Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform

0585878 - ÚI 2025 GB eng J - Journal Article
Mahura, A. - Baklanov, A. - Esau, I. - et al. … Total 48 authors
Towards seamless environmental prediction – development of Pan-Eurasian EXperiment (PEEX) modelling platform.
Big Earth Data. Online 09 April 2024 (2024). ISSN 2096-4471. E-ISSN 2574-5417
R&D Projects: GA TA ČR(CZ) TO01000219
Keywords : multi-scale modelling * multi-process modelling * PEEX-MP * environmental prediction
OECD category: Meteorology and atmospheric sciences
Method of publishing: Open access
https://doi.org/10.1080/20964471.2024.2325019

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.
Permanent Link: https://hdl.handle.net/11104/0353517