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A new implementation of FLEXPART with Enviro-HIRLAM meteorological input,and a case study during a heavy air pollution event

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Big Earth Data 2024年第2期8卷 397-434页

作者： Benjamin Foreback alexander mahura Petri Clusius Carlton Xavier Metin Baykara Putian Zhou Tuomo Nieminen Victoria Sinclair Veli-Matti Kerminen Tom V.Kokkonen Simo Hakala Diego Aliaga Risto Makkonen alexander Baklanov Roman Nuterman Men Xia Chenjie Hua Yongchun Liu Markku Kulmala Pauli Paasonen Michael Boy Aerosol and Haze Laboratory Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijingChina Institute for Atmospheric and Earth System Research/Physics Faculty of ScienceUniversity of HelsinkiHelsinkiFinland Division of Nuclear Physics Department of PhysicsLund UniversityLundSweden Swedish Meteorological and Hydrological Institute(SMHI) Research DepartmentUnit of Meteorology/Environment and ClimateNorrköpingSweden Climate and Marine Sciences Department Eurasia Institute of Earth SciencesIstanbul Technical UniversityIstanbulTurkey Department of Physics Faculty of ScienceUniversity of HelsinkiHelsinkiFinland Department of Meteorology(MISU)and Bolin Centre for Climate Research Stockholm UniversityStockholmSweden Climate System Research Unit Finnish Meteorological InstituteHelsinkiFinland Science and Innovation Department World Meteorological Organization(WMO)GenevaSwitzerland Niels Bohr Institute University of CopenhagenCopenhagenDenmark Joint International Research Laboratory of Atmospheric and Earth System Sciences School of Atmospheric SciencesNanjing UniversityNanjingChina School of Engineering Science Lappeenranta-Lahti University of Technology(LUT)LappeenrantaFinland Atmospheric Modelling Centre Lahti Lahti University CampusLahtiFinland

We integrated Enviro-HIRLAM(Environment-High Resolution Limited Area Model)meteorological output into FLEXPART(FLEXible PARTicle dispersion model).A FLEXPART simulation requires meteorological input from a numerical weather prediction(NWP)*** publicly available version of FLEXPART can utilize either ECMWF(European Centre for Medium-range Weather Forecasts)Integrated Forecast System(IFS)forecast or reanalysis NWP data,or NCEP(*** Center for Environmental Prediction)Global Forecast System(GFS)forecast or reanalysis NWP *** primary benefits of using Enviro-HIRLAM are that it runs at a higher resolution and accounts for aerosol effects in meteorological *** compared backward trajectories gener-ated with FLEXPART using Enviro-HIRLAM(both with and without aerosol effects)to trajectories generated using NCEP GFS and ECMWF IFS meteorological inputs,for a case study of a heavy haze event which occurred in Beijing,China in November *** found that results from FLEXPART were considerably different when using different meteorological *** aerosol effects were included in the NWP,there was a small but noticeable differ-ence in calculated ***,when looking at potential emission sensitivity instead of simply expressing trajectories as lines,additional information,which may have been missed when looking only at trajectories as lines,can be inferred.

关键词： Atmospheric and chemical transport modelling trajectory and particle dispersion modelling severe air pollution episode FLEXPART Enviro-HIRLAM

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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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Atmospheric Trajectory and Chemical Transport Modelling for Elevated Ozone Events in Denmark

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Atmospheric and Climate Sciences 2013年第1期3卷 87-99页

作者： alexander mahura Roman Nuterman Irina Petrova Bjarne Amstrup Danish Meteorological Institute DMI Copenhagen Denmark Danish Meteorological Institute DMI Copenhagen Denmark&Tomsk State University TSU Tomsk Russia Russian State Hydrometeorological University RSHU St. Petersburg Russia&Now at University of Hamburg Max Planck Institute for Meteorology Hamburg Germany

In this study, three Danish sites having the longest (1990-2004) time-series of ozone measurements were analysed on inter-annual, monthly and diurnal cycle variability as well as elevated and lowered ozone concentration events were identified. The atmospheric trajectory (HYSPLIT) and dispersion (HIRLAM + CAMx) models were employed to study dominating atmospheric transport patterns associated with elevated events and to evaluate spatio-temporal variability of ozone specific episode and typical seasonal patterns for Denmark. It was found that generally inter-annual variability has a positive trend, and events with low ozone concentration (≤10 μg/m3) continued to diminish. On a monthly scale, the highest and lowest mean concentrations are observed in May and November-December, respectively. The elevated concentrations (≥120 μg/m3) are observed during March-September. On a diurnal cycle, it is observed mostly during 13-16 of local time, and more frequent (ten-fold) compared with nighttime-early morning hours. For ozone elevated events, several sectors (or pathways of atmospheric transport) were identified depending on the sites’ positions, showing the largest (39%) number of such events associated with the north-western sector, and lowest (13% each)—southwestern and northern sectors. For each site, less than 60 events showed very high concentrations (≥180 μg/m3). Among 12 episodes, one longest elevated episode (19-21 Jun 2000) simultaneously registered at all sites and characterized by dominating transport from the south-southwestern sector, low wind speed, clear-sky, and multiple inversions was studied using modelling tools. For this episode, both measurements and modeling (trajectory and dispersion) results showed a relatively good agreement.

关键词： Elevated Ozone Concentration Event and Episode Atmospheric Trajectory Chemical Transport Modeling HYSPLIT HIRLAM CAMx

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The Silk Road agenda of the Pan-Eurasian Experiment (PEEX) program

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Big Earth Data 2018年第1期2卷 8-35页

作者： Hanna K.Lappalainen Markku Kulmala Joni Kujansuu Tuukka Petaja alexander mahura Gerrit de Leeuw Sergej Zilitinkevich Merli Juustila Veli-Matti Kerminen Bob Bornstein Zhang Jiahua Xue Yong Qiu Yubao Liang Dong Liu Jie Guo Huadong Institute for Atmospheric and Earth System Research(INAR)/Physics University of HelsinkiHelsinkiFinland Finnish Meteorological Institute HelsinkiFinland Climate Research Programme University of TyumenTyumenRussia Institute of Remote Sensing and Digital Earth Chinese Academy of SciencesBeijingChina Aerosol and Haze Laboratory Beijing University of Chemical TechnologyBeijingChina The Joint International Research Laboratory of Atmospheric and Earth System Sciences(JirLatest) Nanjing UniversityNanjingChina College of Resources and Environment University of Chinese Academy of SciencesBeijingChina Department of Radiophysics University of Nizhny NovgorodNizhny NovgorodRussia Department of Geography Moscow State UniversityMoscowRussia Department of Meteorology and Climate Science San Jose State UniversitySan JoseCAUSA

The Silk Road Economic Belt and the 21st-Century Maritime Silk Road(B&R)aims at facilitating the twenty-first Century economic development of ***,climate change,air quality and related feedbacks are affecting the successful development of the environment and societies in the B&R geographical *** most urgent risks related to the atmospheric system,to the land system and to hydrospheric and cryospheric processes are changing climate-air quality interactions,air pollution,changing monsoon dynamics,land degradation,and the melting of Tibetan Plateau glaciers.A framework is needed in which a science and technology-based approach has the critical mass and expertise to identify the main steps toward solutions and is capable to implement this *** Pan-Eurasian Experiment(PEEX)program,initiated in 2012,aims to resolve science,technology and sustainability questions in the Northern Eurasian *** is now identifying its science agenda for the B&R *** fundamental element of the PEEX research agenda is the availability of comprehensive ground-based observations together with Earth observation *** complements the recently launched international scientific program called Digital Belt and Road(DBAR).PEEX has expertise to coordinate the ground-based observations and initiate new flagship stations,while DBAR provides a big data platform on Earth observation from China and countries along the Belt and Road *** DBAR and PEEX have joint interests and synergy expertise on monitoring on ecological environment,urbanization,cultural heritages,coastal zones,and arctic cold regions supporting the sustainable development of the Belt and Road *** this paper we identify the research themes of the PEEX related Silk Road agenda relevant to China and give an overview of the methodological requirements and present the infrastructure requirements needed to carry out large scale research program.

关键词： Silk road Economic Belt air quality land-climate feedbacks Earth observation data in situ observations multiscale modeling SMEa concept Pan-Eurasian Experiment(PEEX)program Digital Belt and road(DBa)program

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