收稿日期: 2006-05-22
修回日期: 2006-10-23
网络出版日期: 2007-01-10
Applications of Data Assimilation in Air Quality Prediction
Received date: 2006-05-22
Revised date: 2006-10-23
Online published: 2007-01-10
白晓平 , 方栋 , 王芬娟 , FrancescaCostabile , 胡非 , 李红 . 资料同化在空气质量预报中的应用[J]. 地球科学进展, 2007 , 22(1) : 66 -73 . DOI: 10.11867/j.issn.1001-8166.2007.01.0066
Along with the improvement of numerical models and the enhancement of observation technology, data assimilation has become an efficient method that can further improve numerical prediction level. Since the seventies of last century, data assimilation has been used in air quality prediction, and has become a new direction in the research on the atmospheric environmental science. The meaning of data assimilation is briefly described, and the basic principle, advantages and drawbacks of Kalman filter, four-dimensional variational assimilation and nudging methods are introduced in detail. The research progress of data assimilation in air quality prediction is mainly reviewed. The existing problems and further research directions of data assimilation applied in air quality prediction are discussed.
Key words： Data assimilation; Air quality prediction.; Numerical prediction
[1]Panofsky H.Objective weather-map analysis[J]. Journal of Applled Meteorology,1949,(6):386-392.
[2]Chou Jifan. On the problems of utilizing past data in numerical weather forecasting[J]. Science in China, 1974,(6):635-644.[丑纪范.天气数值预报中使用过去资料的问题[J].中国科学,1974,(6):635-644.]
[3]Charney J,Halem M,Jastrow R. Use of incomplete historical data to infer the present state of the atmosphere[J].Atomospheric Science,1969,26:1 160-1 163.
[4]Wang Bin, Zou Xiaolei, Zhu Jiang. Data assimilation and its applications[J].PNAS,2000,97(21): 11 143-11 144.
[5]Zhu Jiang,Wang Hui,Masafumi Kamachi.The improvement made by a modified TLM in 4DVAR with a geophysical boundary layer model[J]. Advances in Atmospheric Sciences,2002,19(4):563-582.
[6]Gao Shanhong, Wu Zengmao,Xie Hongqin. The developments and applications of Kalman filters in meteorological data assimilation[J]. Advances in Earth Science,2000,15(5):571-575.[高山红,吴增茂,谢红琴.Kalman滤波在气象数据同化中的发展与应用[J].地球科学进展, 2000,15(5):571-575.]
[7]Zhu Jiang,Zhou Guangqing,Wang Hui.An adaptive variational method of sea surface temperature[J] .Chinese Science Bulletin, 2002,47(19):1 517-1 521.[朱江,周广庆,王辉.海表温度的自适应变分同化[J].科学通报,2002, 47(19):1 517-1 521.]
[8]Desalu A A, Gould L A, Schweppe F C. Dynamic estimation of air pollution[J]. IEEE Transactions on Automatic,Control, 1974,19:904-910.
[9]Fronza G, Spirito A, Tonielli A. Real-time Forecast of Air Pollution Episodes in the Venetian Region, Part 2: the Kalman Predictor[M].1979.
[10]Segers A J, Heemink A W,Verlaan M,et al. Large scale data assimilation based on RRSQRT-filters: Application on atmospheric chemistry models[C]//.Brebbia C A,eds. Proceedings Air Pollution IV. Computational Mechanics Publications, Wessex Institute of Technology, 1998:25-34.
[11]Van Loon M,Builtjes P J H, Segers A J .Data assimilation of ozone in the atmospheric transport chemistry model LOTOS[J]. Environmental Modelling & Software,2000,15:603-609.
[12]Stauffer D R, Seaman N L. Use of four-dimensional data assimilation in a limited-area mesoscale model. Part-I: Experiments with synoptic-scale data[J]. Monthly Weather Review,1990(118):1 250-1 277.
[13]Elbern H, Schmidt H. A four-dimensional variational chemistry data assimilation scheme for Eulerian chemistry transport modelling[J].Journal of Geophysical Reasearch,1999,(104):18 583-18 598.
[14]Wang Yingchun,Liu Fenghui,Zhang Xiaoling,et al. Interpretation of the nonhydrostatic mesoscale NWP products in terms of local weather phenomena and air pollution in Beijing area[J]. Quarterly Journal of Applied Meteorology,2002,13(3):312-321.[王迎春,刘凤辉,张小玲,等.北京地区中尺度非静力数值预报产品释用技术研究[J]. 应用气象学报,2002,13(3):312-321.]
[15]Zhou Shijun,Song Yu,Wu Shijie. The application of Kalman filter approach in air pollutant forecast[J].Environmental Monitoring in China,2000,16(4):50-52.[周势俊,宋煜,吴士杰.Kalman滤波法在城市空气污染预报中的应用[J].中国环境监测,2000,16(4):50-52.]
[16]Smedstad O M，O’Brien J J. Variational data assimilation and parameter estimation in an equatorial paciflc ocean model prog[J]. Oceanogaphy,1992,26:179-241.
[17]Kalman R E.A new approach to linear filtering and prediction problems[J].Journal of Basic, Engineering,Transaction of the ASME(Series D),1960,82:35-45.
[18]Kalman R E,Bucy R.New results in linear filtering and prediction problems[J]. Journal of Basic, Engineering,Transaction of the ASME(Series D),1961,83:95-108.
[19]Evensen G. Using the extended Kalman filtering with a multilayer quasti-geostrophic ocean model[J]. Journal of Geophysical Research,1992,97:17 904-17 905.
[20]Dee D P. Simplification of the Kalman filter for meteorological data assimilation[J]. Quarterly Journal of the Royal Meteorological Society,1991,117:365-384.
[21]Cohn S E, Parrish D P. The behavior of forecast error covariances for a Kalman filter in two dimensions[J].Monthlry Weather Review,1991,119:1 757-1 785.
[22]Sasaki Y. Some basic formulisms in numerical variational analysis[J].Monthly Weather Review,1970, 98(12):875-883.
[23]Lewis J M,Derber J C.The use of adjoint equations to solve a variational adjustment problem with advective constrains[J].Tellus,1985,37A:309-322.
[24]Anthes R A.Data assimilation and initialization of hurricane prediction models[J]. Journal of Atmospheric Science, 1974,31:702-719.
[25]Sistla G,Zhou N,Hao W,et al.Effects of uncertainties in meteorological inputs on Urban Airshed Model Predictions and ozone control strategies[J]. Atmospheric Environment,1996,30:2 011-2 025.
[26]Kumar N,Russel A. Comparing prognostic and diagnostic meteorological fields and their impacts on photochemical air quality modelling[J].Atmospheric Environment,1996,30:1 989-2 010.
[27]Lamprecht R, Berlowitz D. Evaluation of diagnostic and prognostic flow fields over prealpine complex terrain by comparison of the lagrangian prediction of concentrations with tracer measurements[J]. Atmospheric Environment,1998,32:1 283-1 300.
[28]Fisher B E A. COST Action 710. Final Report, Harmonisation of the Pre-processing of Meteorological Data for Atmospheric Dispersion Models[R].L-2985 European Commission, Luxembourg,EUR 18195 EN (ISBN 92-828-3302-X),1998.
[29]Scire J. A users guide for the CALMET meteorological model[EB/OL].http://www.src.com/calpuff/calpuffl.htm,2000.
[30]Seaman N L.Meteorological modelling for air-quality assessments[J]. Atmospheric Environment,2000,34:2 231-2 259.
[31]Seaman N L, Stauffer D R, Lario A M.Multiscale four-dimensional data assimilation system applied in the San Joaquin Valley during SARMAP. Part I: Modeling design and basic performance characteristics[J]. Journal of Applied Meteorology,1995,34:1 739-1 761.
[32]Michelson S A, Seaman N L. Assimilation of NEXRADVAD winds in meteorological simulations over the Northeast U.S. [J].Journal of Applied Meteorology,2000,39:367-383.
[33]Tanrikulu S, Stauffer D R, Seaman N L, et al. A field-coherence technique filed-program design for air-quality studies. Part II: Evaluation in the San Joaquin Valley[J]. Journal of Applied Meteorology,2000,39:317-334.
[34]Seaman N L,Michelson S A. Mesoscale meteorological structure of a high-ozone episode during the 1995 NARSTO-northeast study[J]. Journal of Applied Meteorology,2000,39:384-398.
[35]Seaman N L, Deng A, Hunter G K,et al. Numerical study of the influences on pollutant transport due to multiple convergence zones in the sea breezes of Cape Cod and southeastern Massachusetts[C]//The Application of Air Pollution Meteorology. 12th American Meteorological Society Conference with the Air and Waste Mange Assoc, Norfolk,VA,2002: 17-18.
[36]Seaman N L, Stauffer D R, Deng A, et al. Evaluation of a rapidly relocatable high-resolution numerical model for meteorological nowcasting based on MM5[C]//Weather Analysis and Numerical Weather Prediction. 19th American Meteorological Society and the 15th FCST Joint Conference, San Antonio, TX,2002:47-50.
[37]Egan B A, Seaman N L, Yamartino R, et al. Modeling pollutant dispersion from elevated and ground level sources affected by sea-breeze circulations produced by Cape Cod and its surroundings[C]//Application of Air Pollution Meteorology. 12th American Meteorological Society Conference, Held Jointly with the Air and Waste Mange Assoc, Norfolk, VA, 2002:11-12.
[38]Hurley P, Manins P,Lee S, et al. Year-long, high resolution, urban airshed modelling: Verification of TAPM predictions of smog and particles in Melbourne, Australia[J]. Atmospheric Environment,2003,37:1 899-1 910.
[39]Mulholland M,Seinfeld J H. Inverse air pollution modeling of urban-scale carbon monoxide emissions[J]. Atmospheric Environment,1995,29:497-516.
[40]Haas-Laursen D E,Hartley D E.Optimizing an inverse method to deduce time-varying emissions of trace gases[J]. Journal of Geophysical Research,1996,101:22 823-22 831.
[41]Chang M E,Hartley D E, Cardelino C, et al. On using inverse methods for resolving emissions with large spatial inhomogeneities[J]. Journal of Geophysical Research,1997,102 (D13):16 023-16 036.
[42]Elbern H, Schmidt H, Ebel A. Variational data assimilation for tropospheric chemistry modelling[J]. Journal of Geophysical Research,1997,102(D13): 15 967-15 985.
[43]Elbern H, Schmidt H,Talagrand O,et al. 4D-variational data assimilation with an adjoint air quality model for emission analysis[J].Environmental Modelling & Software,2000,15:539-548.
[44]Ligtmans R, Builtjes P J H, Heemink A W.An introductory study into data assimilation techniques for an atmospheric chemical transport model[J]. Transactions on Ecology and Environment,1996,(8):1 743-3 541.
[45]Kahn R A,Ogren J A,Ackerman T P,et al. Aerosol data sources and their roles within PARAGON[J]. American Meteorological Society,2004,(10):1 511-1 521.
[46]Yang Liu,Sarnat J A,Kilaru V,et al. Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing[J]. Environmental Science & Technology, 2005,39(9):3 269-3 278.
[47]Zhang X F, Heemink A W. Data assimilation in transport models[J].Applied Mathematical Modelling,1997,21:2-14.
[48]Zhang X F,Heemink A W,Janssen L H J M,et al. A computationally efficient Kalman smoother for the evaluation of the CH4 budget in Europe[J]. Applied Mathematical Modelling,1999,23:109-129.
/
| 〈 |
|
〉 |
甘公网安备62010202000687
