An observational and modeling study of a sea fog event over the Yellow Sea on 1 August 2003

A dense sea fog episode that occurred near the coastal city of Qingdao in the Shandong Peninsula of China on 1 August 2003 is investigated by using all of the available observational data and high-resolution modeling results from the Regional Atmospheric Modeling System (RAMS). This fog event reduced the horizontal visibility to be less than 60 m in some locations and caused several traffic accidents locally. In this paper, all of the available observational data, including visible satellite imagery of Geostationary Operational Environmental Satellite (GOES)-9 and MODerate-resolution Imaging Spectroradiometer (MODIS), objectively reanalyzed Final Analysis (FNL) data issued by the National Centers for Environmental Prediction (NCEP), sounding data at the Qingdao and Dalian stations, and the latest 4.4 version of the RAMS model, were employed to study this sea fog case. We begin with the analyses of the environmental conditions of the sea fog event, including the large-scale conditions, the difference between T _2m (air temperature at 2 m altitude) and sea surface temperature (SST), and the atmospheric sounding profiles of the two stations. The characteristics of this sea fog event was documented by using visible satellite imagery of GOES-9 and MODIS. In order to better understand the fog formation mechanism, a high-resolution RAMS model of dimensions 4 km × 4 km was designed, which was initialized and validated by FNL data. A 54-h modeling period that started from 18 UTC 31 July 2003 reproduced the main characteristics of this sea fog event. The simulated lower visibility area agreed well with the sea fog area identified from the satellite imagery. It is shown that advection cooling effect plays a significant role in the fog formation.     

一次黄海海雾成因分析及数值模拟试验

根据GOES-9(Geostationary Operational Environmental Satellite）可见光卫星云图和韩国济州岛探空资料等,利用RAMS(Regional Atmospheric Modeling System)模式（6.1版）对2009年3月17-18日发生在黄海海域的一次大风条件下出现的海雾天气进行模拟。结果表明：与卫星云图所显示的雾区范围相比,模拟结果对海雾的生成、发展、移动都有较好吻合;云水混合比是影响大气水平能见度分布的主要因子,云水混合比大值区主要集中在距地面300 m以下的低空;雾区存在几个云水混合比大值区,并分布在不同的高度,说明海雾的团状不均匀结构;海上平流雾常发生在风速较大的情况下,RAMS模式对此具有一定的模拟能力。     

2009年春季一次黄海海雾的观测分析及数值模拟

利用5种观测资料和RAMS（regional atmospheric modeling system）模式对2009年5月2_5日发生在黄海海域的一次海雾过程进行了观测分析和数值模拟研究。结果表明：1）所取个例的整个生命过程受同一高压系统影响,该高压在海雾过程后期的形变促使海雾消散,这在以往的黄海海雾中较为罕见。2）黄海北部形似“7”的雾区形态的出现和演化与1～3℃气海温差的变化吻合,气海温差对海雾形成和演变的重要作用得到再次验证。3）RAMS模式具有一定的海雾数值模拟能力,得到的雾顶高度分布与卫星云图所显示的雾区形态吻合良好。     

FY-3A卫星近海面气象要素在冬季夜间海上能见度分析中的应用

对FY-3A气象卫星大气温度湿度廓线资料进行夜间大雾低能见度分布反演计算,并运用美国LAPS(Local Analysis and Prediction System)局地分析与预报系统,与FNL再分析资料多要素反演数据进行多源要素融合分析。FY-3A卫星反演得到的大雾低能见度分布,经与Micaps(Meteorological Information Comprehensive Analysis and Process System)系统地面天气图, FY-2E地球同步卫星红外云图,要素统计气象年鉴记录等对比检验,显示反演的低能见度区范围及强度合理。尤其是对海上缺乏常规观测资料网的海域,提供了夜间海上能见度分布信息。进一步地通过LAPS系统对比卫星资料、再分析资料、以及卫星与再分析资料融合的3种方案结果,显示将卫星监测资料与FNL再分析资料的融合效果,对单来源资料反演的大雾低能见度分布有较好的改善。融合后对卫星资料而言,卫星轨道盲区已经弥合,其次,获得了海上低能见度区分布的信息,对海上和沿海雾区能见度的强度得到合理改善。对于FNL再分析资料,原有的各项要素强梯度被合理平滑。低能见度范围也有调整改善。重要的是海上大雾低能见度区的分布,得到FY-3A卫星信息和数值模拟信息的互相验证与信息综合,可信度增强。     

Analyses and numerical modeling of a polar low over the Japan Sea on 19 December 2003

A meso-α-scale polar low was observed over the Japan Sea on 19 December 2003. It initialed around 11 UTC over the northwestern part of the Japan Sea within a synoptic-scale parent low under the influence of baroclinic environment and disappeared over the eastern edge of Japan Islands with a lifetime of about 20 h. It is of interest that this polar low had “concentric eye-walls” and “warm core” structure at its mature stage. The evolutionary process and spatial structure of this polar low were investigated by using almost all available observational data, including the Geostationary Operational Environmental Satellite (GOES)-9, the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery, the Final Analyses (FNL) data issued by National Centers for Environmental Prediction (NCEP), the surface observational data and the 9-station sounding data of Japan Islands. In order to study its development mechanism, a 24-h numerical simulation using the version 4.4 of the Regional Atmospheric Modeling System (RAMS) starting from 12 UTC 19 December 2003 with an 8 km × 8 km resolution was performed. It is shown that the RAMS model reproduced the main features of the polar low reasonably well. The vorticity budget analyses indicate that the stretching term is the major contributor for the vorticity increase of the polar low. The baroclinic background seems to play significant role for the initial development of this polar low. However, the effect of the diabatic heating for its later development is also significant.     

闽南沿海一次春季海雾过程微物理特征分析

利用地面自动站观测、风廓线雷达、ERA5再分析资料、葵花8号高分辨率卫星资料以及FM-120型雾滴谱资料,分析了2019年4月7日闽南沿海一次强浓雾过程的环流形势以及微物理特征。环流形势分析表明,此次海雾过程500 hPa为槽底偏西西北气流,700 hPa至地面为一致的偏南气流,探空形势稳定。海雾发生前,整层风速明显减小,弱风速层厚度迅速增大,为海雾的形成提供了稳定的环流背景。卫星监测分析表明,海雾首先快速形成于台湾海峡上,在偏南气流作用下,平流至沿海地区。水文条件分析表明,福建近海存在一条冷水带,从海峡中部至沿海海温梯度大,海温在18~24℃,近海气海温差介于0~2℃,有利于海峡内平流冷却雾的形成。雾滴谱分析表明,翔安站能见度显著下降伴随着粒子数浓度、液态水含量显著增加,雾滴谱爆发性拓宽。海雾过程中,5 min平均粒子数浓度最大超过200个·cm^-3,瞬时数浓度最大达到468个·cm^-3,雾过程平均数浓度为100个·cm^-3。5 min平均液态水含量最高达到0.41 g·m^-3,瞬时液态水含量最大达到1.35 g·m^-3,雾过程平均液态水含量为0.17 g·m^-3。粒子浓度呈现双峰结构特征,峰值分别位于4~6和22~26μm,表明小粒子和大粒子对海雾的形成均有明显的贡献。     

浙江中部一次大雾过程分析与预报

利用NCEP再分析格点资料、常规观测资料、数值预报产品以及卫星云图对2009年4月6日早晨浙江中部一次大范围大雾天气过程进行诊断分析。结果表明：高空槽后暖脊的大气环流背景有利于地面长波辐射冷却和中层增温,易形成逆温,为大雾生成提供了有利条件,而边界层逆温层或等温层的形成与维持对雾的发展持续具有重要作用;凝结核、低层湍流混合是山区能见度较城镇大的主要原因;交叉温度可用来预示整个潜在雾层的湿度状态,温度与交叉温度差值可作为了解大雾生成、发展、消散过程的一项指标;模式产品能提供雾形成的环境条件;红外云图、可见光云图有助于预测雾的形成、发展、消散过程。     

2018年2月琼州海峡持续性海雾过程的数值模拟分析

2018年2月春节期间琼州海峡发生持续性大雾天气,造成大量船舶停航。本文结合葵花8号卫星反演海雾产品、琼州海峡沿岸站点能见度观测数据及美国国家环境预报中心NCEP（National Centers for Environmental Prediction） 提供的FNL（Final Analysis）客观分析资料,对2018年2月18～20日的大雾过程进行了天气学成因分析,并进一步利用CMA-MESO（Global and Regional Assimilation and Prediction System）高分辨率数值模式从边界层方案、模式垂直分层以及海雾能见度算法三个方面进行敏感性试验,以找出模拟效果更好的模式设置方案。研究结果表明:大雾期间华南近海海温较常年平均偏低,受地面冷高压南下补充的弱冷空气影响,偏东暖湿气流流经冷海面并快速凝结。而数值模拟对比试验显示,采用YSU（Yonsei University）边界层方案、边界层垂直层次加密及美国国家海洋大气局预报系统实验室（FSL/NOAA）的海雾诊断方案（简称FSL）对改进能见度预报效果显著:YSU边界层方案比MRF（Medium Range Forecast Model）边界层方案对该次大雾过程的分布范围和最低能见度出现的时间模拟效果更优;模式低层分层加密可更好体现出低能见度的演变过程;通过能见度算法与实况对比,基于模式预报性能较好的湿度和温度预报而来的FSL算法,其能见度预报与站点实况最为接近。     

基于多灰度共生矩阵特征值的黄渤海白天海雾识别算法

本文基于多灰度共生矩阵特征值,即相关性、对比度、同质性和能量,进行联合海雾遥感判识,提出一种高准确率黄渤海白天海雾识别算法。采用第二代静止气象卫星FY-4A可见光、近红外和红外数据,将该算法应用于黄渤海区域白天海雾判识,并利用2019—2020年沿黄渤海气象站点能见度实测数据及CALIPSO卫星数据产品对本算法识别结果进行精度验证。结果表明：海雾识别平均检测率(POD)为92%,误报率(FAR)为27%,临近成功指数(CSI)为69%,可以实现对海雾的动态监测,为海上交通等领域提供较好的数据支持。     

北京地区一次持续性大雾的宏观物理特征

通过分析北京地区2004年11月30日和12月2日出现的两场大雾生成的天气背景,大雾生成阶段和消散阶段的温度、湿度、气压和风场特征,探讨北京地区大雾的宏观物理特征。所用数据资料是通过系留气球探测所得,分析了气象要素的廓线和时间剖面图特征,从而得到了北京地区有雾生成时的天气背景特征;辐射雾与平流雾的能见度变化区别,雾生成时、持续阶段及雾消散前温度场、湿度场的变化特征;逆温层在辐射雾和平流雾中的形成原因和作用都不同;比湿值增大是判断有暖湿平流带来水汽的重要指标;气压变化平稳、缓慢,使强对流没有发生,逆温层不能被冲破,雾能长时间维持。     

卫星云图在海岸带大雾天气监测及预警中的应用

利用2005-2010年卫星云图FY-2E、海岸带一海区出现的28次大雾天气资料和2008-2010年海岛站资料,依据大气状态方程、热力学原理,在MICAPS3．0系统下,应用云图与同步探空、地面雾区叠加图、温度场逆温层剖面及TBB值与海面温度比较,估算雾区面积、高度及秋、冬季雾区温度垂直递减率。结果表明：在环渤海地区特定的环流背景下,红外云图和可见光云图监测到的雾区分别在大连、烟台及天津一带由轻雾转为大雾,沿海岸带向北发生发展,雾区垂直厚度为400-600m,递减率为0．02-0．04℃／100m,渤海东西向温度差值为1q℃,南北向为3-5℃;辐射雾对应弱高压均压场,平流雾对应弱低压均压场;低云覆盖雾区浓雾加重,轻雾被低云叠加使得能见度降低;平流雾被锋面抬升后混合到低空水汽输送带之中,对后期降雪（水）具有指示作用。在2009-2010年海区一海岸带大雾天气预报及预警信号升级应用中效益显著,可为海岸带大雾预报因子选取及预报监测业务流程的改进提供参考。     

2015-04-28渤海海雾形成过程中的海气相互作用分析

利用FY和MTSAT卫星资料、ERA Interim再分析资料、黄渤海浮标站资料、黄渤海自动站逐小时观测资料,对发生在2015年4月28—29日的渤海海雾成因进行分析,着重探讨了海雾形成过程中的海气相互作用。结果发现,近海面处大气低层逆温层抬升,大于90%的大湿度区向上、向西扩展,对海雾形成非常有利;海雾生成前、生成发展过程中存在明显的东到东南风,有利于黄海水汽向渤海输送,海面上空有水汽通量大值区由渤海海峡向渤海中部移动,使得渤海上空水汽输送加强,提供了海雾形成所需的水汽;在海雾形成过程中渤海上空气温高于海温,风切变造成的海气界面湍流热交换为大气输送向海洋,使得冷海面上空暖湿空气降温冷却达到饱和形成海雾,是平流冷却雾。      

沪宁高速公路无锡段春季浓雾的实时监测和若干特征

20 0 0年 2月到 4月沪宁高速公路 ,共监测到 7次低能见度 (<2 0 0m)的春雾。本文应用环境气象监测仪AMW自动气象站 ,每分钟实测的有关资料和相应的环流背景场 ,对 7次春雾形成的物理过程作了研究分析。揭示了春雾形成过程中的若干特征和设计了实施临近预报制作的思路、流程。并论述了在高速公路沿线布设AMW自动气象监测仪的基础上作出低能见度的预测是可行和可能的     

下垫面热力作用对黄海春季海雾的影响——观测与数值试验

利用海上浮标站、高分辨率数字式探空仪等多种观测手段和中尺度模式WRF,对2008年5月2—3日黄海发生的一次海雾过程进行了观测分析和数值模拟。观测表明,出现海雾时,气温明显下降,气海温差(海表面以上2 m气温减海表面以下1m水温)减小,不足0.5℃,浓雾时,甚至出现海温(SST)高于气温的现象。较强的湍流活动出现在大气边界层低层150 m以下。反映了低层大气稳定性减弱,可能有利于海雾的维持。海雾消散阶段,海气温差明显加大,湍流强度减弱,湍流发展高度升高。海雾过程中,可能存在动量下传的局地海-气相互作用机制,SST的升高可使雾中能见度好转。数值模拟的结果与观测基本一致,雾区内的气海温差明显小于雾区外,敏感性试验进一步表明:100 m以下气层稳定性和湍流发展条件对SST的变化敏感。SST的变化对稳定度的影响和对雾区范围的影响与近海面的水汽含量有关:在湿度较小(q0.5 g/kg)的薄海雾区,SST增加1℃,稳定度明显减弱(θ_v/z≤0.01 K/m),海雾面积缩小;SST下降1℃,稳定度增加(θ_v/z≥0.07 K/m),薄海雾面积增大。在湿度较大(q0.6 g/kg)的浓海雾区,SST的变化对静力稳定度的影响不大,海雾仍然维持。因此,当海气温差减小,甚至出现SST高于气温时,如果仍然有海雾,则一般是水汽含量比较大的浓海雾。该结果有助于对海雾形成机制的认识。     

江苏地区连续性雾霾天气的污染物浓度变化和特征分析

针对2013年1月江苏淮安地区发生的一次连续性雾霾天气过程,分析该天气过程中PM10和PM2.5的质量浓度演变特征、能见度与气象要素之间的关系、中低层环流特征以及污染物来源。结果表明:雾霾期间PM10和PM2.5质量浓度最低值出现在05:00至07:00(北京时间,下同)和13:00至17:00,最高值出现在21:00至23:00,PM10和PM2.5质量浓度并非同时达到极大值;持续变化较小的气压梯度、较低的风速、相对湿度的增大以及PM2.5和PM10质量浓度的增高是雾霾发生发展的必要条件;能见度与气压、相对湿度、PM2.5质量浓度的相关性较好,建立回归方程,对能见度的整体变化趋势拟合效果较好;高空环流形势平稳、中低层的暖平流、持续稳定少动的地面高压场分布为雾霾天气的持续发生发展提供了有利的形势背景;稳定的层结结构、中低层偏东及偏东北方向气团的输送、本地污染源以及严重的空气污染是此次过程中能见度偏低、霾天数较多的主要原因。     

Evaluation of the Global and Regional Assimilation and Prediction System for Predicting Sea Fog over the South China Sea

In the South China Sea, sea fog brings severe disasters every year, but forecasters have yet to implement an effective seafog forecast. To address this issue, we test a liquid-water-content-only(LWC-only) operational sea-fog prediction method based on a regional mesoscale numerical model with a horizontal resolution of about 3 km, the Global and Regional Assimilation and Prediction System(GRAPES), hereafter GRAPES-3 km. GRAPES-3 km models the LWC over the sea, from which we infer the visibility that is then used to identify fog. We test the GRAPES-3 km here against measurements in 2016 and 2017 from coastal-station observations, as well as from buoy data, data from the Integrated Observation Platform for Marine Meteorology, and retrieved fog and cloud patterns from Himawari-8 satellite data. For two cases that we examine in detail, the forecast region of sea fog overlaps well with the multi-observational data within 72 h. Considering forecasting for0–24 h, GRAPES-3 km has a 2-year-average equitable threat score(ETS) of 0.20 and a Heidke skill score(HSS) of 0.335,which is about 5.6%(ETS) and 6.4%(HSS) better than our previous method(GRAPES-MOS). Moreover, the stations near the particularly foggy region around the Leizhou Peninsula have relatively high forecast scores compared to other sea areas.Overall, the results show that GRAPES-3 km can roughly predict the formation, evolution, and dissipation of sea fog on the southern China coast.     

A Heavy Sea Fog Event over the Yellow Sea in March 2005： Analysis and Numerical Modeling

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.     

Analysis of Coastal Fog from a Ship During the C-FOG Campaign

This work presents ship-based measurements of fog off St John’s, Newfoundland, on 13 September 2018 during the Coastal Fog field campaign. The measurements included cloud-particle spectra, cloud-base height and aerosol backscatter, radiation, turbulence, visibility, and sea-surface temperature. Radiosonde soundings were made at intervals of less than 2 h. Fog occurred in two episodes during the passage of an eastward-moving synoptic low-pressure system. The boundary-layer structure during the first fog episode consisted of three layers, separated by two saturated temperature inversions, and capped by a subsidence inversion. The lowest layer was fog, and the upper layers were cloud. The second fog episode consisted of one well-mixed fog layer capped by a subsidence inversion. Low wind speeds and stable stratification maintained low surface-layer turbulence during fog. Droplet size distributions had typical bimodal distributions. The visibility correlated with the droplet number concentration and liquid water content. The air temperature was higher than the sea-surface temperature for the first 30 min of the first fog episode but was lower than the sea for the remainder of all fog. The sensible heat flux was upward, from sea to air, for the first 62% of the first fog episode and then reversed to downward, from air to sea, for the remainder of the first fog episode and the second fog episode. The counter-gradient heat fluxes observed (i.e., opposite to what is expected from the instantaneous air–sea temperature difference) appear to be related to turbulence, entrainment, and stratification in the fog layer that overwhelmed the influence of the air–sea temperature difference. While the synoptic-scale dynamics preconditioned the area for fog formation, the final step of fog appearance in this case was nuanced by stratification–turbulence interactions, local advective processes, and microphysical environment.

     

黄渤海一次持续性大雾过程特征和成因分析

利用日本MTSAT1R卫星数据、常规地面和高空观测数据、NCEP FNL客观再分析资料和NEARGOOS（NorthEast Asian Regional Global Ocean Observing System）的海表温度（SST）数据,分析了2010年5月31日至6月5日发生在黄渤海及周边地区的一次持续性海雾天气的形成、维持、消散特征及其物理机制。结果表明：大雾形成前低层水汽非常充沛,入海变性冷高压的稳定维持为这次持续性海雾过程提供了有利的背景条件,海雾在夜间辐射冷却作用下形成;大雾期间黄渤海     

上海浦东机场平流雾的统计和监测分析

利用2000-2009年常规地面观测资料、探空资料和上海浦东机场地面气象例行观测资料,对浦东机场平流雾的气候特征和天气形势背景进行了统计分析.结果发现:浦东机场平流雾发生频次逐年增多、持续时间有增长趋势.从季节分布来看,平流雾多集中在冬春季出现.平流雾天气多发于“入海高压后部”、“副高西北侧”、“低槽气旋”、“台风外围”和“高压前部”等五类特定天气形势背景下.天气系统在空间上的特定配置使暖湿气流得以稳定的流经浦东机场,是浦东机场平流雾形成的根本原因.此外,利用浦东机场2007-2009年自动气象观测系统时间分辨率为1 min的能见度探测资料,对能见度低于200 m的平流浓雾进行分析,结果表明:浓雾爆发不是一次性完成的,稳定的浓雾形成之前会有较长时间的能见度大幅振荡过程,在能见度图谱上形成明显的“象鼻形”先期振荡特征,这一特性也给平流浓雾的监测和预警提供了依据.