Integration and execution of Community Land Model Urban (CLMU) in a containerized environment

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Junjie Yu , Yuan Sun , Sarah Lindley , Caroline Jay , David O. Topping , Keith W. Oleson , Zhonghua Zheng
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引用次数: 0

Abstract

The Community Land Model Urban (CLMU) is a process-based numerical urban climate model that simulates the interactions between the atmosphere and urban surfaces, serving as a powerful tool for the convergence of urban and climate science research. However, CLMU presents significant challenges due to the complexities of model installation, environment and case configuration, and generating model inputs. To address these challenges, a toolkit was developed, including (1) an operating system-independent containerized application developed to streamline the execution of CLMU and (2) a Python-based tool used to interface with the containerized CLMU and create urban surface and atmospheric forcing data. This toolkit enables users to simulate urban climate and explore climate-related variables such as urban building energy consumption and human thermal stress. It also supports the simulation under future climate conditions and the exploration of urban climate responses to various surface properties, providing a foundation for evaluating urban climate adaptation strategies.
集装箱化环境下社区土地模式城市(CLMU)的整合与实施
城市社区土地模式(CLMU)是一个基于过程的数值城市气候模式,它模拟了大气与城市地表之间的相互作用,是城市与气候科学研究融合的有力工具。然而,由于模型安装、环境和案例配置以及生成模型输入的复杂性,CLMU提出了重大的挑战。为了应对这些挑战,开发了一个工具包,包括:(1)一个独立于操作系统的容器化应用程序,用于简化CLMU的执行;(2)一个基于python的工具,用于与容器化CLMU接口,并创建城市地表和大气强迫数据。该工具包使用户能够模拟城市气候,并探索与气候相关的变量,如城市建筑能耗和人类热应力。支持未来气候条件下的模拟,探索城市气候对各种地表性质的响应,为评估城市气候适应策略提供依据。
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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