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Eurasian Winter Cooling: Intercomparison of Reanalyses and CMIP5 Data Sets

Atmospheric and Oceanic Science Letters 2013年第5期6卷 324-331页

作者： Stephen OUTTEN Richard DAVY igor esau Nansen Environmental and Remote Sensing Centre

A cooling trend in wintertime surface air temperature over continental Eurasia has been identified in reanalysis and the Coupled Model Inter-comparison Project phase 5(CMIP5)‘historical’simulations over the period 1989–*** the authors have shown that this cooling trend is related to changes in Arctic sea-ice around the Barents-Kara *** study illustrates a consistent spatial and temporal structure of the wintertime temperature variability centered over Asia using state-of-the-art reanalyses and global climate model *** findings indicate that there is a physical basis for seasonal predictions of near-surface temperatures over continental Asia based on changes to the ice-cover in the Barents-Kara seas.

关键词： climate change climate simulation atmospheric tele-connections

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Contrasting Vertical Structure of Recent Arctic Warming in Different Data Sets

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Atmospheric and Climate Sciences 2013年第1期3卷 1-5页

作者： igor esau Vladimir Alexeev Irina Repina Svetlana Sorokina A. M. Obukhov Institute for Atmospheric Physics Moscow Russia Centre for Climate Dynamics (SKD) Bergen Norway International Arctic Research Centre University of Alaska Fairbanks USA Nansen Environmental and Remote Sensing Centre G. C. Rieber Climate Institute Bergen Norway

Arctic region is experiencing strong warming and related changes in the state of sea ice, permafrost, tundra, marine environment and terrestrial ecosystems. These changes are found in any climatological data set comprising the Arctic region. This study compares the temperature trends in several surface, satellite and reanalysis data sets. We demonstrate large differences in the 1979-2002 temperature trends. Data sets disagree on the magnitude of the trends as well as on their seasonal, zonal and vertical pattern. It was found that the surface temperature trends are stronger than the trends in the tropospheric temperature for each latitude band north of 50?N for each month except for the months during the ice-melting season. These results emphasize that the conclusions of climate studies drawn on the basis of a single data set analysis should be treated with caution as they may be affected by the artificial biases in data.

关键词： Arctic Warming Data Set Intercomparison Atmospheric Vertical Structure

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

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Big Earth Data 2024年第2期8卷 189-230页

作者： Alexander Mahura Alexander Baklanov Risto Makkonen Michael Boy Tuukka Petäjä Hanna KLappalainen 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 Monks Mads Bruun Poulsen Steffen M.Noe Yuliia Palamarchuk Benjamin Foreback Petri Clusiu Till Andreas Soya Rasmussen Jun She Jens Havskov Sørensen Dominick 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 Faculty of Science Institute for Atmospheric and Earth System Research(INAR)/PhysicsUniversity of Helsinki(UHEL)HelsinkiFinland Science and Innovation Department World Meteorological Organization(WMO)GenevaSwitzerland Niels Bohr Institute University of CopenhagenCopenhagenDenmark Climate System Research Finnish Meteorological Institute(CSR-FMI)HelsinkiFinland School of Engineering Sciences Lappeenranta University of TechnologyLappeenrantaFinland Institute for Climate and Atmospheric Science School of Earth and EnvironmentUniversity of LeedsLeedsUK Biodiversity and Natural Resources Program International Institute for Applied Systems Analysis(IIASA)LaxenburgAustria Department of Physics and Technology UiT-The Arctic University of NorwayTromsoNorway Nansen Environmental and Remote Sensing Center(NERSC) BergenNorway Atmospheric Composition Finnish Meteorological Institute(AC-FMI)HelsinkiFinland Norwegian Institute for Air Research(NILU) KjellerNorway LAGEO Institute of Atmospheric PhysicsChinese Academy of Sciences(IAP-CAS)BeijingChina Max Planck Institute for Chemistry(MPI-Chem) MainzGermany Institute of Atmospheric Sciences and Climate National Research Council of Italy(CNR-15SAC)BolognaItaly Institute of Geographic Sciences and Natural Resources Research(IGSNRR) Chinese Academy of Sciences(CAS)BeijingChina Faculty of Science Helsinki Institute of Sustainability Science(HELSUS)University of Helsinki(UHEL)HelsinkiFinland Atmospheric Research Centre of Eastern Finland Finnish Meteorological Institute(ARCEF-FMI)KuopioFinland Institute of Atmospheric Physics Chinese Academy of Sciences(IAP-CAS)BeijingChina Department of Plant Physiology Estonian University of Life Sciences(EULS)Institute of Agricultural and Environmental Sciences(IAES)TartuEstonia Danish Meteorological Institute(DMI) CopenhagenDenmark State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry(LAPC) Institute of Atmospheric Physics(IAP)Chinese Academy of Sciences(CAS)BeijingChina Uni

The Pan-Eurasian Experiment Modelling Platform(PEEX-MP)is one of the key blocks of the PEEX Research *** PEEX MP has more than 30 models and is directed towards seamless envir-onmental *** main focus area is the Arctic-boreal regions and *** 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 physicalchemicalbiological processes at different spatial and temporal scales and *** 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 *** employed high-performance com-puting facilities,capabilities,and PEEX dataflow for modelling results are *** virtual research platforms(PEEXView,Virtual Research Environment,Web-based Atlas)for handling PEEX modelling and observational results are *** over-all approach allows us to understand better physical-chemicalbiological processes,Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks,impact,consequences,*** population,envir-onment and climate in the PEEX *** work was also one of the last projects of *** Zilitinkevich,who passed away on 15 February *** 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.

关键词： Multi-scale and-processes modelling concept seamless coupling high-performance computing data infrastructure virtual research platforms

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