A33A:
A New Look at Climate Diagnosis and Modeling in the Era of Climate Informatics I Posters


Session ID#: 7924

Session Description:
The size and complexity of observational and model-simulated climate data have seen accelerated growth since the late 1970s. This increasing amount of data and our growing computational capacity create unprecedented opportunities for bringing innovative approaches of machine learning and data mining to climate data for interdisciplinary knowledge discovery, thus the birth of a new area “climate informatics”. This session seeks contributions from all application areas with the goal of improving process-level understanding and modeling of the Earth’s coupled climate system through advanced data mining and machine learning methods. These include but are not restricted to the development and implementation of new data mining methods for climate diagnosis and atmospheric process study, new ideas of data assimilation, stochastic climate and environment modeling, use of causal discovery and structure learning methods to understand large-scale dynamical processes, uncertainty quantification in climate simulation and projection, and data-driven approaches in weather forecasting and climate prediction.
Primary Conveners:  Yi Deng, Georgia Institute of Technology Main Campus, Atlanta, GA, United States
Conveners:  Imme Ebert-Uphoff, Colorado State University, Fort Collins, CO, United States
Chairs:  Yi Deng, Georgia Institute of Technology Main Campus, Atlanta, GA, United States and Imme Ebert-Uphoff, Colorado State University, Fort Collins, CO, United States
OSPA Liaisons:  Yi Deng, Georgia Institute of Technology Main Campus, Atlanta, GA, United States

Cross-Listed:
  • GC - Global Environmental Change
  • H - Hydrology
  • NH - Natural Hazards
  • OS - Ocean Sciences
Co-Sponsor(s):
  • AMS: American Meteorological Society -
Index Terms:

1914 Data mining [INFORMATICS]
1942 Machine learning [INFORMATICS]
3305 Climate change and variability [ATMOSPHERIC PROCESSES]
3337 Global climate models [ATMOSPHERIC PROCESSES]

Abstracts Submitted to this Session:

Xiaoming HU, Sun Yat-Sen University, Guangzhou, China, Song Yang, Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China and Ming Cai, Florida State University, Tallahassee, FL, United States
Yang Zhang1, Yu Nie1,2, Gang Chen3, Xiu-Qun Yang1 and David Alex Burrrows3, (1)Nanjing University, Nanjing, China, (2)Beijing Climate Center, China Meteorological Administration, Beijing, China, (3)Cornell University, Ithaca, NY, United States
Hari Krishnan1, Surendra Byna1, Michael F Wehner2, Junmin Gu1, Travis Allen O'Brien1, Burlen Loring1, Dáithí A Stone1, William Drew Collins3, Mr Prabhat4, Yunjie Liu1, Jeffrey N Johnson1 and Christopher J Paciorek5, (1)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2)Lawrence Berkeley National Laboratory, Computational Research Division, Berkeley, CA, United States, (3)Lawrence Berkeley National Laboratory, Climate & Ecosystem Sciences Division, Berkeley, CA, United States, (4)Lawrence Berkeley National Laboratory, National Energy Research Scientific Computing Center (NERSC), Berkeley, CA, United States, (5)University of California, Berkeley, CA, United States
Xiuhong Chen, Xianglei Huang, Chaoyi Jiao, Mark Flanner, Todd Raeker and Brock Palen, University of Michigan Ann Arbor, Ann Arbor, MI, United States
Ranjini Swaminathan1, Mohan Sridharan1, Katharine Hayhoe2 and Gillian Dobbie1, (1)University of Auckland, Auckland, New Zealand, (2)Texas Tech University, Climate Science Center, Lubbock, TX, United States
Zhiping Wen and Yuanyuan Guo, Sun Yat-Sen University, Guangzhou, China
Ryan Cabell, Luca Delle Monache, Stefano Alessandrini and Luna Marie Rodriguez, National Center for Atmospheric Research, Boulder, CO, United States
Clara Miho Narukawa Iwabe, UNESP Sao Paulo State University, Rio Claro, Brazil and Diogo Fusco, UNESP Sao Paulo State University, Bauru, Brazil
Zhenghui Lu, Peking University, Beijing, China
Yi Deng, Georgia Institute of Technology, Atlanta, GA, United States, Imme Ebert-Uphoff, Colorado State University, Fort Collins, CO, United States and Junwen Chen, Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA, United States