Poster Session 1 AI for Environmental Science Poster Session I

Monday, 13 January 2020: 4:00 PM-6:00 PM
Hall B (Boston Convention and Exhibition Center)

Cochairs:
John K. Williams, The Weather Company, An IBM Business, Andover, MA and Zhonghua Zheng, University of Illinois at Urbana−Champaign, Department of Civil and Environmental Engineering, Urbana, IL
Papers:
U.S. Water Prices: a Machine Learning Approach
Quinn McColly, Texas A&M University-Corpus Christi, Corpus Christi, TX; and P. Tissot and D. Yoskowitz

Gradient-based optimization to reduce uncertainty in radar rainfall estimates using deep learning techniques and in situ measurements from disdrometers
Haonan Chen, Colorado State Univ. and NOAA/Earth System Research Laboratory, Fort Collins, CO; and R. Cifelli and V. Chandrasekar

A Volume-to-Point Approach of Radar Based QPE
Ting-Shuo Yo, National Taiwan University, Taipei City, Taiwan; National Taiwan University, Taipei, Taiwan; and S. H. Su, C. C. Wu, C. W. Chang, and H. C. Kuo

Reconstruction of Severe Storms Observed by Weather Radars Using Recurrent Neural Networks
Cesar Beneti, SIMEPAR - Parana Meteorological System, Curitiba, Brazil; and C. Oliveira, S. Scheer, and L. Calvetti

Automated Detection of the Above Anvil Cirrus Plume Severe Storm Signature with Deep Learning
Charles Liles, NASA, Hampton, VA; and K. M. Bedka, T. D. Smith, Y. X. Huang, R. Biswas, E. Xia, C. Dolan, and A. Hosseini Jafari

Exploring the Application of Machine Learning to Identification of Storm Objects
Patrick A. Campbell, CIMMS/Univ. of Oklahoma and NOAA/NSSL, Norman, OK; and K. L. Ortega, S. S. Williams, and T. M. Smith

MRMS-based Hail Sizing and Classification Using Different, Large Databases
Jose Efraim Aguilar Escamilla, OU/CIMMS and NOAA/OAR/NSSL, Norman, OK; and S. S. Williams and K. L. Ortega

Developing a Hail Probability Product for the Probabilistic Hazards Information Framework
Kiel L. Ortega, OU/CIMMS and NOAA/OAR/NSSL, Norman, OK; and S. S. Williams

A New Machine Learning-Based Tornado Detection Algorithm for the WSR-88D Network
Thea Sandmael, CIMMS/Univ. of Oklahoma and NOAA/OAR/NSSL, Norman, OK; and K. L. Elmore and B. R. Smith

Comparison of shallow and deep neural network water temperature predictions for resource management during cold stunning events
Jensen DeGrande, Texas A&M University-Corpus Christi, Corpus Christi, TX; and P. Tissot, J. Wiliams, H. Kamangir, N. Durham, and S. Bates

Implementation of an Artificial Neural Network to Forecast Storm Surge Time Series
Alexandra N. Ramos-Valle, Rutgers Univ., New Brunswick, NJ; and E. N. Curchitser and C. L. Bruyère

Seasonal Hurricane Forecasting Using Machine Learning
Timothy Hall, Association of Certified Meteorologists (ACM), Walkersville, MD; and K. Hall

Single Station Forecasting from Deep Learning Methods
Nathaneal Beveridge, Air Force Institute of Technology, Wright-Patterson AFB, OK; and A. Geyer and R. C. Tournay

Abstract Submissions Closed



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