中尺度天气预报模式边界层参数化方案以及近地层方案对苏州东山冬季近地层气象要素模拟的影响
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摘要
运用WRF3. 9模式并选取四种常用的边界层参数化方案(YSU、ACM2、MYJ和BL)和两种近地层方案(Eta和MM5)模拟了2015年1月16～25日苏州东山的近地层气象要素,并与东山气象站观测实验数据进行对比,评估了四种边界层参数化方案对近地层气象要素的模拟能力。同时设置了边界层参数化方案与近地层方案耦合的敏感性试验,分析两类方案的耦合对近地层气象要素模拟的影响。结果表明:①白天四种边界层方案对2 m温度的模拟差异较小,两种近地层方案的模拟结果有差异,对流混合较弱时Eta方案模拟较好,对流混合较强时MM5方案较好;夜间四种边界层方案和近地层方案均有影响,但是整个观测期间四种方案的模拟结果统计量差异较小;②无论白天还是夜间,四种边界层参数化方案模拟的2 m相对湿度均高于观测值,BL方案的模拟效果最佳,MYJ方案的模拟偏差最大;③无论白天还是夜间,四种边界层参数化方案对10 m风速的模拟均存在一定程度的高估,MYJ方案的模拟效果最好,四种方案对风向的模拟均优于对风速的模拟,白天的模拟效果整体优于夜间;④选择不同的近地层方案对风速和风向的模拟结果没有明显影响,对2 m气温模拟结果的影响小于对2 m相对湿度模拟结果的影响,BL边界层方案与MM5近地层方案耦合对近地层气象要素2 m气温和2 m相对湿度的模拟效果最好。
Four commonly used planetary boundary layer( PBL) parameterization schemes( YSU,ACM2,MYJ and BL) and two surface layer schemes( Eta and MM5) in WRF3. 9 model were used to estimate the surface values of meteorological parameters observed by Dongshan meteorological station in Suzhou city,China,from 16 to 25 January 2015. The simulation results were compared with the observational data,and the simulation ability of surface meteorological parameters by four PBL schemes was evaluated. Meanwhile,the sensitivity test on the four PBL schemes and the coupling with the two surface layer schemes was set. The influence of the coupling of the two types schemes on the simulations were also analyzed. The results reveal that the differences between the simulations of temperature at 2 m level during the daytime using four PBL schemes is negligible. In contrast to that,the results using two different surface layer schemes show large variation. The Eta scheme performs better when convection mixing is weaker,while the MM5 scheme is better when convection mixing is stronger. For the nighttime simulation,the differences between modeling results using different PBL schemes are small throughout the entire observation period. It is also found that the simulate values of relative humidity at 2 m level are all larger than the observed values,and the BL scheme performs the best while MYJ scheme has the largest deviation. The four PBL schemes used in simulations all overestimate wind speed at 10 m level,in which MYJ scheme behaves the best. The simulations of wind direction using these four PBL schemes are found better than those of wind speed,and better in the daytime than in the nighttime. The selection of the two surface layer schemes has no obvious influence on the simulation of wind speed and wind direction at 10 m level,and the selection has a smaller impact on the simulation of temperature at 2 m level than on the simulation of relative humidity at 2 m level. For the simulation of temperature and relative humidity at 2 m level,the coupling of the BL scheme and the MM5 surface layer scheme is found the best.
Four commonly used planetary boundary layer( PBL) parameterization schemes( YSU,ACM2,MYJ and BL) and two surface layer schemes( Eta and MM5) in WRF3. 9 model were used to estimate the surface values of meteorological parameters observed by Dongshan meteorological station in Suzhou city,China,from 16 to 25 January 2015. The simulation results were compared with the observational data,and the simulation ability of surface meteorological parameters by four PBL schemes was evaluated. Meanwhile,the sensitivity test on the four PBL schemes and the coupling with the two surface layer schemes was set. The influence of the coupling of the two types schemes on the simulations were also analyzed. The results reveal that the differences between the simulations of temperature at 2 m level during the daytime using four PBL schemes is negligible. In contrast to that,the results using two different surface layer schemes show large variation. The Eta scheme performs better when convection mixing is weaker,while the MM5 scheme is better when convection mixing is stronger. For the nighttime simulation,the differences between modeling results using different PBL schemes are small throughout the entire observation period. It is also found that the simulate values of relative humidity at 2 m level are all larger than the observed values,and the BL scheme performs the best while MYJ scheme has the largest deviation. The four PBL schemes used in simulations all overestimate wind speed at 10 m level,in which MYJ scheme behaves the best. The simulations of wind direction using these four PBL schemes are found better than those of wind speed,and better in the daytime than in the nighttime. The selection of the two surface layer schemes has no obvious influence on the simulation of wind speed and wind direction at 10 m level,and the selection has a smaller impact on the simulation of temperature at 2 m level than on the simulation of relative humidity at 2 m level. For the simulation of temperature and relative humidity at 2 m level,the coupling of the BL scheme and the MM5 surface layer scheme is found the best.
引文
1 Makar P A,Zhang J,Gong W,et al. Mass tracking for chemical analysis:the causes of ozone formation in southern Ontario during BAQS-met 2007[J]. Atmospheric Chemistry Physics,2010,10(22):11151-11173
2 VanCuren R,Pederson J,Lashgari A,et al. Aerosol generation and circulation in the shore zone of a large alpine lake-2-aerosol distributions over Lake Tahoe,CA[J]. Atmospheric Environment,2012,46(1):631-644
3 许鲁君,刘辉志.云贵高原洱海湖泊效应的数值模拟[J].气象学报,2015,73(4):789-802Xu Lujun,Liu Huizhi. Numerical simulation of the lake effect of Erhai in the Yunnan-Guizhou Plateau area[J]. Acta Meteorologica Sinica,2015,73(4):789-802
4 Lyons W A. The climatology and prediction of the Chicago lake breeze[J]. Journal of Applied Meteorology, 1972, 11(8):1259-1270
5 Wang L L,Zhang N,Liu Z R,et al. The influence of climate factors,meteorological conditions,and boundary-layer structure on severe haze pollution in the Beijing-Tianjin-Hebei region during January2013[J]. Advanced in Meteorology,2014(7):1-14
6 Wang Y S,Yao L,Wang L L,et al. Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China[J]. Science China-Earth Sciences,2014,57(1):14-25
7 Ji D S,Li L,Wang Y S,et al. The heaviest particulate air-pollution episodes occurred in northern China in January,2013:insights gained from observation[J]. Atmospheric Environment,2014,92:546-556
8 Sun,Y L,Jiang Q,Wang Z F,et al. Investigation of the sources and evolution processes of severe haze pollution in Beijing in January2013[J]. Journal of Geophysical Research Atmospheres,2014,119(7):4380-4398
9 Streets D G,Joshua S F,Carey J J,et al. Air quality during the2008 Beijing Olympic Games[J]. Atmospheric Environment,2007,41(3):480-492
10 Mahrt L,Vickers D. Extremely weak mixing in stable conditions[J]. Boundary-Layer Meteorology,2006,119(1):19-39
11 Banta R M,Mahrt L,Vickers D,et al. The very stable boundary layer on nights with weak low-level jets[J]. Journal of the Atmospheric Sciences,2006,64(9):3068-3090
12 Jericevic A,Vecenaj Z. Improvement of vertical diffusion analytic schemes under stable atmospheric conditions[J]. Boundary-Layer Meteorology,2009,131(2):293-307
13 Hong S Y,Noh Y,Dudhia J. A new vertical diffusion package with an explicit treatment of entrainment processes[J]. Monthly Weather Review,2006,134(9):2318-2341
14 Pleim J E. A combined local and nonlocal closure model for the atmospheric boundary layer. Part II:application and evaluation in a mesoscale meterorological model[J]. Journal of Applied Meteorology and Climatology,2007,46(9):1396-1409
15 Pleim J E. A combined local and nonlocal closure model for the atmospheric boundary layer. Part I:model description and testing[J]. Journal of Applied Meteorology and Climatology,2007,46(9):1383-1395
16 Janjic Z I. The step mountain eta coordinate:physical package[J].Monthly Weather Review,1990,118(7):1429-1443
17 Janjic Z I. The step mountain eta coordinate model:further developments of the convection,viscous sublayer,and turbulence closure schemes[J]. Monthly Weather Review,1994,122(5):927-945
18 Bougeault P,Lacarrere P. Parameterization of orography-induced turbulence in a mesobeta-scale mode[J]. Monthly Weather Review,1989,117(8):1872-1890
19 Zhang D L,Anthes C A. A high-resolution model of the planetary boundary layer—sensitivity tests and comparisons with SESAME-79data[J]. Journal of Applied Meteorology, 1982, 21(11):1594-1609
20 Shin H H,Hong S Y. Intercomparison of planetary boundary-layer parameterizations in the WRF model for a single day from CASES-99[J]. Boundary-Layer Meteorology,2011,139(2):261-281
21 Draxl C,Hahamann A N,Pena A et al. Evaluating winds and vertical wind shear from weather research and forecasting model forecasts using seven planetary boundary layer schemes[J]. Wind Energy,2014,17(1):39-55
22 王成刚,沈滢洁,罗峰,等.晴天及阴天条件下WRF模式中几种边界层参数化方案的对比分析研究[J].地球物理学报,2017,60(3):924-934Wang Chenggang,Shen Yinjie,Luo Feng,et al. Comparison and analysis of several planetary boundary layer schemes in WRF model between clear and overcast days[J]. Chinese Journal of Geophysics,2017,60(3):924-934
23 Hu X M,Nielsen-Gammon J W,Zhang F Q. Evaluation of three planetary boundary layer schemes in the WRF model[J]. Journal of Applied Meteorology and Climatology,2010,49(9):1831-1844
24 罗峰,王成刚.有云条件下WRF模式中5种边界层参数化方案的比较研究[J].科学技术与工程,2015,15(20):1671-1815Luo Feng,Wang Chenggang. The comparative study of five boundary layer schemes in WRF model in cloudy days[J]. Science Technology and Engineering,2015,15(20):1671-1815
25 王颖,张镭,胡菊,等. WRF模式对山谷城市边界层模拟能力的检验及地面气象特征分析[J].高原气象,2010,29(6):1397-1407Wang Ying,Zhang Lei,Hu Ju,et al. Verification of WRF simulation capacity on PBL characteristic and analysis of surface meteorological characteristic over complex terrain[J]. Plateau Meteorology,2010,29(6):1397-1407
26 王成刚,李颖,曹乐,等.苏州东山冬季大气边界层结构特征及其对污染物浓度的影响[J].热带气象学报,2017,33(6):912-921Wang Chenggang,Li Ying,Cao Le,et al. Analysis of atmospheric boundary layer structure and its effect on pollution concentration over Dongshan,Suzhou in winter[J]. Journal of tropical meteorology,2017,33(6):912-921
27 Lin Y L,Farley R D,Orville H D. Bulk parameterization of the snow field in a cloud model[J]. Journal of Applied Meteorology and Climatology,1983,22(6):1065-1092
28 Mlawer E J,Taubman S J,Brown P D,et al. Radiative transfer for inhomogeneous atmospheres:RRTM,a validated correlated-k model for the longwave[J]. Journal of Geophysical Research Atmospheres,1997,102(D14):16663-16682
29 Dudhia J. Numerical study of convection observed during the winter Monsoon experiment using a mesoscale two-dimensional model[J].Journal of the Atmospheric Sciences,1989,46(46):3077-3107
30 Chen F,Dudhia J. Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I:Model implementation and sensitivity[J]. Monthly Weather Review,2001,129(4):569-585
31 Chen F,Kusaka H,Bornstein R,et al. The integrated WRF/urban modelling system:development,evaluation,and applications to urban environmental problems[J]. International Journal of Climatology,2011,31(2):273-288
32 Grell G A,Devenyi D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques[J]. Geophysical Research Letters,2002,29(6):587-590
33 Chen F,Janjic Z,Mitchell K E. Impact of atmospheric surface layer parameterizations in the new land surface scheme of the NCEP mesoscale Eta model[J]. Boundary-Layer Meteorology,1997,85(3):391-421
34 Willmott C J. Some comments on the evaluation of model performance[J]. Bulletin of the American Meteorological Society,1982,63(11):1309-1313
35 Lu R,Turco R P. An integrated air pollution modeling system for urban and regional scales:2. simulations for SCAQS 1987[J].Journal of Geophysical Research,1997,102(D5):6081-6098
36 Gardner M W,Dorling S R. Statistical surface ozone models:an improved methodology to account for non-linear behavior[J]. Atmospheric Environment,2000,34(1):21-34
37 Xie B,Fung J C H,Chan A,et al. Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model[J]. Journal of Geophysical Research,2012,117:D12103
38 邱贵强,李华,张宇,等.高寒草原地区边界层参数化方案的适用性评估[J].高原气象,2013,32(1):46-55Qiu Guiqiang,Li Hua,Zhang Yu,et al. Applicability research of planetary boundary layer parameterization scheme in WRF model over the alpine grassland area[J]. Plateau Meteorology,2013,32(1):46-55
39 Bright D R,Mullen S L. The sensitivity of the numerical simulation of the southwest monsoon boundary layer to the choice of PBL turbulence parameterization in MM5[J]. Weather and Forecasting,2002,17(1):99-114
40 Jankov I,Gallus W A,Segal M,et al. The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall[J]. Weather and Forecasting,2005,20(6):1048-1060
41 Shimada S and Ohsawa T. Accuracy and characteristics of offshore wind speeds simulated by WRF[J]. Sola,2011,7(1):21-24
42 张碧辉,刘树华,LIU He-Ping,等. MYJ和YSU方案对WRF边界层气象要素模拟的影响[J].地球物理学报,2012,55(7):2239-2248Zhang Bihui,Liu Shuhua,LIU He-Ping,et al. The effect of MYJ and YSU schemes on the simulation of boundary layer meteorological factors of WRF[J]. Chinese Journal of Geophysics,2012,55(7):2239-2248
2 VanCuren R,Pederson J,Lashgari A,et al. Aerosol generation and circulation in the shore zone of a large alpine lake-2-aerosol distributions over Lake Tahoe,CA[J]. Atmospheric Environment,2012,46(1):631-644
3 许鲁君,刘辉志.云贵高原洱海湖泊效应的数值模拟[J].气象学报,2015,73(4):789-802Xu Lujun,Liu Huizhi. Numerical simulation of the lake effect of Erhai in the Yunnan-Guizhou Plateau area[J]. Acta Meteorologica Sinica,2015,73(4):789-802
4 Lyons W A. The climatology and prediction of the Chicago lake breeze[J]. Journal of Applied Meteorology, 1972, 11(8):1259-1270
5 Wang L L,Zhang N,Liu Z R,et al. The influence of climate factors,meteorological conditions,and boundary-layer structure on severe haze pollution in the Beijing-Tianjin-Hebei region during January2013[J]. Advanced in Meteorology,2014(7):1-14
6 Wang Y S,Yao L,Wang L L,et al. Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China[J]. Science China-Earth Sciences,2014,57(1):14-25
7 Ji D S,Li L,Wang Y S,et al. The heaviest particulate air-pollution episodes occurred in northern China in January,2013:insights gained from observation[J]. Atmospheric Environment,2014,92:546-556
8 Sun,Y L,Jiang Q,Wang Z F,et al. Investigation of the sources and evolution processes of severe haze pollution in Beijing in January2013[J]. Journal of Geophysical Research Atmospheres,2014,119(7):4380-4398
9 Streets D G,Joshua S F,Carey J J,et al. Air quality during the2008 Beijing Olympic Games[J]. Atmospheric Environment,2007,41(3):480-492
10 Mahrt L,Vickers D. Extremely weak mixing in stable conditions[J]. Boundary-Layer Meteorology,2006,119(1):19-39
11 Banta R M,Mahrt L,Vickers D,et al. The very stable boundary layer on nights with weak low-level jets[J]. Journal of the Atmospheric Sciences,2006,64(9):3068-3090
12 Jericevic A,Vecenaj Z. Improvement of vertical diffusion analytic schemes under stable atmospheric conditions[J]. Boundary-Layer Meteorology,2009,131(2):293-307
13 Hong S Y,Noh Y,Dudhia J. A new vertical diffusion package with an explicit treatment of entrainment processes[J]. Monthly Weather Review,2006,134(9):2318-2341
14 Pleim J E. A combined local and nonlocal closure model for the atmospheric boundary layer. Part II:application and evaluation in a mesoscale meterorological model[J]. Journal of Applied Meteorology and Climatology,2007,46(9):1396-1409
15 Pleim J E. A combined local and nonlocal closure model for the atmospheric boundary layer. Part I:model description and testing[J]. Journal of Applied Meteorology and Climatology,2007,46(9):1383-1395
16 Janjic Z I. The step mountain eta coordinate:physical package[J].Monthly Weather Review,1990,118(7):1429-1443
17 Janjic Z I. The step mountain eta coordinate model:further developments of the convection,viscous sublayer,and turbulence closure schemes[J]. Monthly Weather Review,1994,122(5):927-945
18 Bougeault P,Lacarrere P. Parameterization of orography-induced turbulence in a mesobeta-scale mode[J]. Monthly Weather Review,1989,117(8):1872-1890
19 Zhang D L,Anthes C A. A high-resolution model of the planetary boundary layer—sensitivity tests and comparisons with SESAME-79data[J]. Journal of Applied Meteorology, 1982, 21(11):1594-1609
20 Shin H H,Hong S Y. Intercomparison of planetary boundary-layer parameterizations in the WRF model for a single day from CASES-99[J]. Boundary-Layer Meteorology,2011,139(2):261-281
21 Draxl C,Hahamann A N,Pena A et al. Evaluating winds and vertical wind shear from weather research and forecasting model forecasts using seven planetary boundary layer schemes[J]. Wind Energy,2014,17(1):39-55
22 王成刚,沈滢洁,罗峰,等.晴天及阴天条件下WRF模式中几种边界层参数化方案的对比分析研究[J].地球物理学报,2017,60(3):924-934Wang Chenggang,Shen Yinjie,Luo Feng,et al. Comparison and analysis of several planetary boundary layer schemes in WRF model between clear and overcast days[J]. Chinese Journal of Geophysics,2017,60(3):924-934
23 Hu X M,Nielsen-Gammon J W,Zhang F Q. Evaluation of three planetary boundary layer schemes in the WRF model[J]. Journal of Applied Meteorology and Climatology,2010,49(9):1831-1844
24 罗峰,王成刚.有云条件下WRF模式中5种边界层参数化方案的比较研究[J].科学技术与工程,2015,15(20):1671-1815Luo Feng,Wang Chenggang. The comparative study of five boundary layer schemes in WRF model in cloudy days[J]. Science Technology and Engineering,2015,15(20):1671-1815
25 王颖,张镭,胡菊,等. WRF模式对山谷城市边界层模拟能力的检验及地面气象特征分析[J].高原气象,2010,29(6):1397-1407Wang Ying,Zhang Lei,Hu Ju,et al. Verification of WRF simulation capacity on PBL characteristic and analysis of surface meteorological characteristic over complex terrain[J]. Plateau Meteorology,2010,29(6):1397-1407
26 王成刚,李颖,曹乐,等.苏州东山冬季大气边界层结构特征及其对污染物浓度的影响[J].热带气象学报,2017,33(6):912-921Wang Chenggang,Li Ying,Cao Le,et al. Analysis of atmospheric boundary layer structure and its effect on pollution concentration over Dongshan,Suzhou in winter[J]. Journal of tropical meteorology,2017,33(6):912-921
27 Lin Y L,Farley R D,Orville H D. Bulk parameterization of the snow field in a cloud model[J]. Journal of Applied Meteorology and Climatology,1983,22(6):1065-1092
28 Mlawer E J,Taubman S J,Brown P D,et al. Radiative transfer for inhomogeneous atmospheres:RRTM,a validated correlated-k model for the longwave[J]. Journal of Geophysical Research Atmospheres,1997,102(D14):16663-16682
29 Dudhia J. Numerical study of convection observed during the winter Monsoon experiment using a mesoscale two-dimensional model[J].Journal of the Atmospheric Sciences,1989,46(46):3077-3107
30 Chen F,Dudhia J. Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I:Model implementation and sensitivity[J]. Monthly Weather Review,2001,129(4):569-585
31 Chen F,Kusaka H,Bornstein R,et al. The integrated WRF/urban modelling system:development,evaluation,and applications to urban environmental problems[J]. International Journal of Climatology,2011,31(2):273-288
32 Grell G A,Devenyi D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques[J]. Geophysical Research Letters,2002,29(6):587-590
33 Chen F,Janjic Z,Mitchell K E. Impact of atmospheric surface layer parameterizations in the new land surface scheme of the NCEP mesoscale Eta model[J]. Boundary-Layer Meteorology,1997,85(3):391-421
34 Willmott C J. Some comments on the evaluation of model performance[J]. Bulletin of the American Meteorological Society,1982,63(11):1309-1313
35 Lu R,Turco R P. An integrated air pollution modeling system for urban and regional scales:2. simulations for SCAQS 1987[J].Journal of Geophysical Research,1997,102(D5):6081-6098
36 Gardner M W,Dorling S R. Statistical surface ozone models:an improved methodology to account for non-linear behavior[J]. Atmospheric Environment,2000,34(1):21-34
37 Xie B,Fung J C H,Chan A,et al. Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model[J]. Journal of Geophysical Research,2012,117:D12103
38 邱贵强,李华,张宇,等.高寒草原地区边界层参数化方案的适用性评估[J].高原气象,2013,32(1):46-55Qiu Guiqiang,Li Hua,Zhang Yu,et al. Applicability research of planetary boundary layer parameterization scheme in WRF model over the alpine grassland area[J]. Plateau Meteorology,2013,32(1):46-55
39 Bright D R,Mullen S L. The sensitivity of the numerical simulation of the southwest monsoon boundary layer to the choice of PBL turbulence parameterization in MM5[J]. Weather and Forecasting,2002,17(1):99-114
40 Jankov I,Gallus W A,Segal M,et al. The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall[J]. Weather and Forecasting,2005,20(6):1048-1060
41 Shimada S and Ohsawa T. Accuracy and characteristics of offshore wind speeds simulated by WRF[J]. Sola,2011,7(1):21-24
42 张碧辉,刘树华,LIU He-Ping,等. MYJ和YSU方案对WRF边界层气象要素模拟的影响[J].地球物理学报,2012,55(7):2239-2248Zhang Bihui,Liu Shuhua,LIU He-Ping,et al. The effect of MYJ and YSU schemes on the simulation of boundary layer meteorological factors of WRF[J]. Chinese Journal of Geophysics,2012,55(7):2239-2248
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