In this paper, a heavy sea fog episode that occurred over the Yellow Sea on 9 March 2005 is investigated. The sea fog patch, with a spatial scale of several hundred kilometers at its mature stage, reduced visibility a...In this paper, a heavy sea fog episode that occurred over the Yellow Sea on 9 March 2005 is investigated. The sea fog patch, with a spatial scale of several hundred kilometers at its mature stage, reduced visibility along the Shandong Peninsula coast to 100 m or much less at some sites. Satellite images, surface observations and soundings at islands and coasts, and analyses from the Japan Meteorology Agency （JMA） axe used to describe and analyze this event. The analysis indicates that this sea fog can be categorized as advection cooling fog. The main features of this sea fog including fog area and its movement axe reasonably reproduced by the Fifth-generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model （MM5）. Model results suggest that the formation and evolution of this event can be outlined as： （1） southerly warm/moist advection of low-level air resulted in a strong sea-surface-based inversion with a thickness of about 600 m; （2） when the inversion moved from the warmer East Sea to the colder Yellow Sea, a thermal internal boundary layer （TIBL） gradually formed at the base of the inversion while the sea fog grew in response to cooling and moistening by turbulence mixing; （3） the sea fog developed as the TIBL moved northward and （4） strong northerly cold and dry wind destroyed the TIBL and dissipated the sea fog. The principal findings of this study axe that sea fog forms in response to relatively persistent southerly waxm/moist wind and a cold sea surface, and that turbulence mixing by wind shear is the primary mechanism for the cooling and moistening the marine layer. In addition, the study of sensitivity experiments indicates that deterministic numerical modeling offers a promising approach to the prediction of sea fog over the Yellow Sea but it may be more efficient to consider ensemble numerical modeling because of the extreme sensitivity to model input.展开更多
The fog occurs frequently over the Yellow Sea in spring（April–May）, a climatical period of Asian monsoon transition. A comprehensive survey of the characteristic weather pattern and the air-sea condition is provide...The fog occurs frequently over the Yellow Sea in spring（April–May）, a climatical period of Asian monsoon transition. A comprehensive survey of the characteristic weather pattern and the air-sea condition is provided associated with the fog for the period of 1960–2006. The sea fog is categorized by airflow pathways of backward trajectory cluster analysis with the surface observations derived from international comprehensive oceanatmosphere dataset（I_COADS） I_COADS datasets and contemporaneous wind fields from the National Centers for Environmental Prediction（NCEP）/National Center for Atmospheric Research（NCAR） reanalysis. On the basis of the airflow paths, the large-scale lower-tropospheric circulation patterns and the associated surface divergence,the distribution of a vertical humidity, the horizontal water vapor transportation and the air-sea temperature difference are investigated and the major findings are summarized as follows.（1） Four primary clusters of the airflow paths that lead to spring sea fog formation are identified. They are originated from the northwest, east,southeast and southwest of the Yellow Sea, respectively.（2） Springtime Yellow Sea fog occurs under two typical weather patterns： the Yellow Sea high（YSH） and cyclone and anticyclone couplet（CAC）. Each pattern appears by about equal chance in April but the YSH occurrence drops to around one third and the CAC rises to around two third of chance in May.（3） The common feature in the two types of synoptic conditions is that surface divergence center is located over the Yellow Sea.（4） For the YSH type of fog, water vapor comes mainly from local evaporation with a well-defined dry layer present in the lower atmosphere; for the CAC type of fog, however, water vapor comes mainly from areas outside the Yellow Sea with a thick surface layer of high humidity.（5） With the differences in weather patterns and its associated vertical distribution of the humidity and the transportation of water vapor, there are two types of sea fogs. Most fogs of the CAC types are ＂warm＂ fog, while fogs of YSH type have nearly equal chance to be ＂warm＂ and ＂cold＂ fog.展开更多
In this paper, almost all available observational data and the latest 6.0 version of Regional Atmospheric Modeling System (RAMS) model were employed to investigate a heavy sea fog event occurring over the Yellow Sea f...In this paper, almost all available observational data and the latest 6.0 version of Regional Atmospheric Modeling System (RAMS) model were employed to investigate a heavy sea fog event occurring over the Yellow Sea from 2 to 5 May 2009. The evolutionary process of this event was documented by using Multifunctional Transport Satellites-1 (MTSAT-1) visible satellite imagery. The synoptic situation, sounding profiles at two selected stations were analyzed. The difference between the air temperature and sea surface temperature during the sea fog event over the entire sea region was also analyzed. In order to better understand this event, an RAMS modeling with a 15 km×15 km resolution was performed. The model successfully reproduced the main characteristics of this sea fog event. The simulated height of fog top and the area of lower atmospheric visibility derived from the RAMS modeling results showed good agreement with the sea fog area identified from the satellite imagery. Examinations of both observational data and RAMS modeling results suggested that advection cooling seemed to play an important role in the formation of this sea fog event.展开更多
基于日本气象厅Multi-functional Transport Satellite（MTSAT）可见光卫星云图、韩国气象局天气图和美国国家环境预报中心Climate Forecast System Reanalysis（CFSR）数据,选取2007-2012年2～6月发生的32次黄海海雾个例进行研究.首先...基于日本气象厅Multi-functional Transport Satellite（MTSAT）可见光卫星云图、韩国气象局天气图和美国国家环境预报中心Climate Forecast System Reanalysis（CFSR）数据,选取2007-2012年2～6月发生的32次黄海海雾个例进行研究.首先统计分析了黄海海雾的天气特征,接着归纳总结了有利于黄海海雾生成的天气系统类型,进而分别挑选了各类型的一次个例,解释其海上大气逆温层成因.结果表明：（1）黄海海雾天气系统可分为入海变性高压（南高北低、东高西低和独立高压）、中国大陆东移低压或低槽、北太平洋高压脊和入西太平洋高压4类,各自所占比例约为62.5％、21.9％、9.4％和6.2％.（2）天气系统控制下的冷暖平流与海面湍流冷却作用决定了海上大气逆温层的形成.海雾生成前,天气系统在演变过程中支配着形成逆温的暖气团,暖气团来源于陆上,则主要是上层强暖平流、下层弱暖（冷）平流导致逆温;暖气团来源于海上,则多由近冷海面的湍流混合、冷却降温形成逆温.展开更多
海表面温度(SST)是海气界面上的1个物理量,受到海洋潮汐、海底地形等因素影响,并对海洋大气边界层有着重要的影响。夏季的黄海,由于黄海冷水团的存在和陆架锋的影响,或是潮汐混合的作用导致海水的垂直混合,使海表面温度的分布产生复杂...海表面温度(SST)是海气界面上的1个物理量,受到海洋潮汐、海底地形等因素影响,并对海洋大气边界层有着重要的影响。夏季的黄海,由于黄海冷水团的存在和陆架锋的影响,或是潮汐混合的作用导致海水的垂直混合,使海表面温度的分布产生复杂的结构。通过对卫星观测的海表面温度数据分析,发现在夏季黄海有几个SST冷中心的存在:辽东半岛以及山东半岛的顶端、朝鲜半岛的西侧、山东半岛南侧、江苏外海和黄海南部等。本文利用一系列船舶观测资料、卫星遥感数据、再分析数据分析等,并运用数值模拟研究黄海的冷中心对其上大气的影响。在冷区之上,大气稳定度增加,抑制了近海面大气的垂直混合,使海表面风速减弱。通过对船测数据的分析,在冷区位置有海雾多发区的存在,黄海南部冷区上的海雾发生频率达到15%以上。Weather Research and Forecasting(WRF)模式的数值模拟表明,冷中心降低上空的温度,使海表面风速减弱,形成厚度达500m的逆温层,为海雾的形成创造了有利的条件。与船测数据结果所不同的是黄海南部冷中心之上的海雾发生频率可以达到30%,去掉冷区影响的试验表明冷区较冷的海表面温度最多可以使海雾的发生频率增加15%以上。展开更多
基于WRF(Weather Research and Forecasting)模式及其杂合三维变分(Hybird-3DVAR)同化模块,对2006年3月发生的一次大范围黄海海雾进行了集合预报尝试。详细分析了其预报效果,并与决定性预报结果作了比较。研究揭示:集合预报50%概率雾区...基于WRF(Weather Research and Forecasting)模式及其杂合三维变分(Hybird-3DVAR)同化模块,对2006年3月发生的一次大范围黄海海雾进行了集合预报尝试。详细分析了其预报效果,并与决定性预报结果作了比较。研究揭示:集合预报50%概率雾区预报的公正预兆得分(Equitable threat score,ETS)优于决定性预报大约29%;集合预报中加入海温扰动非常必要,对浓雾预报改善作用明显,ETS提高至少10%;在集合预报中混用YSU与MYNN边界层方案的做法,可以降低只使用其中之一可能导致的预报误差。研究表明,借助Hybrid-3DVAR开展黄海海雾的集合预报技术上可行,集合预报将成为黄海海雾数值预报的一种有希望的途径。展开更多
文摘In this paper, a heavy sea fog episode that occurred over the Yellow Sea on 9 March 2005 is investigated. The sea fog patch, with a spatial scale of several hundred kilometers at its mature stage, reduced visibility along the Shandong Peninsula coast to 100 m or much less at some sites. Satellite images, surface observations and soundings at islands and coasts, and analyses from the Japan Meteorology Agency （JMA） axe used to describe and analyze this event. The analysis indicates that this sea fog can be categorized as advection cooling fog. The main features of this sea fog including fog area and its movement axe reasonably reproduced by the Fifth-generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model （MM5）. Model results suggest that the formation and evolution of this event can be outlined as： （1） southerly warm/moist advection of low-level air resulted in a strong sea-surface-based inversion with a thickness of about 600 m; （2） when the inversion moved from the warmer East Sea to the colder Yellow Sea, a thermal internal boundary layer （TIBL） gradually formed at the base of the inversion while the sea fog grew in response to cooling and moistening by turbulence mixing; （3） the sea fog developed as the TIBL moved northward and （4） strong northerly cold and dry wind destroyed the TIBL and dissipated the sea fog. The principal findings of this study axe that sea fog forms in response to relatively persistent southerly waxm/moist wind and a cold sea surface, and that turbulence mixing by wind shear is the primary mechanism for the cooling and moistening the marine layer. In addition, the study of sensitivity experiments indicates that deterministic numerical modeling offers a promising approach to the prediction of sea fog over the Yellow Sea but it may be more efficient to consider ensemble numerical modeling because of the extreme sensitivity to model input.
基金The National Natural Science Foundation of China under contract No.41275025the Special Fund for Strategic Pilot Technology of Chinese Academy of Sciences under contract No.XDA11010403the National Key Basic Research Program(973 Progrom)of China under controut No.2014CB953903
文摘The fog occurs frequently over the Yellow Sea in spring（April–May）, a climatical period of Asian monsoon transition. A comprehensive survey of the characteristic weather pattern and the air-sea condition is provided associated with the fog for the period of 1960–2006. The sea fog is categorized by airflow pathways of backward trajectory cluster analysis with the surface observations derived from international comprehensive oceanatmosphere dataset（I_COADS） I_COADS datasets and contemporaneous wind fields from the National Centers for Environmental Prediction（NCEP）/National Center for Atmospheric Research（NCAR） reanalysis. On the basis of the airflow paths, the large-scale lower-tropospheric circulation patterns and the associated surface divergence,the distribution of a vertical humidity, the horizontal water vapor transportation and the air-sea temperature difference are investigated and the major findings are summarized as follows.（1） Four primary clusters of the airflow paths that lead to spring sea fog formation are identified. They are originated from the northwest, east,southeast and southwest of the Yellow Sea, respectively.（2） Springtime Yellow Sea fog occurs under two typical weather patterns： the Yellow Sea high（YSH） and cyclone and anticyclone couplet（CAC）. Each pattern appears by about equal chance in April but the YSH occurrence drops to around one third and the CAC rises to around two third of chance in May.（3） The common feature in the two types of synoptic conditions is that surface divergence center is located over the Yellow Sea.（4） For the YSH type of fog, water vapor comes mainly from local evaporation with a well-defined dry layer present in the lower atmosphere; for the CAC type of fog, however, water vapor comes mainly from areas outside the Yellow Sea with a thick surface layer of high humidity.（5） With the differences in weather patterns and its associated vertical distribution of the humidity and the transportation of water vapor, there are two types of sea fogs. Most fogs of the CAC types are ＂warm＂ fog, while fogs of YSH type have nearly equal chance to be ＂warm＂ and ＂cold＂ fog.
基金supported by the National Natural Science Foundation of China under the grant numbers 41175006 and 40675060the Chinese Meteorological Administration under thegrant GYHY200706031+1 种基金the Chinese Ministry of Science and Technology under the 973 Project grant number 2009CB421504the financial support of the Student Research and Development Program of the Ocean University of China under the grant number 1111010101
文摘In this paper, almost all available observational data and the latest 6.0 version of Regional Atmospheric Modeling System (RAMS) model were employed to investigate a heavy sea fog event occurring over the Yellow Sea from 2 to 5 May 2009. The evolutionary process of this event was documented by using Multifunctional Transport Satellites-1 (MTSAT-1) visible satellite imagery. The synoptic situation, sounding profiles at two selected stations were analyzed. The difference between the air temperature and sea surface temperature during the sea fog event over the entire sea region was also analyzed. In order to better understand this event, an RAMS modeling with a 15 km×15 km resolution was performed. The model successfully reproduced the main characteristics of this sea fog event. The simulated height of fog top and the area of lower atmospheric visibility derived from the RAMS modeling results showed good agreement with the sea fog area identified from the satellite imagery. Examinations of both observational data and RAMS modeling results suggested that advection cooling seemed to play an important role in the formation of this sea fog event.
文摘基于日本气象厅Multi-functional Transport Satellite（MTSAT）可见光卫星云图、韩国气象局天气图和美国国家环境预报中心Climate Forecast System Reanalysis（CFSR）数据,选取2007-2012年2～6月发生的32次黄海海雾个例进行研究.首先统计分析了黄海海雾的天气特征,接着归纳总结了有利于黄海海雾生成的天气系统类型,进而分别挑选了各类型的一次个例,解释其海上大气逆温层成因.结果表明：（1）黄海海雾天气系统可分为入海变性高压（南高北低、东高西低和独立高压）、中国大陆东移低压或低槽、北太平洋高压脊和入西太平洋高压4类,各自所占比例约为62.5％、21.9％、9.4％和6.2％.（2）天气系统控制下的冷暖平流与海面湍流冷却作用决定了海上大气逆温层的形成.海雾生成前,天气系统在演变过程中支配着形成逆温的暖气团,暖气团来源于陆上,则主要是上层强暖平流、下层弱暖（冷）平流导致逆温;暖气团来源于海上,则多由近冷海面的湍流混合、冷却降温形成逆温.
文摘海表面温度(SST)是海气界面上的1个物理量,受到海洋潮汐、海底地形等因素影响,并对海洋大气边界层有着重要的影响。夏季的黄海,由于黄海冷水团的存在和陆架锋的影响,或是潮汐混合的作用导致海水的垂直混合,使海表面温度的分布产生复杂的结构。通过对卫星观测的海表面温度数据分析,发现在夏季黄海有几个SST冷中心的存在:辽东半岛以及山东半岛的顶端、朝鲜半岛的西侧、山东半岛南侧、江苏外海和黄海南部等。本文利用一系列船舶观测资料、卫星遥感数据、再分析数据分析等,并运用数值模拟研究黄海的冷中心对其上大气的影响。在冷区之上,大气稳定度增加,抑制了近海面大气的垂直混合,使海表面风速减弱。通过对船测数据的分析,在冷区位置有海雾多发区的存在,黄海南部冷区上的海雾发生频率达到15%以上。Weather Research and Forecasting(WRF)模式的数值模拟表明,冷中心降低上空的温度,使海表面风速减弱,形成厚度达500m的逆温层,为海雾的形成创造了有利的条件。与船测数据结果所不同的是黄海南部冷中心之上的海雾发生频率可以达到30%,去掉冷区影响的试验表明冷区较冷的海表面温度最多可以使海雾的发生频率增加15%以上。
文摘基于WRF(Weather Research and Forecasting)模式及其杂合三维变分(Hybird-3DVAR)同化模块,对2006年3月发生的一次大范围黄海海雾进行了集合预报尝试。详细分析了其预报效果,并与决定性预报结果作了比较。研究揭示:集合预报50%概率雾区预报的公正预兆得分(Equitable threat score,ETS)优于决定性预报大约29%;集合预报中加入海温扰动非常必要,对浓雾预报改善作用明显,ETS提高至少10%;在集合预报中混用YSU与MYNN边界层方案的做法,可以降低只使用其中之一可能导致的预报误差。研究表明,借助Hybrid-3DVAR开展黄海海雾的集合预报技术上可行,集合预报将成为黄海海雾数值预报的一种有希望的途径。
