A dynamic data driven wildland fire model

被引：0

作者：

Mandel, Jan ^{[1
,2
]}

Beezley, Jonathan D. ^{[1
,2
]}

Bennethum, Lynn S. ^{[1
]}

Chakraborty, Soham ^{[3
]}

Coen, Janice L. ^{[2
]}

Douglas, Craig C. ^{[3
,5
]}

Hatcher, Jay ^{[3
]}

Kim, Minjeong ^{[1
]}

Vodacek, Anthony ^{[4
]}

机构：

[1] Univ Colorado, Denver, CO 80217 USA

[2] Natl Ctr Atmospher Res, Boulder, CO 80307 USA

[3] Univ Kentucky, Lexington, KY 40506 USA

[4] Rochester Inst Technol, Rochester, NY 14623 USA

[5] Yale Univ, New Haven, CT 06520 USA

来源：

COMPUTATIONAL SCIENCE - ICCS 2007, PT 1, PROCEEDINGS | 2007年 / 4487卷

基金：

美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We present an overview of an ongoing project to build DDDAS to use all available data for a short term wildfire prediction. The project involves new data assimilation methods to inject data into a running simulation, a physics based model coupled with weather prediction, on-site data acquisition using sensors that can survive a passing fire, and on-line visualization using Google Earth.

引用

页码：1042 / +

页数：3

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