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Understanding architectural tradeoffs necessary to increase climate model intercomparison efficiency

Authors:

Chris A. Mattmann,

Amy J. Braverman,

Daniel J. CrichtonAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 35, Issue 3

Pages 1 - 6

https://doi.org/10.1145/1764810.1764826

Published: 11 May 2010 Publication History

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Abstract

NASA's Jet Propulsion Laboratory, in partnership with Lawrence Livermore National Laboratory, has been leading an effort to allow remote sensing data available from NASA satellites to be easily compared with climate model outputs available from the DOE-funded Earth System Grid, a national asset in climate science. This partnership is timely with the looming Intergovernmental Panel on Climate Change (IPCC)'s 5th Assement Report (AR5) in active discussion, and the metrics to better understand Earth's climate under formulation. JPL's project, titled the Climate Data eXchange (CDX) provides an easy-to-use software framework for cimate scientists to rapidliy integrate and evaluate the efficacy of observational data as applied to climate models.

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Cited By

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Schnase JLee TMattmann CLynnes CCinquini LRamirez PHart AWilliams DWaliser DRinsland PWebster WDuffy DMcInerney MTamkin GPotter GCarriere L(2016)Big Data Challenges in Climate Science: Improving the next-generation cyberinfrastructureIEEE Geoscience and Remote Sensing Magazine10.1109/MGRS.2015.25141924:3(10-22)Online publication date: Sep-2016
https://doi.org/10.1109/MGRS.2015.2514192
Crichton DMattmann CCinquini LBraverman AWaliser DGunson MHart AGoodale CLean PKim J(2012)Sharing Satellite Observations with the Climate-Modeling CommunityIEEE Software10.1109/MS.2012.2129:5(73-81)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1109/MS.2012.21
Crichton DMattmann CHughes JKelly SHart A(2011)A Multidisciplinary, Model-Driven, Distributed Science Data System ArchitectureGuide to e-Science10.1007/978-0-85729-439-5_5(117-143)Online publication date: 13-Apr-2011
https://doi.org/10.1007/978-0-85729-439-5_5

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Understanding architectural tradeoffs necessary to increase climate model intercomparison efficiency

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cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 35, Issue 3

May 2010

151 pages

ISSN:0163-5948

DOI:10.1145/1764810

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Association for Computing Machinery

New York, NY, United States

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Published: 11 May 2010

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Schnase JLee TMattmann CLynnes CCinquini LRamirez PHart AWilliams DWaliser DRinsland PWebster WDuffy DMcInerney MTamkin GPotter GCarriere L(2016)Big Data Challenges in Climate Science: Improving the next-generation cyberinfrastructureIEEE Geoscience and Remote Sensing Magazine10.1109/MGRS.2015.25141924:3(10-22)Online publication date: Sep-2016
https://doi.org/10.1109/MGRS.2015.2514192
Crichton DMattmann CCinquini LBraverman AWaliser DGunson MHart AGoodale CLean PKim J(2012)Sharing Satellite Observations with the Climate-Modeling CommunityIEEE Software10.1109/MS.2012.2129:5(73-81)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1109/MS.2012.21
Crichton DMattmann CHughes JKelly SHart A(2011)A Multidisciplinary, Model-Driven, Distributed Science Data System ArchitectureGuide to e-Science10.1007/978-0-85729-439-5_5(117-143)Online publication date: 13-Apr-2011
https://doi.org/10.1007/978-0-85729-439-5_5

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Sugarcane model intercomparison

Spatial variations of rain-use efficiency along a climate gradient on the Tibetan Plateau: A satellite-based analysis

Spatial variations of rain-use efficiency along a climate gradient on the Tibetan Plateau: A satellite-based analysis

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