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 cove...
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Taylor & Francis
2024
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Online Access: | https://hdl.handle.net/10037/33786 https://doi.org/10.1080/20964471.2024.2325019 |
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ftunivtroemsoe:oai:munin.uit.no:10037/33786 2024-09-09T19:26:37+00:00 Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform Mahura, Alexander Baklanov, Alexander Makkonen, Risto Boy, Michael Petäjä, Tuukka Lappalainen, Hanna K. Nuterman, Roman Kerminen, Veli-Matti Arnold, Stephen R. Jochum, Markus Shvidenko, Anatoly Esau, Igor Sofiev, Mikhail Stohl, Andreas Aalto, Tuula Bai, Jianhui Chen, Chuchu Cheng, Yafang Drofa, Oxana Huang, Mei Järvi, Leena Kokkola, Harri Kouznetsov, Rostislav Li, Tingting Malguzzi, Piero Monks, Sarah Poulsen, Mads Bruun Noe, Steffen M. Palamarchuk, Yuliia Foreback, Benjamin Clusius, Petri Rasmussen, Till Andreas Soya She, Jun Sørensen, Jens Havskov Spracklen, Dominick Su, Hang Tonttila, Juha Wang, Siwen Wang, Jiandong Wolf, Tobias Yu, Yongqiang Zhang, Qing Zhang, Wei Zhang, Wen Zheng, Xunhua Li, Siqi Li, Yong Zhou, Putian Kulmala, Markku 2024-04-09 https://hdl.handle.net/10037/33786 https://doi.org/10.1080/20964471.2024.2325019 eng eng Taylor & Francis Big Earth Data Norges forskningsråd: 322317 Mahura, Baklanov, Makkonen, Boy, Petäjä, Lappalainen, Nuterman, Kerminen, Arnold, Jochum, Shvidenko, Esau, Sofiev, Stohl, Aalto, Bai, Chen, Cheng, Drofa, Huang, Järvi, Kokkola, Kouznetsov, Li, Malguzzi, Monks, Poulsen, Noe, Palamarchuk, Foreback, Clusius, Rasmussen, She, Sørensen, Spracklen, Su, Tonttila, Wang, Wang, Wolf, Yu, Zhang, Zhang, Zhang, Zheng, Li, Li, Zhou, Kulmala. Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform. Big Earth Data. 2024;8:189-230 FRIDAID 2266981 doi:10.1080/20964471.2024.2325019 2096-4471 2574-5417 https://hdl.handle.net/10037/33786 Attribution 4.0 International (CC BY 4.0) openAccess Copyright 2024 The Author(s) https://creativecommons.org/licenses/by/4.0 Journal article Tidsskriftartikkel Peer reviewed publishedVersion 2024 ftunivtroemsoe https://doi.org/10.1080/20964471.2024.2325019 2024-06-18T23:58:13Z 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. Article in Journal/Newspaper Arctic University of Tromsø: Munin Open Research Archive Arctic Big Earth Data 8 2 189 230 |
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Open Polar |
collection |
University of Tromsø: Munin Open Research Archive |
op_collection_id |
ftunivtroemsoe |
language |
English |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Mahura, Alexander Baklanov, Alexander Makkonen, Risto Boy, Michael Petäjä, Tuukka Lappalainen, Hanna K. Nuterman, Roman Kerminen, Veli-Matti Arnold, Stephen R. Jochum, Markus Shvidenko, Anatoly Esau, Igor Sofiev, Mikhail Stohl, Andreas Aalto, Tuula Bai, Jianhui Chen, Chuchu Cheng, Yafang Drofa, Oxana Huang, Mei Järvi, Leena Kokkola, Harri Kouznetsov, Rostislav Li, Tingting Malguzzi, Piero Monks, Sarah Poulsen, Mads Bruun Noe, Steffen M. Palamarchuk, Yuliia Foreback, Benjamin Clusius, Petri Rasmussen, Till Andreas Soya She, Jun Sørensen, Jens Havskov Spracklen, Dominick Su, Hang Tonttila, Juha Wang, Siwen Wang, Jiandong Wolf, Tobias Yu, Yongqiang Zhang, Qing Zhang, Wei Zhang, Wen Zheng, Xunhua Li, Siqi Li, Yong Zhou, Putian Kulmala, Markku |
spellingShingle |
Mahura, Alexander Baklanov, Alexander Makkonen, Risto Boy, Michael Petäjä, Tuukka Lappalainen, Hanna K. Nuterman, Roman Kerminen, Veli-Matti Arnold, Stephen R. Jochum, Markus Shvidenko, Anatoly Esau, Igor Sofiev, Mikhail Stohl, Andreas Aalto, Tuula Bai, Jianhui Chen, Chuchu Cheng, Yafang Drofa, Oxana Huang, Mei Järvi, Leena Kokkola, Harri Kouznetsov, Rostislav Li, Tingting Malguzzi, Piero Monks, Sarah Poulsen, Mads Bruun Noe, Steffen M. Palamarchuk, Yuliia Foreback, Benjamin Clusius, Petri Rasmussen, Till Andreas Soya She, Jun Sørensen, Jens Havskov Spracklen, Dominick Su, Hang Tonttila, Juha Wang, Siwen Wang, Jiandong Wolf, Tobias Yu, Yongqiang Zhang, Qing Zhang, Wei Zhang, Wen Zheng, Xunhua Li, Siqi Li, Yong Zhou, Putian Kulmala, Markku Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform |
author_facet |
Mahura, Alexander Baklanov, Alexander Makkonen, Risto Boy, Michael Petäjä, Tuukka Lappalainen, Hanna K. Nuterman, Roman Kerminen, Veli-Matti Arnold, Stephen R. Jochum, Markus Shvidenko, Anatoly Esau, Igor Sofiev, Mikhail Stohl, Andreas Aalto, Tuula Bai, Jianhui Chen, Chuchu Cheng, Yafang Drofa, Oxana Huang, Mei Järvi, Leena Kokkola, Harri Kouznetsov, Rostislav Li, Tingting Malguzzi, Piero Monks, Sarah Poulsen, Mads Bruun Noe, Steffen M. Palamarchuk, Yuliia Foreback, Benjamin Clusius, Petri Rasmussen, Till Andreas Soya She, Jun Sørensen, Jens Havskov Spracklen, Dominick Su, Hang Tonttila, Juha Wang, Siwen Wang, Jiandong Wolf, Tobias Yu, Yongqiang Zhang, Qing Zhang, Wei Zhang, Wen Zheng, Xunhua Li, Siqi Li, Yong Zhou, Putian Kulmala, Markku |
author_sort |
Mahura, Alexander |
title |
Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform |
title_short |
Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform |
title_full |
Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform |
title_fullStr |
Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform |
title_full_unstemmed |
Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform |
title_sort |
towards seamless environmental prediction–development of pan-eurasian experiment (peex) modelling platform |
publisher |
Taylor & Francis |
publishDate |
2024 |
url |
https://hdl.handle.net/10037/33786 https://doi.org/10.1080/20964471.2024.2325019 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
Big Earth Data Norges forskningsråd: 322317 Mahura, Baklanov, Makkonen, Boy, Petäjä, Lappalainen, Nuterman, Kerminen, Arnold, Jochum, Shvidenko, Esau, Sofiev, Stohl, Aalto, Bai, Chen, Cheng, Drofa, Huang, Järvi, Kokkola, Kouznetsov, Li, Malguzzi, Monks, Poulsen, Noe, Palamarchuk, Foreback, Clusius, Rasmussen, She, Sørensen, Spracklen, Su, Tonttila, Wang, Wang, Wolf, Yu, Zhang, Zhang, Zhang, Zheng, Li, Li, Zhou, Kulmala. Towards seamless environmental prediction–development of Pan-Eurasian EXperiment (PEEX) modelling platform. Big Earth Data. 2024;8:189-230 FRIDAID 2266981 doi:10.1080/20964471.2024.2325019 2096-4471 2574-5417 https://hdl.handle.net/10037/33786 |
op_rights |
Attribution 4.0 International (CC BY 4.0) openAccess Copyright 2024 The Author(s) https://creativecommons.org/licenses/by/4.0 |
op_doi |
https://doi.org/10.1080/20964471.2024.2325019 |
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Big Earth Data |
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2 |
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