基于传输矩阵法的全球海洋生物地球化学模拟

IF 4.6 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Samar Khatiwala
{"title":"基于传输矩阵法的全球海洋生物地球化学模拟","authors":"Samar Khatiwala","doi":"10.1029/2025MS005028","DOIUrl":null,"url":null,"abstract":"<p>Marine biogeochemical models are important tools in the quest to understand the cycling of chemical and biological tracers such as nutrients, carbon and oxygen, as well as key components of the Earth System Models used to project climate change. Historically, given the need for speed, global scale modeling has been performed in compiled languages like Fortran. However, as high level scripting languages such as Python and Julia gain popularity, the need for models and tools accessible from them has become imperative. This paper introduces <span>tmm4py</span>, a Python interface to a redesigned version of the Transport Matrix Method (TMM) software, a computationally efficient numerical scheme for “offline” simulation of marine geochemical and biogeochemical tracers. The TMM provides a convenient framework for developing and testing new biogeochemical parameterizations, as well as running existing complex models driven by circulations derived from state-of-the-art physical models. <span>tmm4py</span> exposes all of the TMM library's functionality in Python, including transparent parallelization, allowing users to not only interactively use models written in compiled languages, but also develop complex models in pure Python with performance similar to compiled code. <span>tmm4py</span> enables users to exploit the large Python-based scientific software ecosystem, including libraries for machine learning and deploying models on Graphics Processing Units. The various features of <span>tmm4py</span> are described and illustrated through practical examples, including a full-fledged biogeochemical model written entirely in Python.</p>","PeriodicalId":14881,"journal":{"name":"Journal of Advances in Modeling Earth Systems","volume":"17 8","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS005028","citationCount":"0","resultStr":"{\"title\":\"tmm4py: Global Ocean Biogeochemical Modeling in Python With the Transport Matrix Method\",\"authors\":\"Samar Khatiwala\",\"doi\":\"10.1029/2025MS005028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Marine biogeochemical models are important tools in the quest to understand the cycling of chemical and biological tracers such as nutrients, carbon and oxygen, as well as key components of the Earth System Models used to project climate change. Historically, given the need for speed, global scale modeling has been performed in compiled languages like Fortran. However, as high level scripting languages such as Python and Julia gain popularity, the need for models and tools accessible from them has become imperative. This paper introduces <span>tmm4py</span>, a Python interface to a redesigned version of the Transport Matrix Method (TMM) software, a computationally efficient numerical scheme for “offline” simulation of marine geochemical and biogeochemical tracers. The TMM provides a convenient framework for developing and testing new biogeochemical parameterizations, as well as running existing complex models driven by circulations derived from state-of-the-art physical models. <span>tmm4py</span> exposes all of the TMM library's functionality in Python, including transparent parallelization, allowing users to not only interactively use models written in compiled languages, but also develop complex models in pure Python with performance similar to compiled code. <span>tmm4py</span> enables users to exploit the large Python-based scientific software ecosystem, including libraries for machine learning and deploying models on Graphics Processing Units. The various features of <span>tmm4py</span> are described and illustrated through practical examples, including a full-fledged biogeochemical model written entirely in Python.</p>\",\"PeriodicalId\":14881,\"journal\":{\"name\":\"Journal of Advances in Modeling Earth Systems\",\"volume\":\"17 8\",\"pages\":\"\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025MS005028\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Advances in Modeling Earth Systems\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025MS005028\",\"RegionNum\":2,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Advances in Modeling Earth Systems","FirstCategoryId":"89","ListUrlMain":"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025MS005028","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

海洋生物地球化学模型是了解化学和生物示踪剂(如营养物质、碳和氧)循环的重要工具,也是用于预测气候变化的地球系统模型的关键组成部分。从历史上看,考虑到对速度的需求,全球规模的建模一直是用Fortran等编译语言执行的。然而,随着Python和Julia等高级脚本语言的流行,对可从它们访问的模型和工具的需求已经变得势在必行。本文介绍了tmm4py,一个Python接口,用于重新设计版本的传输矩阵方法(TMM)软件,一个计算效率高的数值方案,用于“离线”模拟海洋地球化学和生物地球化学示踪剂。TMM为开发和测试新的生物地球化学参数化提供了方便的框架,也为运行由最先进的物理模型衍生的环流驱动的现有复杂模型提供了方便。tmm4py在Python中公开了TMM库的所有功能,包括透明的并行化,允许用户不仅可以交互式地使用用编译语言编写的模型,还可以用纯Python开发性能与编译代码相似的复杂模型。tmm4py使用户能够利用基于python的大型科学软件生态系统,包括用于机器学习和在图形处理单元上部署模型的库。通过实际示例描述和说明了tmm4py的各种特性,包括完全用Python编写的成熟的生物地球化学模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

tmm4py: Global Ocean Biogeochemical Modeling in Python With the Transport Matrix Method

tmm4py: Global Ocean Biogeochemical Modeling in Python With the Transport Matrix Method

tmm4py: Global Ocean Biogeochemical Modeling in Python With the Transport Matrix Method

Marine biogeochemical models are important tools in the quest to understand the cycling of chemical and biological tracers such as nutrients, carbon and oxygen, as well as key components of the Earth System Models used to project climate change. Historically, given the need for speed, global scale modeling has been performed in compiled languages like Fortran. However, as high level scripting languages such as Python and Julia gain popularity, the need for models and tools accessible from them has become imperative. This paper introduces tmm4py, a Python interface to a redesigned version of the Transport Matrix Method (TMM) software, a computationally efficient numerical scheme for “offline” simulation of marine geochemical and biogeochemical tracers. The TMM provides a convenient framework for developing and testing new biogeochemical parameterizations, as well as running existing complex models driven by circulations derived from state-of-the-art physical models. tmm4py exposes all of the TMM library's functionality in Python, including transparent parallelization, allowing users to not only interactively use models written in compiled languages, but also develop complex models in pure Python with performance similar to compiled code. tmm4py enables users to exploit the large Python-based scientific software ecosystem, including libraries for machine learning and deploying models on Graphics Processing Units. The various features of tmm4py are described and illustrated through practical examples, including a full-fledged biogeochemical model written entirely in Python.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Advances in Modeling Earth Systems
Journal of Advances in Modeling Earth Systems METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
11.40
自引率
11.80%
发文量
241
审稿时长
>12 weeks
期刊介绍: The Journal of Advances in Modeling Earth Systems (JAMES) is committed to advancing the science of Earth systems modeling by offering high-quality scientific research through online availability and open access licensing. JAMES invites authors and readers from the international Earth systems modeling community. Open access. Articles are available free of charge for everyone with Internet access to view and download. Formal peer review. Supplemental material, such as code samples, images, and visualizations, is published at no additional charge. No additional charge for color figures. Modest page charges to cover production costs. Articles published in high-quality full text PDF, HTML, and XML. Internal and external reference linking, DOI registration, and forward linking via CrossRef.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信