Joint Poster Session 1 Big Data, Big Computing, Bigger Science

Monday, 7 January 2019: 4:00 PM-6:00 PM
Hall 4 (Phoenix Convention Center - West and North Buildings)
Hosts: (Joint between the Fifth Symposium on High Performance Computing for Weather, Water, and Climate; and the 18th Conference on Artificial and Computational Intelligence and its Applications to the Environmental Sciences )
Philippe Tissot, Texas A&M University−Corpus Christi, Conrad Blucher Institute, Corpus Christi, TX and Scott Collis, Argonne National Laboratory, Environmental Science Division, Argonne, IL
Timothy S. Sliwinski, Texas Tech University, Department of Geosciences, Atmospheric Science Group, Lubbock, TX

This session will address the challenges with respect to the collection, storage, transfer, and analysis of "Big Data" across the earth sciences, and the methods being used or developed to overcome them. Speakers will address real-world Big Data challenges they've encountered in their workflows and the solutions they've used to overcome them. Solutions could include data mining or machine learning algorithms, new or established Python toolkits, high performance parallel computing systems or platforms, advanced data storage and transfer capabilities, and more.

Community Data Management Systems for CMIP6
Denis Nadeau, LLNL, Livermore, CA; and C. Doutriaux, D. Williams, and T. Reshel

An Update on the Collaborative REAnalysis Technical Environment (CREATE)
Gerald L. Potter, NASA GSFC, Greenbelt, MD; and L. Carriere, J. Hertz, J. Peters, T. P. Maxwell, S. Strong, J. Shute, Y. Shen, and D. Duffy

Analyzing Big Data Produced by Mesoscale-Domain Large-Eddy Simulation
Song-Lak Kang, Gangneung-Wonju National Univ., Gangneung, Korea, Republic of (South)

Developing a Machine Learning–Based Hail Climatology Using the SHAVE and MYRORSS Databases
Skylar S. Williams, Oklahoma Univ./CIMMS and NOAA/OAR/NSSL, Norman, OK; and K. L. Ortega

Handout (12.3 MB)

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