DocumentCode
576582
Title
Data management and analysis with WRF and SFIRE
Author
Beezley, Jonathan D. ; Martin, Mavin ; Rosen, Paul ; Mandel, Jan ; Kochanski, Adam K.
Author_Institution
Dept. of Math. & Stat. Sci., Univ. of Co., Denver, CO, USA
fYear
2012
fDate
22-27 July 2012
Firstpage
5274
Lastpage
5277
Abstract
We introduce several useful utilities in development for the creation and analysis of real wildland fire simulations using WRF and SFIRE. These utilities exist as standalone programs and scripts as well as extensions to other well known software. Python web scrapers automate the process of downloading and preprocessing atmospheric and surface data from common sources. Other scripts simplify the domain setup by creating parameter files automatically. Integration with Google Earth allows users to explore the simulation in a 3D environment along with real surface imagery. Postprocessing scripts provide the user with a number of output data formats compatible with many commonly used visualization suites allowing for the creation of high quality 3D renderings. As a whole, these improvements build toward a unified web application that brings a sophisticated wildland fire modeling environment to scientists and users alike.
Keywords
geographic information systems; geophysical image processing; geophysical techniques; geophysics computing; solid modelling; 3D environment; Google Earth; Python web scrapers; atmospheric data downloading; atmospheric data preprocessing; data analysis; data management; high quality 3D renderings; output data formats; postprocessing scripts; real surface imagery; real wildland fire simulations; standalone programs; surface data downloading; surface data preprocessing; unified web application; wildland fire modeling environment; Atmospheric modeling; Computational modeling; Data models; Google; Meteorology; Predictive models; Standards; Client-server systems; Data analysis; Data preprocessing; Geophysics computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6352419
Filename
6352419
Link To Document