Demonstrating the validity of a wildfire DDDAS

Craig C. Douglas; Jonathan D. Beezley; Janice Coen; Deng Li; Wei Li; Alan K. Mandel; Jan Mandel; Guan Qin; Anthony Vodacek

doi:10.1007/11758532_69

Demonstrating the validity of a wildfire DDDAS

Craig C. Douglas, Jonathan D. Beezley, Janice Coen, Deng Li, Wei Li, Alan K. Mandel, Jan Mandel, Guan Qin, Anthony Vodacek

Mesoscale & Microscale Meteorology Lab

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

17 Scopus citations

Abstract

We report on an ongoing effort to build a Dynamic Data Driven Application System (DDDAS) for short-range forecast of weather and wildfire behavior from real-time weather data, images, and sensor streams. The system changes the forecast as new data is received. We encapsulate the model code and apply an ensemble Kalman filter in time-space with a highly parallel implementation. In this paper, we discuss how we will demonstrate that our system works using a DDDAS testbed approach and data collected from an earlier fire.

Original language	English
Title of host publication	Computational Science - ICCS 2006
Subtitle of host publication	6th International Conference, Proceedings
Publisher	Springer Verlag
Pages	522-529
Number of pages	8
ISBN (Print)	3540343830, 9783540343837
DOIs	https://doi.org/10.1007/11758532_69
State	Published - 2006
Event	ICCS 2006: 6th International Conference on Computational Science - Reading, United Kingdom Duration: May 28 2006 → May 31 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3993 LNCS - III
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	ICCS 2006: 6th International Conference on Computational Science
Country/Territory	United Kingdom
City	Reading
Period	05/28/06 → 05/31/06

Access to Document

10.1007/11758532_69

Cite this

Douglas, C. C., Beezley, J. D., Coen, J., Li, D., Li, W., Mandel, A. K., Mandel, J., Qin, G., & Vodacek, A. (2006). Demonstrating the validity of a wildfire DDDAS. In Computational Science - ICCS 2006: 6th International Conference, Proceedings (pp. 522-529). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3993 LNCS - III). Springer Verlag. https://doi.org/10.1007/11758532_69

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title = "Demonstrating the validity of a wildfire DDDAS",

abstract = "We report on an ongoing effort to build a Dynamic Data Driven Application System (DDDAS) for short-range forecast of weather and wildfire behavior from real-time weather data, images, and sensor streams. The system changes the forecast as new data is received. We encapsulate the model code and apply an ensemble Kalman filter in time-space with a highly parallel implementation. In this paper, we discuss how we will demonstrate that our system works using a DDDAS testbed approach and data collected from an earlier fire.",

author = "Douglas, \{Craig C.\} and Beezley, \{Jonathan D.\} and Janice Coen and Deng Li and Wei Li and Mandel, \{Alan K.\} and Jan Mandel and Guan Qin and Anthony Vodacek",

year = "2006",

doi = "10.1007/11758532\_69",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

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booktitle = "Computational Science - ICCS 2006",

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note = "ICCS 2006: 6th International Conference on Computational Science ; Conference date: 28-05-2006 Through 31-05-2006",

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Douglas, CC, Beezley, JD, Coen, J, Li, D, Li, W, Mandel, AK, Mandel, J, Qin, G & Vodacek, A 2006, Demonstrating the validity of a wildfire DDDAS. in Computational Science - ICCS 2006: 6th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3993 LNCS - III, Springer Verlag, pp. 522-529, ICCS 2006: 6th International Conference on Computational Science, Reading, United Kingdom, 05/28/06. https://doi.org/10.1007/11758532_69

Demonstrating the validity of a wildfire DDDAS. / Douglas, Craig C.; Beezley, Jonathan D.; Coen, Janice et al.
Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag, 2006. p. 522-529 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3993 LNCS - III).

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

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AU - Beezley, Jonathan D.

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AU - Li, Wei

AU - Mandel, Alan K.

AU - Mandel, Jan

AU - Qin, Guan

AU - Vodacek, Anthony

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AB - We report on an ongoing effort to build a Dynamic Data Driven Application System (DDDAS) for short-range forecast of weather and wildfire behavior from real-time weather data, images, and sensor streams. The system changes the forecast as new data is received. We encapsulate the model code and apply an ensemble Kalman filter in time-space with a highly parallel implementation. In this paper, we discuss how we will demonstrate that our system works using a DDDAS testbed approach and data collected from an earlier fire.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Douglas CC, Beezley JD, Coen J, Li D, Li W, Mandel AK et al. Demonstrating the validity of a wildfire DDDAS. In Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag. 2006. p. 522-529. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11758532_69

Demonstrating the validity of a wildfire DDDAS

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