Session 2B Deep Learning Applications for Environmental Science I

Monday, 13 January 2020: 2:00 PM-4:00 PM
156A (Boston Convention and Exhibition Center)

Cochairs:
Tianle Yuan, GSFC, Climate and Radiation Laboratory, Greenbelt, MD and Sarvesh Garimella, ACME AtronOmatic, LLC, Portland, OR
Papers:
2:00 PM
2B.1
Classifying Global Low Cloud Morphology with a Deep Learning Model: Results and Potential Use
Tianle Yuan, JCET, Baltimore, MD; and J. Mohrmann, H. Song, R. Wood, K. Meyer, and L. Oreopoulos

2:15 PM
2B.2
A Deep Learning Approach for Intelligent Compression of Satellite Data
Sarvesh Garimella, ACME AtronOmatic, LLC, Portland, OR

2:30 PM
2B.3
Artificial Intelligence (AI) Techniques to Enhance Satellite Data Use for Nowcasting and NWP/Data Assimilation
SA. Boukabara, NOAA/NESDIS/STAR, College Park, MD; and E. Maddy, N. Shahroudi, R. N. Hoffman, T. Connor, S. Upton, and J. E. Ten Hoeve III

2:45 PM
2B.4
Convective Storm Nowcasting Using a Deep Learning Approach
Lei Han, Ocean Univ. of China, Qingao, China; and W. Zhang and J. Sun

3:00 PM
2B.5
Using Deep Learning Algorithms in Forecasting the Severe Haze Events in Southeast Asia
Chien Wang, CNRS/UPS, Toulouse, France

3:15 PM
2B.6
Learning and Inference of Advective Fluid Transport in Geophysical Environments
Chinmay S Kulkarni, MIT, Cambridge, MA; and P. F. Lermusiaux

3:30 PM
2B.7
Downscaling Numerical Weather Models with GANs
Alok Singh, Terrafuse, Berkeley, CA; and B. White and A. Albert

3:45 PM
2B.8
Fine-scale surface climate data with deep learning
Thomas C. M. Martin, University of São Paulo (USP), São Paulo, Brazil; and H. R. Rocha, K. Brauman, M. Flörke, G. M. P. Perez, R. L. N. Wanderley, L. M. Domingues, and R. C. Abreu

Abstract Submissions Closed



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