST Gwangju Institute of Science and Technology, Gwangju, Korea, Republic of (South)
 
Estimating the Rate of Change of Stratospheric Ozone using Deep Neural Networks (737325)
Helge Mohn1, Daniel Kreyling1, Ingo Wohltmann1, Merlin Barschke2 and Markus Rex1, (1)Alfred Wegener Institute Helmholtz-Center for Polar and Marine Research Potsdam, Climate Sciences | Atmospheric Physics, Potsdam, Germany, (2)Technische Universität Berlin, Institute for Aeronautics and Astronautics | Chair of Space Technology, Berlin, Germany
 
Identifying and correcting climate projection biases using artificial intelligence (718391)
Baoxiang Pan1, Gemma Jayne Anderson1, Donald D Lucas2, Andre Goncalves3, Celine Bonfils1, Jiwoo Lee4 and Yang Tian5, (1)Lawrence Livermore National Laboratory, Livermore, CA, United States, (2)LLNL, Livermore, CA, United States, (3)INPE National Institute for Space Research, CCST, Sao Jose dos Campos, Brazil, (4)Lawence Livermore National Laboratory, Livermore, CA, United States, (5)Harvard University, Cambridge, United States
 
Probabilistic deep learning for seasonal forecasting (670501)
Gemma Jayne Anderson1, Baoxiang Pan2, Andre Goncalves3, Donald D Lucas4, Celine Bonfils1 and Jiwoo Lee1, (1)Lawrence Livermore National Laboratory, Livermore, CA, United States, (2)Lawrence Livermore National Laboratory, Atmospheric, Earth, & Energy Science Division, Livermore, CA, United States, (3)Lawrence Livermore National Laboratory, Computer Engineering Directorate, Livermore, CA, United States, (4)LLNL, Livermore, CA, United States
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