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

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 

机构地区：[1]Aerosol and Haze Laboratory,Beijing Advanced Innovation Center for Soft Matter Science and Engineering,Beijing University of Chemical Technology,Beijing,China [2]Institute for Atmospheric and Earth System Research/Physics,Faculty of Science,University of Helsinki,Helsinki,Finland [3]Division of Nuclear Physics,Department of Physics,Lund University,Lund,Sweden [4]Swedish Meteorological and Hydrological Institute(SMHI),Research Department,Unit of Meteorology/Environment and Climate,Norrköping,Sweden [5]Climate and Marine Sciences Department,Eurasia Institute of Earth Sciences,Istanbul Technical University,Istanbul,Turkey [6]Department of Physics,Faculty of Science,University of Helsinki,Helsinki,Finland [7]Department of Meteorology(MISU)and Bolin Centre for Climate Research,Stockholm University,Stockholm,Sweden [8]Climate System Research Unit,Finnish Meteorological Institute,Helsinki,Finland [9]Science and Innovation Department,World Meteorological Organization(WMO),Geneva,Switzerland [10]Niels Bohr Institute,University of Copenhagen,Copenhagen,Denmark [11]Joint International Research Laboratory of Atmospheric and Earth System Sciences,School of Atmospheric Sciences,Nanjing University,Nanjing,China [12]School of Engineering Science,Lappeenranta-Lahti University of Technology(LUT),Lappeenranta,Finland [13]Atmospheric Modelling Centre Lahti,Lahti University Campus,Lahti,Finland

出　　处：《Big Earth Data》2024年第2期397-434,共38页地球大数据（英文）

基　　金：the Jenny and Antti Wihuri Foundation project,with the grant for“Air pollution cocktail in Gigacity”;Funding was also received from the Research Council of Finland(formerly the Academy of Finland,AoF)project 311932 and applied towards this project;Partially,funding included contribution from EU Horizon 2020 CRiceS project“Climate relevant interactions and feedbacks:the key role of sea ice and snow in the polar and global climate system”under grant agreement No 101003826;and AoF project ACCC“The Atmosphere and Climate Competence Center”under grant agreement No 337549.

摘　　要：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)model.The 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(U.S.National Center for Environmental Prediction)Global Forecast System(GFS)forecast or reanalysis NWP data.The primary benefits of using Enviro-HIRLAM are that it runs at a higher resolution and accounts for aerosol effects in meteorological fields.We 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 2018.We found that results from FLEXPART were considerably different when using different meteorological inputs.When aerosol effects were included in the NWP,there was a small but noticeable differ-ence in calculated trajectories.Moreover,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 

分 类 号：P45[天文地球—大气科学及气象学]