TECA: Petascale pattern recognition for climate science

Prabhat; Surendra Byna; Venkatram Vishwanath; Eli Dart; Michael Wehner; William D. Collins

doi:10.1007/978-3-319-23117-4_37

TECA: Petascale pattern recognition for climate science

Prabhat
, Surendra Byna
, Venkatram Vishwanath
, Eli Dart
, Michael Wehner
, William D. Collins

School of Environmental Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Citations (Scopus)

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. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 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.

Original language	English
Title of host publication	Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings
Editors	George Azzopardi, Nicolai Petkov
Publisher	Springer-Verlag Berlin Heidelberg
Pages	426-436
Number of pages	11
ISBN (Print)	9783319231167
DOIs	https://doi.org/10.1007/978-3-319-23117-4_37
Publication status	Published - 2015
Event	16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015 - Valletta, Malta Duration: 2 Sept 2015 → 4 Sept 2015

Publication series

Name	Lecture Notes in Computer Science
Volume	9257 9257 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015
Country/Territory	Malta
City	Valletta
Period	2/09/15 → 4/09/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

Climate science
Data mining
High performance computing
Parallel I/O
Pattern detection
Petascale

Access to Document

10.1007/978-3-319-23117-4_37

Cite this

Prabhat, Byna, S., Vishwanath, V., Dart, E., Wehner, M., & Collins, W. D. (2015). TECA: Petascale pattern recognition for climate science. In G. Azzopardi, & N. Petkov (Eds.), Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings (pp. 426-436). (Lecture Notes in Computer Science; Vol. 9257 9257 LNCS). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-319-23117-4_37

@inproceedings{1386d06d3e474b709725a6ab1d0a1dd1,

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. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 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.",

keywords = "Climate science, Data mining, High performance computing, Parallel I/O, Pattern detection, Petascale",

author = "Prabhat and Surendra Byna and Venkatram Vishwanath and Eli Dart and Michael Wehner and Collins, \{William D.\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015 ; Conference date: 02-09-2015 Through 04-09-2015",

year = "2015",

doi = "10.1007/978-3-319-23117-4\_37",

language = "English",

isbn = "9783319231167",

series = "Lecture Notes in Computer Science",

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}

Prabhat, Byna, S, Vishwanath, V, Dart, E, Wehner, M & Collins, WD 2015, TECA: Petascale pattern recognition for climate science. in G Azzopardi & N Petkov (eds), Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings. Lecture Notes in Computer Science, vol. 9257 9257 LNCS, Springer-Verlag Berlin Heidelberg, pp. 426-436, 16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015, Valletta, Malta, 2/09/15. https://doi.org/10.1007/978-3-319-23117-4_37

TECA: Petascale pattern recognition for climate science. / Prabhat; Byna, Surendra; Vishwanath, Venkatram et al.
Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings. ed. / George Azzopardi; Nicolai Petkov. Springer-Verlag Berlin Heidelberg, 2015. p. 426-436 (Lecture Notes in Computer Science; Vol. 9257 9257 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - TECA

T2 - 16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015

AU - Prabhat,

AU - Byna, Surendra

AU - Vishwanath, Venkatram

AU - Dart, Eli

AU - Wehner, Michael

AU - Collins, William D.

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - 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. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 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.

AB - 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. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 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.

KW - Climate science

KW - Data mining

KW - High performance computing

KW - Parallel I/O

KW - Pattern detection

KW - Petascale

UR - https://www.scopus.com/pages/publications/84945980161

U2 - 10.1007/978-3-319-23117-4_37

DO - 10.1007/978-3-319-23117-4_37

M3 - Conference contribution

AN - SCOPUS:84945980161

SN - 9783319231167

T3 - Lecture Notes in Computer Science

SP - 426

EP - 436

BT - Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings

A2 - Azzopardi, George

A2 - Petkov, Nicolai

PB - Springer-Verlag Berlin Heidelberg

Y2 - 2 September 2015 through 4 September 2015

ER -

Prabhat, Byna S, Vishwanath V, Dart E, Wehner M, Collins WD. TECA: Petascale pattern recognition for climate science. In Azzopardi G, Petkov N, editors, Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings. Springer-Verlag Berlin Heidelberg. 2015. p. 426-436. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-23117-4_37

TECA: Petascale pattern recognition for climate science

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this