Building a dynamic data driven application system for hurricane forecasting

Gabrielle Allen

doi:10.1007/978-3-540-72584-8_136

Building a dynamic data driven application system for hurricane forecasting

Gabrielle Allen

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

Abstract

The Louisiana Coastal Area presents an array of rich and urgent scientific problems that require new computational approaches. These problems are interconnected with common components: hurricane activity is aggravated by ongoing wetland erosion; water circulation models are used in hurricane forecasts, ecological planning and emergency response; environmental sensors provide information for models of different processes with varying spatial and time scales. This has prompted programs to build an integrated, comprehensive, computational framework for meteorological, coastal, and ecological models. Dynamic and adaptive capabilities are crucially important for such a framework, providing the ability to integrate coupled models with real-time sensor information, or to enable deadline based scenarios and emergency decision control systems. This paper describes the ongoing development of a Dynamic Data Driven Application System for coastal and environmental applications (DynaCode), highlighting the challenges of providing accurate and timely forecasts for hurricane events.

Original language	English (US)
Title of host publication	Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I
Publisher	Springer
Pages	1034-1041
Number of pages	8
ISBN (Print)	9783540725831
DOIs	https://doi.org/10.1007/978-3-540-72584-8_136
State	Published - 2007
Externally published	Yes
Event	7th International Conference on Computational Science, ICCS 2007 - Beijing, China Duration: May 27 2007 → May 30 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4487 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	7th International Conference on Computational Science, ICCS 2007
Country/Territory	China
City	Beijing
Period	5/27/07 → 5/30/07

Keywords

Coastal modeling
Computational frameworks
DDDAS
Dynamic data driven application systems
Event driven computing
Hurricane forecasting
Priority computing

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Online availability

10.1007/978-3-540-72584-8_136

Library availability

Discover UIUC Full Text

Cite this

Allen, G. (2007). Building a dynamic data driven application system for hurricane forecasting. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I (pp. 1034-1041). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4487 LNCS). Springer. https://doi.org/10.1007/978-3-540-72584-8_136

Building a dynamic data driven application system for hurricane forecasting. / Allen, Gabrielle.
Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I. Springer, 2007. p. 1034-1041 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4487 LNCS).

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

Allen, G 2007, Building a dynamic data driven application system for hurricane forecasting. in Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4487 LNCS, Springer, pp. 1034-1041, 7th International Conference on Computational Science, ICCS 2007, Beijing, China, 5/27/07. https://doi.org/10.1007/978-3-540-72584-8_136

Allen G. Building a dynamic data driven application system for hurricane forecasting. In Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I. Springer. 2007. p. 1034-1041. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-72584-8_136

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Building a dynamic data driven application system for hurricane forecasting

Abstract

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Other

Keywords

ASJC Scopus subject areas

Online availability

Library availability

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