Data management and analysis with WRF and SFIRE
Data management and analysis with WRF and SFIRE
复制标题
使用 WRF 和 SFIRE 进行数据管理和分析
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
A. Kochanski
中科院分区：
文献类型：
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作者：
J. Beezley;Mavin Martin;P. Rosen;J. Mandel;A. Kochanski
我们介绍了几个有用的实用程序在开发中的创建和分析真实的荒地火灾模拟使用WRF和SFIRE。这些实用程序作为独立的程序和脚本以及对其他知名软件的扩展而存在。Python web scraper自动化了从公共源下载和预处理大气和地表数据的过程。其他脚本通过自动创建参数文件来简化域设置。与Google Earth的集成允许用户在3D环境中探索模拟沿着真实的表面图像。后处理脚本为用户提供了许多与许多常用可视化套件兼容的输出数据格式，允许创建高质量的3D渲染。总的来说，这些改进是为了建立一个统一的Web应用程序，为科学家和用户带来一个复杂的野火建模环境。
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.