实现无缝环境预测--开发泛欧亚实验(PEEX)建模平台

IF 4.2 3区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Big Earth Data Pub Date : 2024-04-09 DOI:10.1080/20964471.2024.2325019
A. Mahura, Alexander Baklanov, R. Makkonen, Michael Boy, T. Petäjä, Hanna K. Lappalainen, R. Nuterman, V. Kerminen, Stephen R. Arnold, Markus Jochum, Anatoly Shvidenko, Igor Esau, Mikhail Sofiev, Andreas Stohl, T. Aalto, Jianhui Bai, Chuchu Chen, Yafang Cheng, O. Drofa, Mei Huang, L. Järvi, H. Kokkola, R. Kouznetsov, Tingting Li, P. Malguzzi, Sarah Monks, Mads Bruun Poulsen, Steffen M. Noe, Y. Palamarchuk, B. Foreback, Petri S. Clusius, T. Rasmussen, Jun She, J. H. Sørensen, D. Spracklen, Hang Su, J. Tonttila, Siwen Wang, Jiandong Wang, Tobias Wolf-Grosse, Yongqiang Yu, Qing Zhang, Wei Zhang, Wen Zhang, Xunhua Zheng, Siqi Li, Yong Li, Putian Zhou, M. Kulmala
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引用次数: 0

摘要

泛欧亚实验建模平台(PEEX-MP)是 PEEX 研究计划的重要组成部分之一。PEEX MP 有 30 多个模型,旨在进行无缝环境预测。主要重点领域是北极-滨海地区和中国。PEEX MP 中使用的模型涵盖了地球系统的几个主要组成部分,如大气圈、水圈、土壤圈和生物圈,并解决了不同时空尺度和分辨率下的物理-化学-生物过程。本文介绍并讨论了 PEEX MP 地球系统多尺度建模概念、在线综合建模、正演/反演建模、社会经济建模和其他方法,尤其侧重于 PEEX 地理域中的应用。介绍了所使用的高性能计算设施、能力和 PEEX 建模结果数据流。介绍了处理 PEEX 建模和观测结果的几个虚拟研究平台(PEEX-View、虚拟研究环境、基于网络的 Atlas)。总体方法使我们能够更好地了解物理-化学-生物过程、地球系统的相互作用和反馈,并为评估研究提供有价值的信息,以评价 PEEX 领域对人口、环境和气候的风险、影响和后果等。这项工作也是 Sergej Zilitinkevich 教授的最后一个项目,他于 2021 年 2 月 15 日去世。由于定稿需要时间,论文实际上是在 2023 年提交的,我们无法证明最终的论文文本是与他达成一致的。
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Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform
The Pan-Eurasian Experiment Modelling Platform (PEEX-MP) is one of the key blocks of the PEEX Research Programme. The PEEX MP has more than 30 models and is directed towards seamless environmental prediction. The main focus area is the Arctic-boreal regions and China. The models used in PEEX-MP cover several main components of the Earth’s system, such as the atmosphere, hydrosphere, pedosphere and biosphere, and resolve the physical-chemical-biological processes at different spatial and temporal scales and resolutions. This paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system, online integrated, forward/inverse, and socioeconomical modelling, and other approaches with a particular focus on applications in the PEEX geographical domain. The employed high-performance computing facilities, capabilities, and PEEX dataflow for modelling results are described. Several virtual research platforms (PEEX-View, Virtual Research Environment, Web-based Atlas) for handling PEEX modelling and observational results are introduced. The over-all approach allows us to understand better physical-chemical-biological processes, Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks, impact, consequences, etc. for population, environment and climate in the PEEX domain. This work was also one of the last projects of Prof. Sergej Zilitinkevich, who passed away on 15 February 2021. Since the finalization took time, the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.
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来源期刊
Big Earth Data
Big Earth Data Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
7.40
自引率
10.00%
发文量
60
审稿时长
10 weeks
期刊最新文献
Long-term (2013–2022) mapping of winter wheat in the North China Plain using Landsat data: classification with optimal zoning strategy Marginal land in China suitable for bioenergy crops under diverse socioeconomic and climate scenarios from 2020–2100 Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform GEOSatDB: global civil earth observation satellite semantic database Time-first approach for land cover mapping using big Earth observation data time-series in a data cube – a case study from the Lake Geneva region (Switzerland)
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