A043
Machine Learning for Weather and Climate Modeling III Posters

Tuesday, 8 December 2020: 04:00-20:59
Poster
Primary Convener:  Noah Brenowitz, Vulcan, Climate Modeling, Seattle, WA, United States
Conveners:  Christopher Stephen Bretherton, University of Washington Seattle Campus, Seattle, WA, United States, Laure Zanna, University of Oxford, Dept. of Physics, Oxford, United Kingdom and Maike Sonnewald, Princeton University, Princeton, NJ, United States
Primary Liaison:  Noah Brenowitz, Vulcan, Climate Modeling, Seattle, WA, United States
Chairs:  Christopher Stephen Bretherton, University of Washington Seattle Campus, Seattle, WA, United States and Maike Sonnewald, Harvard University, Earth and Planetary Sciences, Cambridge, MA, United States
OSPA Liaison:  Noah Brenowitz, Vulcan, Inc., Climate Modeling, Seattle, WA, United States
 
Detecting Forecast Error Signatures (770354)
Stance Mason1, Hannah Aizenman2, Michael Grossberg2 and Nicarline Perdomo3, (1)CUNY City College of New York, Wappingers Falls, United States, (2)CUNY City College of New York, New York, NY, United States, (3)CUNY City College of New York, Bronx, United States
 
Building a Monthly Earth System Model Emulator for local temperature (697177)
Shruti Nath1,2, Quentin Lejeune1, Lea Beusch2, Carl-Friedrich Schleussner1 and Sonia I Seneviratne2, (1)Climate Analytics GmbH, Berlin, Germany, (2)Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
 
Causality linking ENSO with North American rainfall: inference by data-driven causal discovery methods and physical evaluation (714492)
Tao Zhang1, Wuyin Lin1, Zhaohua Wu2, Yangang Liu1 and Andrew M Vogelmann3, (1)Brookhaven National Laboratory, Upton, NY, United States, (2)Florida State University, Tallahassee, FL, United States, (3)Brookhaven Natl Lab, Upton, NY, United States
 
Interpretable Machine Learning applied to Seasonal Forecasting of Western US Precipitation (670571)
Peter Bernard Gibson1, William Chapman2, Alphan Altinok3, Michael J Deflorio1, Luca Delle Monache1 and Duane Edward Waliser3, (1)Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States, (2)Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, CA, United States, (3)NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
 
Improving Accumulated Precipitation Forecasts with Convolutional Neural Networks (768923)
Anirudhan Badrinath1, Luca Delle Monache2, Negin Hayatbini3, William Chapman3, Forest Cannon4 and Marty Ralph3, (1)University of California, Berkeley, Berkeley, CA, United States, (2)Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States, (3)Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, CA, United States, (4)Scripps Institution of Oceanography - Center for Western Weather & Water Extremes, La Jolla, CA, United States
 
Equivariant Deep Spatial Transformers for Auto-regressiveData-driven Forecasting of Geophysical Turbulence (720045)
Mustafa Mustafa1, Ashesh Kumar Chattopadhyay2, Pedram Hassanzadeh2 and Karthik Kashinath1, (1)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2)Rice University, Houston, TX, United States
 
Data-driven Medium-range Weather Prediction Achieves Comparable Skill to Dynamical Models. But What Does It Mean? (664258)
Stephan Rasp and Nils Thuerey, Technical University of Munich, Munich, Germany
 
Application of Generative Adversarial Networks (GANs) for Precipitation Forecasting (771797)
Negin Hayatbini1, Luca Delle Monache2, Bailey Kong3, Forest Cannon4, William Chapman1, Rachel R Weihs5, Anirudhan Badrinath6 and Marty Ralph1, (1)Scripps Institution of Oceanography, Center for Western Weather and Water Extremes (CW3E), La Jolla, CA, United States, (2)Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, United States, (3)University of California, Irvine, Department of Computer Science, Irvine, CA, United States, (4)Scripps Institution of Oceanography - Center for Western Weather & Water Extremes, La Jolla, CA, United States, (5)Scripps Institution of Oceanography, La Jolla, CA, United States, (6)University of California, Berkeley, Berkeley, CA, United States
 
Generative Large Eddy Simulations with conditional Variational Autoencoders (773465)
Surya Karthik Mukkavilli1, Mike S Pritchard2, Kyle Gregory Pressel3, Griffin Mooers4, Po-Lun Ma3 and Stephan Mandt5, (1)University of California Irvine, Irvine, CA, United States, (2)University California Irvine, Department of Earth System Science, Irvine, CA, United States, (3)Pacific Northwest National Laboratory, Richland, WA, United States, (4)University of California Irvine, Earth System Science, Irvine, CA, United States, (5)University of California Irvine, Computer Science, Irvine, United States
 
Non-Intrusive Reduced Order Model of Urban Wind Field with Dynamic Boundary Conditions (674358)
Songlin Xiang1, Xiangwen Fu2, Jingcheng Zhou3, Yuqing Wang3, Yizhou Zhang3, Xiurong Hu4, Jiayu Xu1, Huazhen Liu3, Junfeng Liu3, Jianmin Ma5 and Shu Tao1, (1)Peking University, College of Urban and Environmental Sciences, Beijing, China, (2)Princeton University, Woodrow Wilson School of Public and International Affairs, Princeton, NJ 08544, United States, (3)Peking University, Beijing, China, (4)Peking University, Beijing, Beijing, China, (5)Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
 
Physics-Informed Machine Learning for Urban Climate Modeling (675642)
Zhonghua Zheng1, Keith W Oleson2 and Lei Zhao1, (1)University of Illinois at Urbana-Champaign, Department of Civil and Environmental Engineering, Urbana, IL, United States, (2)NCAR, Boulder, CO, United States
 
Probabilistic forecasts with Bayesian Convolutional Long-Short Term Memory Networks: an idealized Lorenz 84 model and real world Arctic application (690033)
Yang Liu1, Jisk Jakob Attema1 and Wilco Hazeleger2, (1)Netherlands eScience Center, Amsterdam, Netherlands, (2)Utrecht University, Utrecht, Netherlands
 
Real-Time Spatiotemporal NO2 Air Pollution Prediction with Deep Convolutional LSTM through Satellite Image Analytics (669839)
Pratyush Muthukumar1, Emmanuel Cocom1, Jeanne Holm2, Dawn Comer2, Anthony Lyons2, Irene Burga2, Christa A Hasenkopf3, Chisato Calvert3 and Mohammad Pourhomayoun1, (1)California State University Los Angeles, Department of Computer Science, Los Angeles, CA, United States, (2)City of Los Angeles, Los Angeles, CA, United States, (3)OpenAQ, Washington, DC, United States
 
Satellite Imagery-Based Urban Noise Prediction Model – Case study over Vancouver, Canada (774735)
Meytar Sorek-Hamer1, Emily Deardorff2, Violet Lingenfelter2, Michael von Pohle3, Adwait Sahasrabhojanee4, Ata Akbari Asanjan5, Michael Brauer6 and Hugh Davies7, (1)NASA Ames Research Center, USRA, Moffett Field, United States, (2)NASA Ames Research Center (USRA), Moffet Field, United States, (3)NASA Ames Research Center, USRA, Moffet Field, United States, (4)NASA Ames Research Center (USRA), Moffet Field, CA, United States, (5)NASA Ames Research Center, USRA, Moffett Field, CA, United States, (6)University of British Columbia, School of Population and Public Health, Vancouver, BC, Canada, (7)University of British Columbia, Vancouver, Canada
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