GC134
Deep Learning for Climate Science and Extreme Weather Prediction I

Thursday, 17 December 2020: 07:00-08:00
Virtual
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
07:00
GC134-01
Towards Physics-informed Deep Learning for Turbulent Flow Prediction (Invited) (665298)
Rose Yu, University of California San Diego, La Jolla, CA, United States
07:04
GC134-02
Analog forecasting of heat waves and cold spells using deep learning (Invited) (661532)
Pedram Hassanzadeh, Ashesh Kumar Chattopadhyay and Ebrahim Nabizadeh, Rice University, Houston, TX, United States
07:08
GC134-03
Artificial intelligence reconstructs missing climate information (745305)
Christopher Kadow, DKRZ German Climate Computing Centre, Hamburg, Germany, David Hall, NVIDIA, Lafayette, CO, United States and Uwe Ulbrich, Free University of Berlin, Institute of Meteorology, Berlin, Germany
07:12
GC134-04
Using Visualization of Semi-Supervised Learning to Study Drivers of Distinct Atmospheric River Conditions Historically and in GCMs (713647)
Naomi L Goldenson and Alexander D Hall, University of California Los Angeles, Los Angeles, CA, United States
07:16
GC134-05
Applying Machine Learning to Associate Precipitation Extremes with Synoptic-Scale Weather Events (757210)
Katherine Dagon1, Julie Caron2, Gerald Meehl1, Maria J Molina1 and John E Truesdale3, (1)National Center for Atmospheric Research, Boulder, CO, United States, (2)National Center for Atmospheric Research, Boulder, United States, (3)NCAR, Boulder, United States
07:20
GC134-06
Challenges with Machine Learning Interpretability as shown by a Climate Study (765112)
Maria J Molina1, David John Gagne II2 and Andreas F Prein1, (1)National Center for Atmospheric Research, Boulder, CO, United States, (2)NCAR/MMM, Boulder, CO, United States
07:24
GC134-07
Joint inter-seasonal forecasts with deep multitask learning (676014)
Andre Goncalves1, Gemma Jayne Anderson2, Baoxiang Pan3, Donald D Lucas2, Jiwoo Lee2 and Celine Bonfils2, (1)Lawrence Livermore National Laboratory, Computer Engineering Directorate, Livermore, CA, United States, (2)Lawrence Livermore National Laboratory, Livermore, CA, United States, (3)Lawrence Livermore National Laboratory, Atmospheric, Earth, & Energy Science Division, Livermore, CA, United States
07:28
GC134-08
Volcanic Forecasting with Intermittent Infrared Images via Deep Learning (755939)
Jeremy Diaz1, Guido Cervone1 and Christelle Wauthier2, (1)Pennsylvania State University Main Campus, Department of Geography and Institute for Computational and Data Sciences, University Park, PA, United States, (2)Pennsylvania State University Main Campus, Department of Geosciences and Institute for Computational and Data Sciences, University Park, PA, United States
07:32
Discussion
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