The Community for Technology Leaders
RSS Icon
Issue No.05 - Sept.-Oct. (2012 vol.29)
pp: 73-81
Daniel J. Crichton , NASA Jet Propulsion Laboratory
Chris A. Mattmann , NASA Jet Propulsion Laboratory
Luca Cinquini , NASA Jet Propulsion Laboratory
Amy Braverman , NASA Jet Propulsion Laboratory
Duane Waliser , NASA Jet Propulsion Laboratory
Michael Gunson , NASA Jet Propulsion Laboratory
Andrew F. Hart , NASA Jet Propulsion Laboratory
Cameron E. Goodale , NASA Jet Propulsion Laboratory
Peter Lean , University of Reading
Jinwon Kim , University of California, Los Angeles
The disparate communities of climate modeling and remote sensing are finding economic, political, and societal benefit from the direct comparisons of climate model outputs to satellite observations, using these comparisons to help tune models and to provide ground truth in understanding the Earth's climate processes. In the context of the Intergovernmental Panel on Climate Change (IPCC) and its upcoming 5th Assessment Report (AR5), the authors have been working with principals in both communities to build a software infrastructure that enables these comparisons. This infrastructure must overcome several software engineering challenges, including bridging heterogeneous data file formats and metadata formats, transforming swath-based remotely sensed data into globally gridded datasets, and navigating and aggregating information from the largely distributed ecosystem of organizations that house these climate model outputs and satellite data. The authors' focus in this article is on the description of software tools and services that meet these stringent challenges, and on informing the broader communities of climate modelers, remote sensing experts, and software engineers on the lessons learned from their experience so that future systems can benefit and improve upon their existing results.
Meteorology, Distributed databases, Software development, Data models, Remote sensing, Computational modeling, Internet, Satellite communication, domain-specific architectures, distributed applications, evolving Internet applications
Daniel J. Crichton, Chris A. Mattmann, Luca Cinquini, Amy Braverman, Duane Waliser, Michael Gunson, Andrew F. Hart, Cameron E. Goodale, Peter Lean, Jinwon Kim, "Sharing Satellite Observations with the Climate-Modeling Community: Software and Architecture", IEEE Software, vol.29, no. 5, pp. 73-81, Sept.-Oct. 2012, doi:10.1109/MS.2012.21
1. Intergovernmental Panel on Climate Change, “Scoping the IPCC 5th Assessment Report, Proposal for an IPCC Expert Meeting on Assessing and Combining Multi Model Climate Projections,” IPCCXXX/Doc. 11, IPCC, Apr. 2009; .
2. F. Giorgi, C. Jones, and G. Asrar, “Addressing Climate Information Needs at the Regional Level: The CORDEX Framework,” WMO Bulletin, vol. 58, no. 3, 2009, pp. 175–183.
3. B Fortner, “HDF: The Hierarchical Data Format,” Dr Dobb's J. Software Tools and Professional Programming, 1998;
4. R.K. Rew and G.P. Davis, “NetCDF: An Interface for Scientific Data Access,” IEEE Computer Graphics and Applications, vol. 10, no. 4, 1990, pp. 76–82.
5. R.K. Rew et al., “The CF Conventions: Governance and Community Issues in Establishing Standards for Representing Climate, Forecast, and Observational Data,” slide presentation, Am. Geophysical Union Fall Meeting, abstract #IN52A-07, 2007.
6. C. Mattmann, A. Braverman, and D. Crichton, “Understanding Architectural Tradeoffs Necessary to Increase Climate Model Intercomparison Efficiency,” ACM SIGSOFT Software Eng. Notes, vol. 35, no. 3, 2010, pp. 1–6.
7. C. Mattmann et al., “A Software Architecture-Based Framework for Highly Distributed and Data Intensive Scientific Applications,” Proc. Int'l Conf. Software Eng. (ICSE 06), IEEE CS, 2006, pp. 721–730.
8. D. Crichton et al., “Facilitating Climate Modeling Research by Integrating NASA and the Earth System Grid,” 2011; http://bit.lyf7akgL, 2011.
9. R. Fielding and R.N. Taylor, “Principled Design of the Modern Web Architecture,” ACM Trans. Internet Technology, vol. 2, no 2, 2002, pp. 115–150.
47 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool