Title
TECA: Petascale Pattern Recognition for Climate Science
Abstract
Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. High-resolution climate simulations produce \"Big Data\": contemporary climate archives are $$\\approx 5PB$$ in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA Toolkit for Extreme Climate Analysis framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBM BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.
Year
DOI
Venue
2015
10.1007/978-3-319-23117-4_37
CAIP
Keywords
DocType
Volume
Pattern detection, Climate science, High performance computing, Parallel I/O, Data mining, Petascale
Conference
9257
ISSN
Citations 
PageRank 
0302-9743
4
0.47
References 
Authors
1
6
Name
Order
Citations
PageRank
Prabhat145634.79
Surendra Byna255139.65
Venkatram Vishwanath350747.27
Eli Dart4566.44
Michael Wehner510013.13
William D. Collins6243.05