Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform
- Autor(en)
- Alexander Mahura, Alexander A. Baklanov, Risto Makkonen, Michael Boy, Tuukka Petäjä, Hanna K. Lappalainen, Roman Nuterman, Veli-Matti Kerminen, Stephen R. Arnold, Markus Jochum, Anatoly Shvidenko, Igor Esau, Mikhail Sofiev, Andreas Stohl, Tuula Aalto, Jianhui Bai, Chuchu Chen, Yafang Cheng, Oxana Drofa, Mei Huang, Leena Järvi, Harri Kokkola, Rostislav Kouznetsov, Tingting Li, Piero Malguzzi, Sarah A. Monks, Mads Bruun Poulsen, Steffen M. Noe, Yuliia Palamarchuk, Benjamin Foreback, Petri Clusius, Till Andreas Soya Rasmussen, Jun She, Jens Havskov Sørensen, Dominick V. Spracklen, Hang Su, Juha Tonttila, Siwen Wang, Jiandong Wang, Tobias Wolf-Grosse, Yongqiang Yu, Qing Zhang, Wei Zhang, Wen Zhang, Xunhua Zheng, Siqi Li, Yong Li, Putian Zhou, Markku Kulmala
- Abstrakt
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 overall 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.
- Organisation(en)
- Institut für Meteorologie und Geophysik
- Externe Organisation(en)
- University of Helsinki, LUT University, University of Copenhagen, University of Leeds, Finnish Meteorological Institute, World Meteorological Organisation, International Institute for Applied Systems Analysis, Bjerknes Centre for Climate Research, University of Tromsø - The Arctic University of Norway, Max-Planck-Institut für Chemie (Otto-Hahn-Institut), National Research Council of Italy (CNR-ISAC), Bologna, University of the Chinese Academy of Sciences, Estonian University of Life Sciences, Nansen Environmental and Remote Sensing Center, Chinese Academy of Sciences (CAS), Danish Meteorological Institute (DMI)
- Journal
- Big Earth Data
- Band
- 8
- Seiten
- 189-230
- Anzahl der Seiten
- 42
- DOI
- https://doi.org/10.1080/20964471.2024.2325019
- Publikationsdatum
- 2024
- Peer-reviewed
- Ja
- ÖFOS 2012
- 105206 Meteorologie
- Schlagwörter
- ASJC Scopus Sachgebiete
- Computers in Earth Sciences, Computer Science Applications
- Link zum Portal
- https://ucrisportal.univie.ac.at/de/publications/f902dc71-72e1-4dd0-8504-307887f2df0e