IN11A:
An Object-Oriented View of Atmospheric Science: Feature Detection and Characterization in Big Data Posters

Submit an Abstract to this Session



Session ID#: 24654

Session Description:
Computation has played a substantial role in furthering atmospheric research that extends beyond running models. Objectively detecting features such as hurricanes, extra-tropical cyclones, atmospheric rivers, blocking anticyclones and other short term weather phenomena is a topic of great interest both to those who study their physical properties as well as to those interested in their impacts. Ongoing improvements in computational throughput is leading to the production of high resolution multi-decadal simulations leading terabyte to petabyte data sets. Machine learning and other innovative algorithms can provide rapid exploration of these massive datasets and lead to new insights into these features. This session highlights new methods and improvements in feature detection research.
Primary Convener:  Marielle Cristine Pinheiro, University of California Davis, Land, Air, and Water Resources, Davis, CA, United States
Conveners:  Michael F Wehner, Lawrence Berkeley National Laboratory, Berkeley, CA, United States and Paul Aaron Ullrich, University of California Davis, Land, Air and Water Resources, Davis, CA, United States
Chairs:  Marielle Cristine Pinheiro, University of California Davis, Land, Air, and Water Resources, Davis, CA, United States and Michael F Wehner, Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, United States
OSPA Liaison:  Marielle Cristine Pinheiro, University of California Davis, Land, Air, and Water Resources, Davis, CA, United States
Index Terms:

0520 Data analysis: algorithms and implementation [COMPUTATIONAL GEOPHYSICS]
1914 Data mining [INFORMATICS]
1942 Machine learning [INFORMATICS]
1976 Software tools and services [INFORMATICS]

Abstracts Submitted to this Session:

Deep Learning for Extreme Weather Detection (Invited) (214443)
Mr Prabhat1, Evan Racah2, Jim Biard3, Yunjie Liu2, Mayur Mudigonda1, Karthik Kashinath4, Christopher Beckham5, Tegan Maharaj5, Samira Kahou6, Chris Pal5, Travis Allen O'Brien7, Michael F Wehner8, Kenneth Kunkel9 and William Drew Collins10, (1)University of California Berkeley, Berkeley, CA, United States, (2)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (3)Cooperative Institute for Climate and Satellite North Carolina State, Asheville, NC, United States, (4)NVIDIA Corporation, Santa Clara, CA, United States, (5)U. Montreal, Montreal, Canada, (6)Microsoft Research, Montreal, Canada, (7)Lawrence Berkeley National Lab, Climate & Ecosystem Sciences Division, Berkeley, United States, (8)Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, United States, (9)CICS-NC/NCDC, Asheville, NC, United States, (10)Berkeley Lab and UC Berkeley, Berkeley, United States
Topological data analyses and machine learning for detection, classification and characterization of atmospheric rivers (296980)
Karthik Kashinath, NVIDIA Corporation, Santa Clara, CA, United States, Grzegorz Muszynski, British Antarctic Survey, Cambridge, United Kingdom, Michael F Wehner, Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, United States, Mr Prabhat, Lawrence Berkeley National Laboratory, Berkeley, CA, United States and Vitaliy Kurlin, University of Liverpool, Computer Science, Liverpool, United Kingdom
Using "CONNected objECT (CONNECT)" Algorithm to Explore Intense Global Water Vapor Transport to Investigate Impacts of Climate Variability and Change (293509)
Brian Kawzenuk1, Scott L Sellars2, Phu Nguyen3, F Martin Ralph1 and Soroosh Sorooshian4, (1)Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, UC San Diego, La Jolla, United States, (2)Scripps Institution of Oceanography, Center for Western Weather and Water Extremes, La Jolla, CA, United States, (3)University of California, Irvine, Department of Civil and Environmental Engineering, Irvine, United States, (4)UC Irvine, Irvine, CA, United States
Towards a Statistical Model of Tropical Cyclone Genesis (243422)
Arturo Fernandez1,2, Karthik Kashinath3, Jon McAuliffe4, Mr. Prabhat2, Philip B Stark1 and Michael F Wehner2, (1)University of California Berkeley, Statistics, Berkeley, CA, United States, (2)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (3)NVIDIA Corporation, Santa Clara, CA, United States, (4)University of California Berkeley, Statistics, Berkeley, United States
Lidar Cloud Detection with Fully Convolutional Networks (292294)
Erol Cromwell and Donna Flynn, Pacific Northwest National Laboratory, Richland, WA, United States

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