Emulating Wildfire Plume Injection Using Machine Learning Trained by Large Eddy Simulation (LES)

IF 10.8 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Siyuan Wang
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引用次数: 0

Abstract

Wildfires have a major influence on the Earth system, with costly impacts on society. Despite decades of research, wildfires are still challenging to represent in air quality and chemistry-climate models. Wildfire plume rise (injection) is one of those poorly resolved processes and is also a major source of uncertainty in evaluating the wildfire impacts on air quality. Studies have shown that current plume rise models are subject to large uncertainties, including the Freitas Scheme, a widely used 1-dimensional, cloud-resolving subgrid model. In this work, a new machine learning-based plume rise emulator is presented, trained using a high-resolution, turbulence-resolving large eddy simulation (LES) model coupled with microphysics. The preliminary results show that this machine learning emulator outperforms the benchmark model, the Freitas scheme, in both accuracy and computational efficiency. Furthermore, a bagging ensemble is built to further increase the robustness and to battle internal variability. Efforts have been made to ensure that the machine learning emulator is robust, transparent, and not overtrained, and the results are interpretable and physically sound. Overall, this Plume Rise Emulating System using Machine Learning (PRESML) is a promising solution for regional and global air quality and chemistry-climate models.

Abstract Image

利用大涡模拟(LES)训练的机器学习模拟野火羽流喷射
野火对地球系统有重大影响,对社会造成代价高昂的影响。尽管经过了几十年的研究,野火在空气质量和化学气候模型中仍然具有挑战性。野火烟羽上升(喷射)是其中一个难以解决的过程,也是评估野火对空气质量影响的主要不确定性来源。研究表明,目前的羽流上升模型存在很大的不确定性,包括Freitas方案,这是一种广泛使用的一维云分辨子网格模型。在这项工作中,提出了一种新的基于机器学习的羽流上升模拟器,该模拟器使用高分辨率,湍流分辨大涡模拟(LES)模型与微物理相结合进行训练。初步结果表明,该仿真器在精度和计算效率方面都优于基准模型Freitas方案。此外,为了进一步提高鲁棒性和对抗内部变异性,还构建了bagging集成。已经做出了努力,以确保机器学习模拟器是鲁棒的,透明的,而不是过度训练,结果是可解释的和物理健全的。总的来说,使用机器学习(PRESML)的烟羽上升模拟系统是区域和全球空气质量和化学气候模型的一个有前途的解决方案。
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来源期刊
环境科学与技术
环境科学与技术 环境科学-工程:环境
CiteScore
17.50
自引率
9.60%
发文量
12359
审稿时长
2.8 months
期刊介绍: Environmental Science & Technology (ES&T) is a co-sponsored academic and technical magazine by the Hubei Provincial Environmental Protection Bureau and the Hubei Provincial Academy of Environmental Sciences. Environmental Science & Technology (ES&T) holds the status of Chinese core journals, scientific papers source journals of China, Chinese Science Citation Database source journals, and Chinese Academic Journal Comprehensive Evaluation Database source journals. This publication focuses on the academic field of environmental protection, featuring articles related to environmental protection and technical advancements.
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