Joint Session 3 How Artificial Intelligence at Scale Will Link Weather and Climate Data to Society

Monday, 13 January 2020: 10:30 AM-12:00 PM
157AB (Boston Convention and Exhibition Center)
Hosts: (Joint between the 10th Symposium on Advances in Modeling and Analysis Using Python; the 19th Conference on Artificial Intelligence for Environmental Science; the 36th Conference on Environmental Information Processing Technologies; and the Sixth Symposium on High Performance Computing for Weather, Water, and Climate )
Cochairs:
David John Gagne II, NCAR, Boulder, CO and Scott Collis, Argonne National Laboratory, Environmental Science Division, Argonne, IL

Papers:
10:30 AM
J3.1
How Python Can Help us to Create the Physical Data Scientists of the Future (Core Science Keynote)
Amy McGovern, University of Oklahoma, Norman, OK

11:00 AM
J3.2
Cloud Nowcasting on Satellite Images: A Novel Dataset and Experimental Comparisons
Andreas Holm Nielsen, Aarhus University, Aarhus C, Denmark; and A. Wagner, A. Iosifidis, and H. Karstoft

11:15 AM
J3.3
A Deep Neural Network Deriving Cloud Properties from Satellite Remote Sensing
thomas rink, University of Wisconsin - Madison, Madison, WI; and A. Wimmers

11:30 AM
J3.4
Geocaching with Geohashing – scaling weather APIs with Python and Spark for Big Data Machine Learning
Alexander Kalmikov, QuantumBlack, a McKinsey Company, Cambridge, MA; and Y. Zhu, L. Zhang, and J. Annor

11:45 AM
J3.5
Frameworks for gaining insight and machine learning on large climate and weather datasets
Robert Jackson, Argonne National Laboratory, Argonne, IL; and S. Collis, I. Foster, B. Blaiszik, and S. Fiore

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