This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
Downloads
Authors
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. Despite its advanced capabilities, CLMU presents significant challenges for users unfamiliar with numerical modeling 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 (Pyclmuapp) used to interface the containerized CLMU and create urban surface data and atmospheric forcing data for the model. This toolkit enables users to simulate urban climate and explore climate-related variables such as urban building energy consumption, urban water balance, 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. Overall, this toolkit makes urban climate modeling more accessible, promoting broader applications from research to practical urban planning and policy-making.
DOI
https://doi.org/10.31223/X5CD9C
Subjects
Civil Engineering, Computer Sciences, Earth Sciences, Environmental Engineering, Environmental Sciences
Keywords
Urban climate modeling, Containerized application, climate change, Urban Climate
Dates
Published: 2024-11-26 22:40
Last Updated: 2024-11-27 06:40
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data Availability (Reason not available):
https://doi.org/10.5281/zenodo.14224042
There are no comments or no comments have been made public for this article.