黄东海大气边界层高度时空变化特征
|
摘要
海洋大气边界层高度对于污染物的扩散、海气能量的交换以及海雾的产生和海上层云、积云对流的发展都有着重要的影响,本文利用2005～2008年大连、青岛和台州5325个高分辨率L波段二次测风雷达探空资料、地面观测资料以及再分析资料,对沿海台站以及整个黄东海边界层高度时空变化特征进行了分析,主要结论如下:
(1)青岛和台州傍晚的边界层高度略高于清晨,多为稳定和中性状态,青岛在春季稳定边界层最多,与4～7月的季节性逆温相对应;台州稳定边界层分布在秋冬季节,受地面辐射逆温影响,并且逆温高度要高于青岛。
(2)青岛边界层高度存在日变化,在01、07、13和19LST四个时刻的计算结果中,午后13LST最高,傍晚19LST要高于清晨,高度变化程度介于内陆和海洋之间;通过小波分析发现,九月边界层高度日变化最为显著,这是由于7、8月份青岛盛行偏南风,受到海洋的调节,昼夜温差减小,同时7、8月多云和阴雨天气较多,热力因素对边界层的日变化影响明显减小,边界层的日变化减弱;通过典型天气的个例分析发现,热力对流占优势时边界层高度日变化比动力剪切占优势时明显。
(3)分别用位温梯度法和干绝热法计算混合层高度,与观测的正午边界层高度对比,干绝热法计算结果更接近实际观测值;通过比较,沿海台站的边界层高度的季节变化与内陆台站不同,在夏季(6月)最低,秋季(9、10月)最高。在沿海台站,春、夏季海气温差小甚至为负值,下垫面相对稳定,浮力热通量最小,约920 hPa暖平流导致的低层季节性稳定大气层的建立以及夏季小的风切变都使得边界层高度在春、夏季节较低;相反的,在秋冬季节,下垫面不稳定,浮力热通量大,以及大的风剪切都有利于湍流的发展,形成更高的边界层。此外,台州秋冬季节近地面辐射逆温对当日混合层的发展没有影响;
(4)通过小波分析,发现沿海台站边界层高度有显著的2～4天天气尺度振荡,10～20天准双周振荡以及30～60天的准40天振荡。天气尺度周期和准双周振荡的显著时域在春秋季节,台州较另外两个台站约延迟一个月;大连和青岛准40天振荡在夏季最为明显,而台州在1、2月最明显,说明这种季节内的振荡与地域分布有关;
(5)黄东海大部分海区边界层高度季节变化呈现夏季低、冬季高的单峰结构,和东高西低、南高北低的空间分布。与陆地边界层高度的季节变化主要收到太阳辐射强度的影响不同,在海洋上空,由于海气温差和风速的季节变化,从而产生与陆地相反的感热通量和潜热通量的季节变化,是海洋上空大气边界层高度季节变化与陆地相反的主要原因。边界层高度在11、12月份有明显的东西分布,而在夏季(6、7月)主要表现为南北分布。边界层高度季节变化在黄海北部最为明显,在东海海域季节变化约700m,黄海海域可达约1000m。
The Atmospheric Boundary Layer Height (ABLH) over Sea can have an important influence on the spread of pollution, the exchange between oceanic and atmospheric energy, the generation of sea fog, and the development of cumulus convection. In this paper, we analyzed the temporal and spatial variation of ABLH using the daily high-resolution L-band radar sounding data of Dalian Qingdao and Taizhou from 2005 to 2008. The main conclusions are as follows.
(1) The boundary height in the evening in Qingdao and Taizhou is a little higher than that in the morning, and they are mostly in a stable and neutral condition. As for Qingdao, the highest ABLH occurs in the spring, which is related to the April-to-July seasonal inversion. As for Taizhou, the stable boundary layer occurs in the fall and winter, and it is influenced by the radiation inversion with an inversional height higher than that of Qingdao. However, the convectional boundary layer over Taizhou most occurs in summer, for it is influenced by the seasonal variation of the time of sunset and sunrise.
(2) On the daily variation of ABLH of Qingdao, among the results of 01, 07, 13 and 19 LST, the highest boundary layer occurred at 13 LST, while the 19 LST one was a little higher than that of early morning, and the amplitude was situated between the land and the ocean. Wavelet analyses show that the daily variation of boundary layer is most dominant in September, which is because the prevailing wind in July and August in Qingdao is south wind and the temperature difference during day and night is decreased due to the effect of the ocean. Meanwhile, there is more cloudy and rainy weather in July and August, so the daily variation accounted for by thermal factors is decreased. Through the analyses of typical cases, the ABLH which was caused mainly by convection was found to be higher than that was caused mainly by dynamic shears.
(3) The dry adiabatic method (DAM) and potential temperature gradient method (TGM) were both used to calculate the height of mixing layer. Compared with observational noon boundary layer height, the DAM is closer to the real. The seasonal variation of coastal stations, which is different from that of inland stations, has a lowest boundary layer in summer and a highest in fall. The boundary layer height of coastal stations in fall and winter is similar to that of the inland stations, but significantly lower in spring and summer. In spring, the seasonal stable stratification is the main factor of preventing the development of turbulence. In summer, due to the effect of the ocean, the temperature difference between day and night at coastal stations are obviously less than inland, resulting a lower mixing layer height. In that of Taizhou, the boundary layer height is lower due to the descend airflow caused by subtropical high; However, in the fall and winter, the prevailing wind is north wind with dry air mass from mainland; the daily variation caused by thermal factors increases, and the strengthened wind shear is also good for the development of turbulence; they are all contributing factors to higher boundary layer height; In fall and winter, the radiation inversion contributes less to the development of the mixing layer.
(4) Wavelet analyses found that the ABLH at coastal stations have a 2-4 day weather scale oscillation, 10-20 day quasi-two-week oscillation, and 30-60 day quasi-40-day oscillation. The dominant time of the former two is the spring and fall. Taizhou is later than the other two stations by 1 month. The quasi-40-day oscillation in Dalian and Qingdao was dominant in summer, while winter for Taizhou. So the intraseasonal oscillation is regionally different.
(5) The ABLH of the Yellow-East China Sea has significant seasonal variation -- the lowest in the summer and the highest in the autumn, its space distribution is lower in the northwest and higher in the southeast. The most important influence on the seasonal variation of ocean ABLH is SST-SAT and wind seasonal variations, which is different from the inland ABLH. Deeply exposed to this influence, the sensible and latent heat fluxes also make the same changes, and have an opposite phase compared to those inland. The east-west distribution of ABLH in the Yellow Sea is most obvious in November and December, significant north-south distribution of ABLH is obvious in the summer. The region which has the most distinct seasonal variation is the north yellow sea, which has a boundary layer up to 1000m, in contrast with the East China Sea with 700m boundary layer height.
(1)青岛和台州傍晚的边界层高度略高于清晨,多为稳定和中性状态,青岛在春季稳定边界层最多,与4～7月的季节性逆温相对应;台州稳定边界层分布在秋冬季节,受地面辐射逆温影响,并且逆温高度要高于青岛。
(2)青岛边界层高度存在日变化,在01、07、13和19LST四个时刻的计算结果中,午后13LST最高,傍晚19LST要高于清晨,高度变化程度介于内陆和海洋之间;通过小波分析发现,九月边界层高度日变化最为显著,这是由于7、8月份青岛盛行偏南风,受到海洋的调节,昼夜温差减小,同时7、8月多云和阴雨天气较多,热力因素对边界层的日变化影响明显减小,边界层的日变化减弱;通过典型天气的个例分析发现,热力对流占优势时边界层高度日变化比动力剪切占优势时明显。
(3)分别用位温梯度法和干绝热法计算混合层高度,与观测的正午边界层高度对比,干绝热法计算结果更接近实际观测值;通过比较,沿海台站的边界层高度的季节变化与内陆台站不同,在夏季(6月)最低,秋季(9、10月)最高。在沿海台站,春、夏季海气温差小甚至为负值,下垫面相对稳定,浮力热通量最小,约920 hPa暖平流导致的低层季节性稳定大气层的建立以及夏季小的风切变都使得边界层高度在春、夏季节较低;相反的,在秋冬季节,下垫面不稳定,浮力热通量大,以及大的风剪切都有利于湍流的发展,形成更高的边界层。此外,台州秋冬季节近地面辐射逆温对当日混合层的发展没有影响;
(4)通过小波分析,发现沿海台站边界层高度有显著的2～4天天气尺度振荡,10～20天准双周振荡以及30～60天的准40天振荡。天气尺度周期和准双周振荡的显著时域在春秋季节,台州较另外两个台站约延迟一个月;大连和青岛准40天振荡在夏季最为明显,而台州在1、2月最明显,说明这种季节内的振荡与地域分布有关;
(5)黄东海大部分海区边界层高度季节变化呈现夏季低、冬季高的单峰结构,和东高西低、南高北低的空间分布。与陆地边界层高度的季节变化主要收到太阳辐射强度的影响不同,在海洋上空,由于海气温差和风速的季节变化,从而产生与陆地相反的感热通量和潜热通量的季节变化,是海洋上空大气边界层高度季节变化与陆地相反的主要原因。边界层高度在11、12月份有明显的东西分布,而在夏季(6、7月)主要表现为南北分布。边界层高度季节变化在黄海北部最为明显,在东海海域季节变化约700m,黄海海域可达约1000m。
The Atmospheric Boundary Layer Height (ABLH) over Sea can have an important influence on the spread of pollution, the exchange between oceanic and atmospheric energy, the generation of sea fog, and the development of cumulus convection. In this paper, we analyzed the temporal and spatial variation of ABLH using the daily high-resolution L-band radar sounding data of Dalian Qingdao and Taizhou from 2005 to 2008. The main conclusions are as follows.
(1) The boundary height in the evening in Qingdao and Taizhou is a little higher than that in the morning, and they are mostly in a stable and neutral condition. As for Qingdao, the highest ABLH occurs in the spring, which is related to the April-to-July seasonal inversion. As for Taizhou, the stable boundary layer occurs in the fall and winter, and it is influenced by the radiation inversion with an inversional height higher than that of Qingdao. However, the convectional boundary layer over Taizhou most occurs in summer, for it is influenced by the seasonal variation of the time of sunset and sunrise.
(2) On the daily variation of ABLH of Qingdao, among the results of 01, 07, 13 and 19 LST, the highest boundary layer occurred at 13 LST, while the 19 LST one was a little higher than that of early morning, and the amplitude was situated between the land and the ocean. Wavelet analyses show that the daily variation of boundary layer is most dominant in September, which is because the prevailing wind in July and August in Qingdao is south wind and the temperature difference during day and night is decreased due to the effect of the ocean. Meanwhile, there is more cloudy and rainy weather in July and August, so the daily variation accounted for by thermal factors is decreased. Through the analyses of typical cases, the ABLH which was caused mainly by convection was found to be higher than that was caused mainly by dynamic shears.
(3) The dry adiabatic method (DAM) and potential temperature gradient method (TGM) were both used to calculate the height of mixing layer. Compared with observational noon boundary layer height, the DAM is closer to the real. The seasonal variation of coastal stations, which is different from that of inland stations, has a lowest boundary layer in summer and a highest in fall. The boundary layer height of coastal stations in fall and winter is similar to that of the inland stations, but significantly lower in spring and summer. In spring, the seasonal stable stratification is the main factor of preventing the development of turbulence. In summer, due to the effect of the ocean, the temperature difference between day and night at coastal stations are obviously less than inland, resulting a lower mixing layer height. In that of Taizhou, the boundary layer height is lower due to the descend airflow caused by subtropical high; However, in the fall and winter, the prevailing wind is north wind with dry air mass from mainland; the daily variation caused by thermal factors increases, and the strengthened wind shear is also good for the development of turbulence; they are all contributing factors to higher boundary layer height; In fall and winter, the radiation inversion contributes less to the development of the mixing layer.
(4) Wavelet analyses found that the ABLH at coastal stations have a 2-4 day weather scale oscillation, 10-20 day quasi-two-week oscillation, and 30-60 day quasi-40-day oscillation. The dominant time of the former two is the spring and fall. Taizhou is later than the other two stations by 1 month. The quasi-40-day oscillation in Dalian and Qingdao was dominant in summer, while winter for Taizhou. So the intraseasonal oscillation is regionally different.
(5) The ABLH of the Yellow-East China Sea has significant seasonal variation -- the lowest in the summer and the highest in the autumn, its space distribution is lower in the northwest and higher in the southeast. The most important influence on the seasonal variation of ocean ABLH is SST-SAT and wind seasonal variations, which is different from the inland ABLH. Deeply exposed to this influence, the sensible and latent heat fluxes also make the same changes, and have an opposite phase compared to those inland. The east-west distribution of ABLH in the Yellow Sea is most obvious in November and December, significant north-south distribution of ABLH is obvious in the summer. The region which has the most distinct seasonal variation is the north yellow sea, which has a boundary layer up to 1000m, in contrast with the East China Sea with 700m boundary layer height.
引文
陈长和,王海啸,黄建国等.城市气溶胶的辐射效应对混合层发展的影响.科学通报, 1993, 38(15): 1399~1402.
陈炯,王建捷.北京地区夏季边界层结构日变化的高分辨模拟对比.应用气象学报,2006,17(4):403~411.
程水源,张宝宁,白天雄等.北京地区大气混合层高度的研究及气象特征.环境科学丛刊, 1990,13(4):46 ~52.
程水源,张宝宁,李现丽.用清晨探空曲线确定混合层高度的研究.环境科学丛刊,1990,13(3):76~80.
程水源,席德立,张宝宁等.大气混合层高度的确定与计算方法研究.中国环境科学,1997,17(6):512~515.
范绍佳,Wang Qing,邓茂芝,汪华莉.北冰洋春夏季海洋大气边界层特征的初步研究.中山大学学报(自然科学版),2002,41(1):91~94.
付秀华,常用边界层高度计算方法比较.电力环境保护,1989,5(3):24~29.
葛哲学,沙威.小波分析理论与MATLAB R2007实现.北京:电子工业出版社. 2007.
谷良雷,胡泽勇,吕世华,姚济敏.敦煌和酒泉夏季晴天和阴天边界层气象要素特征分析.干旱区地理,2007,30(6):871~878.
胡非,洪钟祥,雷孝恩.大气边界层和大气环境研究进展.大气科学, 2003,27(4):712~727.
胡基福.气象统计原理与方法[M].青岛:青岛海洋大学出版社,1996:235.
梁汉明,董保群,彭贤安,田广生.珠江三角洲地区大气混合层特征分析.气象,18(7):7~11.
廖国莲.大气混合层厚度的计算方法及影响因子.中山大学研究生学刊(自然科学、医学版),2005,26(4):66~73.
柳艳菊,丁一汇.南海季风爆发前后大气层结和混合层的演变特征.气候与环境研究,2000,5(4) :460.
孟庆珍,冯艺.成都大气混会层厚度的计算和分析.成都气象学院学报,1996,II:73~81.
孟庆珍,朱炳省.重庆市大气混合层厚度的计算和分析.成都气象学院学报,1999,14(2):163~170.
盛裴轩,毛节泰,李建国等.大气物理学.北京:北京大学出版社,2003:239.
史宝忠,郑方成,曹国良.对大气混合层高度确定方法的比较分析.西安建筑科技大学学报,1997,29(2):131~141.
王海龙,张镭,陈长和等.兰州市东部地区冬季低空风场和温度场分析.兰州大学学报(自然科学版),1999,35(4):121~122.
王式功,姜大膀,杨德保等.兰州市区最大混合层厚度变化特征分析.高原气象,2000,19 (3):367.
王晓丽,张苏平,张晓梅.青岛市水平能见度变化特征及气象影响因子分析.气象科学,2008,28(增刊):31~36.
王珍珠,李炬,钟志庆,刘东,周军.激光雷达探测北京城区夏季大气边界层.应用光学,2008,29(1):96~100.
吴祖常,董保群.我国陆域大气最大混合层厚度的地理分布与季节变化.科技通报,1998,14(3):158~163.
徐芙蓉,施介宽.混合层高度变化趋势及其代表值的探讨.东华大学学报(自然科学版),2003,29(4):99~102.
杨勇杰,谈建国,郑有飞,陈舜华.上海市近1 5 a大气稳定度和混合层厚度的研究.气象科学,2006,26(5):536~541.
叶堤,王飞,陈德蓉.重庆市多年大气混合层厚度变化特征及其对空气质量的影响分析.气象与环境学报,2008,24(4):41~44.
盂庆珍.重庆11 a来大气混合层厚度研究.重庆环境科学,1994,16(4):12~16.
曾智华.大气混合层高度的模式计算和分析.高原气象,2004,23(3):368~373.
张海鹰,刘元海,林奇昌.声雷达探测边界层高度的研究.齐齐哈尔师范学院学报(自然科学版),1994,14(4):43~47.
张美根,韩志伟.复杂地形对对流混合层的影响.气候与环境研究,1998,3(2):122.
张苏平,杨育强,王新功,魏建苏.低层大气季节变化及与黄海雾季的关系.中国海洋大学学报,2008,38(5):689~698.
张苏平.黄海海雾季节变化特殊性形成机理的研究:[博士学位论文].青岛:中国海洋大学,2008.
张鑫,蔡旭晖,柴发合.北京市秋季大气边界层结构与特征分析.北京大学学报(自然科学版),2006,42(2):220~225.
周颖.贵阳市混合层高度的研究.贵州环保科技,1997,4:37~40.
朱乾根,林锦瑞,寿绍文等.天气学原理与方法.北京:气象出版社.2007.
Arakawa A., and W. H. Schubert. Interaction of a cumulus cloud ensemble with the large-scale environment, part I. Atmos. Sci., 1974, 31, 674~701.
Brian Medeiros, AlexhallL, Bjorn Stevens. What Controls the Mean Depth of the PBL?. Journal of Climate, 2005, 18:3157~3172.
Cao Guangxia, Thomas W, Giambelluca, Duane E, Stevens and Thomnas A. Schroeder. Inversion Variability in the Hawaiian Trade Wind Regime. Journal of Climate.2007, (20):1145~1160.
Deardorff, J. W. Parameterization of the planetary boundary layer for use in general circulation models. Mon. Wea. Rev., 1972, 100:93~106.
Holtslag, A. A. M., and F. T. M. Nieuwstadt. Scaling the atmospheric boundary layer. Bound.-Layer Meteor., 1986, 36:201~209.
Holzworth, George C. Estimates of mean maximum mixing depth s in the Contiguous United States. Mon. Wea. Rev., 1964, 92:235~242.
Konor, C. S., G. C. Boezio, C. R. Mechoso, and A. Arakawa. Parameterization of PBL processes in an atmospheric general circulation model: Description and preliminary assessment. Mon. Wea. Rev., 2009, 137, 1061~1082.
Leipper D F. Fog on the U.S.WestCoast:a review . Bull Amer Meteor Soc,1994,75(2):229~240.
Lewis J M,Koracin D,Redmond T K. Sea fog research in the United Kingdom and United States: a historical essay including outlook . Bull killer Meteor Soc, 2004, 85(3):395~408.
Lin, J.-T., D. Youn, X.-Z. Liang, and D. J. Wuebbles. Global model simulation of summertime U.S. ozone diurnal cycle and its sensitivity to PBL mixing, spatial resolution, and emissions. Atmos. Environ., 2008, 42:8470~8483.
Liu Shuyan and Liang Xinzhong. Obserned Diurnal Cycle Climatology of Planetary Boundary Layer Height. Journal of Climate, 2010, 23:5790~5808.
Nicholas A. Bond. Observations of Planetary Boundary-Layer Structure in the Eastern Equatorial Pacific. Journal of Climate, 1992, 5:700~706.
Seibert, P., F. Beyrich, S. E. Gryning, S. Joffre, A. Rasmussen, and P. Tercier. Review and intercomparison of operational methods for the determination of the mixing height. Atmos. Environ., 2000, 34:1001~1027.
Stull.边界层气象学导论.青岛:青岛海洋大学出版社.1991: 1~11, 105~112, 309~366.
Suarez, M. J., A. Arakawa and D. A. Randall. The parameterization of the planetary boundary layer in the UCLA general circulation model: Formulation and results. Mon. Wea. Rev., 1983, 111: 2224~2243.
Vogelezang, D. H. P and A. A. M. Holtslag, Evaluation and model impacts of alternative boundary-layer height formulations. Bound.-Layer Meteor., 1996, 81: 245~269.
Zeng Xubin, Michael A. Brunke. Marine Atmospheric Boundary Layer Height over the Eastern Pacific: Data Analysis and Model Evaluation. Journal of Climate, 2004, 17:4159~4170.
Zhang Suping, Ren Zhaopeng, Liu Jingwu, Yang Yuqiang, and Wang Xingong. Variations in the Lower of the PBL Associated with the Yellow Sea Fog-New Observations by L-Band Radar. Ocean Univ.Chin, 2008:353~361.
陈炯,王建捷.北京地区夏季边界层结构日变化的高分辨模拟对比.应用气象学报,2006,17(4):403~411.
程水源,张宝宁,白天雄等.北京地区大气混合层高度的研究及气象特征.环境科学丛刊, 1990,13(4):46 ~52.
程水源,张宝宁,李现丽.用清晨探空曲线确定混合层高度的研究.环境科学丛刊,1990,13(3):76~80.
程水源,席德立,张宝宁等.大气混合层高度的确定与计算方法研究.中国环境科学,1997,17(6):512~515.
范绍佳,Wang Qing,邓茂芝,汪华莉.北冰洋春夏季海洋大气边界层特征的初步研究.中山大学学报(自然科学版),2002,41(1):91~94.
付秀华,常用边界层高度计算方法比较.电力环境保护,1989,5(3):24~29.
葛哲学,沙威.小波分析理论与MATLAB R2007实现.北京:电子工业出版社. 2007.
谷良雷,胡泽勇,吕世华,姚济敏.敦煌和酒泉夏季晴天和阴天边界层气象要素特征分析.干旱区地理,2007,30(6):871~878.
胡非,洪钟祥,雷孝恩.大气边界层和大气环境研究进展.大气科学, 2003,27(4):712~727.
胡基福.气象统计原理与方法[M].青岛:青岛海洋大学出版社,1996:235.
梁汉明,董保群,彭贤安,田广生.珠江三角洲地区大气混合层特征分析.气象,18(7):7~11.
廖国莲.大气混合层厚度的计算方法及影响因子.中山大学研究生学刊(自然科学、医学版),2005,26(4):66~73.
柳艳菊,丁一汇.南海季风爆发前后大气层结和混合层的演变特征.气候与环境研究,2000,5(4) :460.
孟庆珍,冯艺.成都大气混会层厚度的计算和分析.成都气象学院学报,1996,II:73~81.
孟庆珍,朱炳省.重庆市大气混合层厚度的计算和分析.成都气象学院学报,1999,14(2):163~170.
盛裴轩,毛节泰,李建国等.大气物理学.北京:北京大学出版社,2003:239.
史宝忠,郑方成,曹国良.对大气混合层高度确定方法的比较分析.西安建筑科技大学学报,1997,29(2):131~141.
王海龙,张镭,陈长和等.兰州市东部地区冬季低空风场和温度场分析.兰州大学学报(自然科学版),1999,35(4):121~122.
王式功,姜大膀,杨德保等.兰州市区最大混合层厚度变化特征分析.高原气象,2000,19 (3):367.
王晓丽,张苏平,张晓梅.青岛市水平能见度变化特征及气象影响因子分析.气象科学,2008,28(增刊):31~36.
王珍珠,李炬,钟志庆,刘东,周军.激光雷达探测北京城区夏季大气边界层.应用光学,2008,29(1):96~100.
吴祖常,董保群.我国陆域大气最大混合层厚度的地理分布与季节变化.科技通报,1998,14(3):158~163.
徐芙蓉,施介宽.混合层高度变化趋势及其代表值的探讨.东华大学学报(自然科学版),2003,29(4):99~102.
杨勇杰,谈建国,郑有飞,陈舜华.上海市近1 5 a大气稳定度和混合层厚度的研究.气象科学,2006,26(5):536~541.
叶堤,王飞,陈德蓉.重庆市多年大气混合层厚度变化特征及其对空气质量的影响分析.气象与环境学报,2008,24(4):41~44.
盂庆珍.重庆11 a来大气混合层厚度研究.重庆环境科学,1994,16(4):12~16.
曾智华.大气混合层高度的模式计算和分析.高原气象,2004,23(3):368~373.
张海鹰,刘元海,林奇昌.声雷达探测边界层高度的研究.齐齐哈尔师范学院学报(自然科学版),1994,14(4):43~47.
张美根,韩志伟.复杂地形对对流混合层的影响.气候与环境研究,1998,3(2):122.
张苏平,杨育强,王新功,魏建苏.低层大气季节变化及与黄海雾季的关系.中国海洋大学学报,2008,38(5):689~698.
张苏平.黄海海雾季节变化特殊性形成机理的研究:[博士学位论文].青岛:中国海洋大学,2008.
张鑫,蔡旭晖,柴发合.北京市秋季大气边界层结构与特征分析.北京大学学报(自然科学版),2006,42(2):220~225.
周颖.贵阳市混合层高度的研究.贵州环保科技,1997,4:37~40.
朱乾根,林锦瑞,寿绍文等.天气学原理与方法.北京:气象出版社.2007.
Arakawa A., and W. H. Schubert. Interaction of a cumulus cloud ensemble with the large-scale environment, part I. Atmos. Sci., 1974, 31, 674~701.
Brian Medeiros, AlexhallL, Bjorn Stevens. What Controls the Mean Depth of the PBL?. Journal of Climate, 2005, 18:3157~3172.
Cao Guangxia, Thomas W, Giambelluca, Duane E, Stevens and Thomnas A. Schroeder. Inversion Variability in the Hawaiian Trade Wind Regime. Journal of Climate.2007, (20):1145~1160.
Deardorff, J. W. Parameterization of the planetary boundary layer for use in general circulation models. Mon. Wea. Rev., 1972, 100:93~106.
Holtslag, A. A. M., and F. T. M. Nieuwstadt. Scaling the atmospheric boundary layer. Bound.-Layer Meteor., 1986, 36:201~209.
Holzworth, George C. Estimates of mean maximum mixing depth s in the Contiguous United States. Mon. Wea. Rev., 1964, 92:235~242.
Konor, C. S., G. C. Boezio, C. R. Mechoso, and A. Arakawa. Parameterization of PBL processes in an atmospheric general circulation model: Description and preliminary assessment. Mon. Wea. Rev., 2009, 137, 1061~1082.
Leipper D F. Fog on the U.S.WestCoast:a review . Bull Amer Meteor Soc,1994,75(2):229~240.
Lewis J M,Koracin D,Redmond T K. Sea fog research in the United Kingdom and United States: a historical essay including outlook . Bull killer Meteor Soc, 2004, 85(3):395~408.
Lin, J.-T., D. Youn, X.-Z. Liang, and D. J. Wuebbles. Global model simulation of summertime U.S. ozone diurnal cycle and its sensitivity to PBL mixing, spatial resolution, and emissions. Atmos. Environ., 2008, 42:8470~8483.
Liu Shuyan and Liang Xinzhong. Obserned Diurnal Cycle Climatology of Planetary Boundary Layer Height. Journal of Climate, 2010, 23:5790~5808.
Nicholas A. Bond. Observations of Planetary Boundary-Layer Structure in the Eastern Equatorial Pacific. Journal of Climate, 1992, 5:700~706.
Seibert, P., F. Beyrich, S. E. Gryning, S. Joffre, A. Rasmussen, and P. Tercier. Review and intercomparison of operational methods for the determination of the mixing height. Atmos. Environ., 2000, 34:1001~1027.
Stull.边界层气象学导论.青岛:青岛海洋大学出版社.1991: 1~11, 105~112, 309~366.
Suarez, M. J., A. Arakawa and D. A. Randall. The parameterization of the planetary boundary layer in the UCLA general circulation model: Formulation and results. Mon. Wea. Rev., 1983, 111: 2224~2243.
Vogelezang, D. H. P and A. A. M. Holtslag, Evaluation and model impacts of alternative boundary-layer height formulations. Bound.-Layer Meteor., 1996, 81: 245~269.
Zeng Xubin, Michael A. Brunke. Marine Atmospheric Boundary Layer Height over the Eastern Pacific: Data Analysis and Model Evaluation. Journal of Climate, 2004, 17:4159~4170.
Zhang Suping, Ren Zhaopeng, Liu Jingwu, Yang Yuqiang, and Wang Xingong. Variations in the Lower of the PBL Associated with the Yellow Sea Fog-New Observations by L-Band Radar. Ocean Univ.Chin, 2008:353~361.