一次黄海海雾的数据同化试验与形成机制研究

选取2012年4月14日的一次存在东西2片雾区的黄海春季海雾为研究对象,借助WRF（Weather Research and Forecasting）模式,采用循环3DVAR（3-Dimensional Variational）数据同化方案,考虑了湿度控制变量的背景误差协方差CV6,进行了AIRS（Atmospheric Infrared Sounder）卫星温度与湿度廓线数据的同化试验,并基于同化试验结果探讨了此次海雾的形成机制。同化试验结果表明：同化 AIRS 卫星温度与湿度廓线数据后,模式能成功再现海雾的形成过程,特别是东西2片雾区之间的晴空区的存在,这归功于AIRS数据的同化能够显著改善海上大气边界层的温湿结构、影响海雾的低层高压的范围与强度;机制分析揭示：东西2片雾均为典型的平流冷却雾,但二者厚薄和气团来源不同;海上高压控制黄海西岸陆地的暖空气入海,受低海温的冷却作用降温先形成逆温层,然后逆温层底部生成了较薄的西侧雾区;来自黄海中部的空气向东北移动至朝鲜半岛西部海域,高压下沉增温形成一个顶部较高的稳定层,从而生成较厚的东侧雾区;高压中心下沉区内,近海面风速小使得机械湍流弱,空气增温与海温暖舌共同作用下使得近海面气海温差小,海雾无法生成导致了晴空区的存在。     

多种机器学习方法在京津冀地区低能见度天气预报中的应用

利用2017—2021年的ERA5再分析资料和京津冀国家站地面资料,结合多种机器学习方法建立预报模型,开展轻雾、大雾客观预报。探讨了再分析资料、地形因素的影响,并结合多模型集成、统计消空进一步优化模型。结果表明:(1) XGBoost (eXtreme Gradient Boosting)、LightGBM (Light Gradient Boosting Machine)、随机森林等集成学习方法的预报效果均优于决策树方法;(2)在引入ERA5再分析资料、地形建模后,XGBoost、LightGBM模型的预报性能显著提高。相比仅使用地面要素建模,大雾预报的TS (Threat Score)提升了30%、32%,达到0.52、0.49,命中率分别为0.62、0.87。此外,经过多模型集成后,轻雾、大雾预报的TS提升到了0.51、0.54;(3)2022年秋季一次大雾过程中,本方法提前72 h准确预报了京津冀地区的大雾,其中以LightGBM模型表现最好。0~72 h轻雾预报和0~36 h逐小时大雾预报的TS均达到0.3,预报准确率、时效性均优于ECMWF (European Center for Medium Weather Forecasting)模式。     

沪宁高速公路一次复杂性大雾过程的数值模拟试验

为探明高速公路大雾天气的成因和演变规律,揭示雾影响交通能见度的机理,本文根据布设于我国沪宁高速公路沿线的环境气象自动监测系统(AWMS)实测资料和覆盖公路周边地区的常规气象台站观测资料,筛选出2009年11月7日发生在沪宁高速公路上的一次典型复杂性大雾天气过程.在分析天气实况的基础上,应用高时空分辨率的非静力中尺度数值预报模式WRF3.1,结合NCEP 0.5°×0.5°气象再分析资料,对该过程进行了数值模拟;利用实测资料对模拟结果进行了验证,并剖析了此次复杂性大雾过程形成的动力、水汽和热力条件.研究表明:(1)本次大雾前后的天气形势相对稳定,江苏地区主要受入海反气旋西南侧东南气流影响,整个大雾过程中地面风力始终微弱,为大雾形成提供了有利的动力条件;(2)模式模拟的由大气液态含水量条件判别的成雾区分布与实测雾区范围基本吻合;(3)模式模拟的能见度与AWMS实测能见度十分接近;(4)本次大雾过程最初是团雾雏形,在夜间辐射冷却作用下,转为辐射雾,之后,来自东南海上的暖湿空气平流进入江苏陆地后,所产生的平流雾雾体与原有辐射雾雾体结合发展为范围更大的辐射平流混合雾;(5)日出后短波辐射增温是此次复杂性大雾雾体得以快速消散的主要原因.     

HAZE-TO-FOG TRANSFORMATION DURING A LONG LASTING, LOW VISIBILITY EPISODE IN NANJING

Haze-to-fog transformation during a long lasting, low visibility episode was examined using the observations from a comprehensive field campaign conducted in Nanjing, China during 4-9 December 2013. In this episode, haze was transformed into fog and the fog lasted for dozens of hours. The impacts of meteorological factors such as wind, temperature (T) and relative humidity (RH) on haze, transition and fog during this episode were investigated. Results revealed significant differences between haze and fog days, due to their different formation mechanisms. Comparison was made for boundary-layer conditions during hazy days, haze-to-fog days and foggy days. Distributions of wind speed and wind direction as well as synoptic weather conditions around Nanjing had determinative impacts on the occurrences and characteristics of haze and fog. Weakened southerly wind in southern Nanjing resulted in high concentration of pollutants, and haze events occurred frequently during the study period. The wind speed was less than 1 m s-1 in the haze event, which resulted in a stable atmospheric condition and weak dispersion of the pollutants. The height of the temperature inversion was about 400 m during the period. The inversion intensity was weak and the temperature-difference was 4°C km-1 or less in haze, while the inversion was stronger, and temperature-difference was about 6°C km-1, approaching the inversion layer intensity in the fog event. Haze event is strongly influenced by ambient RH. RH values increased, which resulted in haze days evidently increased, suggesting that an increasing fraction of haze events be caused by hygroscopic growth of aerosols, rather than simply by high aerosol loading. When RH was above 90%, haze aerosols started to be transformed from haze to fog. This study calls for more efforts to control emissions to prevent haze events in the region.     

Fog detection using geostationary satellite data: Temporally continuous algorithm

A fog detection algorithm that uses geostationary satellite data has been developed and tested. This algorithm focuses on continuous fog detection since temporal discontinuities, especially at dawn and dusk, are a major problem with current fog detection algorithms that use satellite imagery data. This is because the spectral radiance at 3.7 μm contains overlapping emissive and reflectance components. In order to determine the radiance at 3.7 μm under fog conditions, radiative transfer model simulations were performed. The results showed that the radiance at 3.7 μm obviously varies with the solar zenith angle, and the brightness temperature differences between 3.7 μm and 10.8 μm are completely dissimilar between day and night (positive and varying with the angle during the daytime, but negative and constant at night). In this algorithm, a dynamic threshold is used as a function of the solar zenith angle. Moreover, additional criteria such as infrared, split-window channels, and a water vapor channel are used to remove high-level clouds. Also, the visible reflectance (0.67 μm) channel is used in the daytime algorithm because visible channel images are very practical for confirming a fog area with the high reflectivity and the smooth texture. The clear-sky visible reflectance for the previous 15 days was also employed to eliminate the surface effect that appeared during dawn and dusk. As the results, fog areas were estimated continuously, allowing the lifecycle of the fog system, from its development to decline, to appear obviously in the resulting images. Moreover, the estimated fog areas matched well with surface observations, except in a high latitude region that was covered by thin cirrus clouds.     

On the fog variability over south Asia

An increasing trend in fog frequencies over south Asia during winter in the last few decades has resulted in large economical losses and has caused substantial difficulties in the daily lives of people. In order to better understand the fog phenomenon, we investigated the climatology, inter-annual variability and trends in the fog occurrence from 1976 to 2010 using observational data from 82 stations, well distributed over India and Pakistan. Fog blankets large area from Pakistan to Bangladesh across north India from west to east running almost parallel to south of the Himalayas. An EOF analysis revealed that the fog variability over the whole region is coupled and therefore must be governed by some large scale phenomenon on the inter-annual time scale. Significant positive trends were found in the fog frequency but this increase is not gradual, as with the humidity, but comprises of two distinct regimes shifts, in 1990 and 1998, with respect to both mean and variance. The fog is also detected in ERA-Interim 3 hourly, surface and model level forecast data when using the concept of “cross-over temperature” combined with boundary layer stability. This fog index is able to reproduce the regime shift around 1998 and shows that the method can be applied to analyze fog over south Asia. The inter-annual variability seems to be associated with the wave train originating from the North Atlantic in the upper troposphere that when causing higher pressure over the region results in an increased boundary layer stability and surface-near relative humidity. The trend and shifts in the fog occurrence seems to be associated with the gradual increasing trend in relative humidity from 1990 onwards.     

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。     

南海西北部一次海上海雾的微物理及化学特性分析

利用2017年3月MICAPS资料、欧洲气象中心再分析ERA-Interim数据及在南海西北部海上的海雾观测数据,分析了南海西北部一次海上海雾的微物理特征和雾水化学特性,并将海上海雾与南海岸边海雾进行对比分析。结果表明:此次海雾为南海偏南暖气流移至冷海面发生冷却并达到饱和而形成。海雾过程中气压与气温变化趋势相反,相对湿度不断增加,雾滴数浓度、液态含水量和平均直径的平均值分别为198 cm-3、0.116 g/cm3和5.6 μm。相比广东湛江东海岛和广东茂名博贺地区岸边海雾个例,本次海上海雾水汽充足,雾滴偏大。本次海雾属于酸性海雾,pH值变化范围为2.51~3.50,海雾后的雨水样本pH值则为4.05。海雾发生初期电导率比其它阶段高很多,说明海雾发生的初始阶段雾水溶解了大量的气溶胶。海上雾水中Na+和Cl-浓度最高,浓度分别为32 535 μmol/L和53 466 μmol/L,K+浓度远高于Mg2+和Ca2+,而东海岛岸边海雾相反。      

Fog collection in the western Mediterranean basin (Valencia region, Spain)

Four different mountainous locations were selected in the Valencia region, East coast of the Iberian Peninsula, for fog water collection studies. Data for 2004 were obtained by means of an instrument ensemble consisting essentially of a passive cylindrical fog water collector, a raingauge, a wind direction and velocity sensor and a temperature and humidity probe. An approximate data reduction technique was also found for this specific ensemble to eliminate the simultaneous rain water component from the fog water measurements. Main results indicate that fog water collection holds significant potential in this region, and especially for southern locations. Annual rates of fog water yield can be as high as 7.0 l/m²/day in the southern locations, in contrast to 2.0 l/m²/day collected at one site in a northern location. The highest summer fog water yield was 4.6 l/m²/day, a relatively large value. Except for the summer period, fog episodes delivering sizeable water volumes are inherently coupled to rainfall. Hourly frequencies of fog collection were also examined to show a distinct daily cycle in summer, denoting orographic fog formation during this period. Lastly, winds were analysed to resolve the most suitable directions for fog collector alignment.     

2004-11-28～12-04华北等地大雾天气的中尺度分析

对2004年11月28日~12月4日发生在华北及黄河中下游地区的持续性大雾天气进行了中尺度分析,结果发现,地面中尺度辐合线(区)与辐射降温有利于形成辐射雾。此次大雾在持续过程中性质发生了改变,由辐射雾转变为平流雾。若东北地区的地面冷高压中心西侧或南侧另有一小高压环流,通常为一种有利于华北及中东部地区产生或维持大雾天气的环流型,在其南侧及西南侧产生的准地转流和非地转流在华北及黄河中下游地区的交汇为该地区带来了丰沛的水汽。     

Characterization of aerosol optical depth, aerosol mass concentration, UV irradiance and black carbon aerosols over Indo-Gangetic plains, India, during fog period

Every year during winter months (December?CJanuary) fog formation over Indo-Gangetic plains (IGP) of Indian region is believed to create numerous hazards. The present study addresses variations in aerosol optical properties, aerosol mass concentration and their impact on solar irradiance for pre-during-post fog conditions of December 2004 over IGP, India. Continuous measurements on aerosol optical depth (AOD), total aerosol mass concentration, black carbon (BC) aerosols, UV_ery and UVA were carried out for pre, during and post fog periods over study site of Allahabad, India, during December 2004 as a part of Aerosol Land Campaign-II conducted by Indian Space Research Organization (ISRO). High aerosol mass concentrations were observed during fog and post-fog periods. Accumulation mode particle loading was found to be high during pre-fog period and coarse mode particle loading was observed to be high during fog and post-fog periods. Considerable reduction in UV_ery and UVA irradiance was observed during fog period compared with pre and post-fog periods. Analysis of NOAA-HYSPLIT model runs suggested that enhanced biomass burning episodes down-wind to the study area increased the concentration of AOD and BC.     

安徽省不同等级雾和重度霾时空分布特征及地面气象条件比较

雾和霾都是低能见度天气,生成条件相似。利用安徽78个地面站逐时观测资料,基于雾、霾发生物理条件,建立了不同等级雾日和重度霾日的观测诊断方法,重建了不同等级雾和重度霾的时序资料。根据各站强浓雾发生的同步性,将安徽分为5个雾、霾分布特征不同的区域,探讨了各区域不同等级雾及重度霾出现时地面气象条件的异同。结果表明:（1）安徽省强浓雾主要是辐射雾。强浓雾、浓雾和大雾空间分布形势大体一致,淮河以北东、西部和江南都属于强浓雾高发区,但各地强浓雾的时、空分布特征和影响系统不同;重度霾有明显的北多、南少、山区最少的分布特征。（2）强浓雾年变化呈双峰型分布,峰值在1月和4月,日变化为单峰型,峰值在06时;而重度霾年变化为单峰型,峰值在1月,日变化为双峰型。（3）在强浓雾的高发时段（02—08时）,强浓雾时降温幅度最大,比重度霾平均高1℃,风速显著偏低,超过75%的样本风速低于1.5 m/s,且无明显主导风向;而重度霾时,风速比雾时明显要大,个别区域有超过75%的样本风速大于1.5 m/s,且以西北风到东北风为主。说明重度霾能否演变为强浓雾的关键地面气象因子是风速、风向和降温幅度。      

北京2009~2013年期间持续性大雾的类型、垂直结构及物理成因

北京地区持续性大雾天气近几年呈显著增加趋势,但由于缺乏高时间分辨率的雾微物理和大气廓线数据,限制了对大雾垂直结构和物理成因的深入了解。本文基于美国Radiometrics公司生产的35通道MP-3000A型微波辐射计廓线仪(Microwave Radiometer Profiler,简称MWRP)及常规气象和卫星观测资料分析研究了2009~2013年期间北京地区13次大雾天气过程的类型、垂直结构特征及其产生的物理成因。按照雾产生的基本条件,将13次大雾天气主要划为平流雾和蒸发雾两类,辐射雾存在于持续性大雾过程中,不做单独划分。平流雾的平均雾顶高度不超过1.0 km,而蒸发雾的平均雾顶高度在0.5~1.5 km之间。平流雾主要是由来自西南和东南的暖湿平流移经北京地区冷下垫面后冷却降温过程产生,强逆温的形成有利于雾的持续发展。而蒸发雾是由本地区降水蒸发冷却形成,或是冷平流移经暖湿下垫面形成。按照微波辐射计连续观测的雾宏微观垂直结构特征,将13次大雾天气过程又划分为单一雾结构和云雾共存结构,并采用卫星和地面气象观测数据对部分典型雾个例进行了比较验证研究。结果表明,在13次大雾天气中,平流雾和蒸发雾各占69%和31%。由此说明北京地区持续性大雾天气主要是由暖湿平流过程和降水蒸发冷却过程造成,与天气过程的异常密切相关。单一雾结构仅占15%,而云雾共存结构占近85%,且持续三天以上的大雾天气基本具有云雾共存结构。     

宁夏雾日和霜日的变化趋势分析

利用1961～2012年宁夏22个气象台站逐日天气现象、能见度、相对湿度资料,采用气候倾向率、趋势系数、最大熵谱分析、突变分析等方法,分析了宁夏各区域雾日数和霾日数的空间分布及变化趋势。结果表明：宁夏雾目数、霾日数均呈南北多、中间少的空间特征,但雾日数南部最多,而霾日数北部最多。近52a来,雾日数除南部山区呈不显著的减少趋势外,其他3个区域均呈增多趋势,而霾日数各区域均呈显著的增多趋势;另外,二者均有明显的阶段性演变特征,1961—1980年为明显偏少阶段,1981～2000年为波动变化阶段,2001年以后为明显偏多阶段;雾日数具有较明显的准7．5a,4．3a周期振荡,霾日数具有较明显的准4．6a、3,0a周期振荡;各区域雾日数与霾日数均未发生突变现象。     

MODIS遥感数据在我国台湾海峡海雾监测中的应用

海雾是一种常见的灾害性天气现象。以我国台湾海峡为示范研究区, 利用新一代卫星传感器MODIS的可见光和红外探测通道数据, 在分析海洋、中高云、低云和海雾等不同下垫面的MODIS光谱辐射特征基础上, 选择对海雾具有敏感反应的探测通道, 通过综合判识建立台湾海峡海雾遥感监测模型。利用该模型对2004-2007年我国台湾海峡海雾事件进行监测, 并用福建沿海5个地面气象观测站的能见度数据对监测结果进行验证分析。结果表明:基于MODIS数据的海雾遥感监测模型能够较准确地对台湾海峡海雾分布和发展过程进行监测, 从地面观测数据与卫星监测结果对比验证来看, 海雾监测的准确率可达80 %以上, 具有较高的业务化应用前景。     

国内外雾预报技术研究进展

大雾是引起低能见度的主要天气现象.提高雾的预报技术水平是确保交通安全的重要措施.从统计和数值预报两个方面,回顾了过去几十年来国内外在雾预报技术上的主要研究进展,并总结了各种方法的特点及存在的缺陷.在某些情形下,新统计方法的应用提高了雾的预报准确率,但仍然无法摆脱统计方法本身的缺陷.相比较而言,数值模式在大雾预报方面具有更广泛的应用和更大的潜力.在目前的计算机水平下,使用高分辨率的一维雾模式与中尺度天气模式相结合的方法,在一定程度上可以提高雾的预报准确率,该方法在大雾易发区的机场及高速公路沿线具有重要的应用价值.随着计算机能力的不断提高,包含大雾形成和演变的各种复杂过程、具有先进资料同化过程的高分辨率三维雾模式,以及集合数值预报系统将是未来的发展方向.     

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.     

EVOLUTION OF LIQUID WATER CONTENT IN A SEA FOG CONTROLLED BY A HIGH-PRESSURE PATTERN

On March 16–17, 2008, a sea fog occurred in Dianbai in the west of Guangdong Province and was accompanied by a high-pressure synoptic system. Using comprehensive observation datasets, this study analyzes the evolution of liquid water content during this sea fog and investigates the relationships between liquid water content and the average diameters and count densities of fog droplets, air temperature, wind speed and turbulence exchanges. The main results are presented as follows. (1) The sea fog showed a quasi-periodic oscillation characteristic, i.e., it developed, disappeared and then developed again. (2) During the sea fog, the number of fog droplets changed significantly while the changes in average diameter of the fog droplets were relatively small. The development and disappearance of the sea fog correlated significantly with the fog droplet numbers. (3) The air-cooling mechanism played a significant role in sea fog formation and development. However, the influences of this mechanism were not evident during fog persistence. (4) During sea fog formation, weak turbulence exchanges were helpful for fog formation. During sea fog development and persistence, liquid water content increased when turbulence exchanges weakened, and vice versa. The changes in turbulence exchanges were closely related to the quasi-periodic oscillations observed in sea fog presence.     

基于深度学习的公路能见度分类及应用

以VGG16为基准模型,融合批归一化处理、全局平均池化和联合损失函数,提出了一种基于卷积神经网络的高速公路雾天能见度等级分类方法。实验结果表明,改进后的神经网络模型的平均识别正确率达83.9%,相较于其他几种模型具有较高的正确率和较好的收敛性。将模型封装入业务系统后进行业务化检验,其平均识别正确率可达84.9%,且白天识别效果要优于夜间。通过系统监测到2019年4月4日京沪高速发生了一次团雾动态生消过程。该次团雾过程具有移动快、范围小、生存时间短的特征。系统的应用能够为交通管理部门应对团雾发生时的智能管控和决策调度提供技术支持。     

一次深厚浓雾过程的边界层特征和生消物理机制

2007年12月13-14日,南京出现一次厚度达600 m、持续近14 h的浓雾过程,其中强浓雾阶段维持4 h.通过系留气球边界层探测系统、涡动协方差测量系统、雾滴尺度分布和自动气象站等外场试验资料分析了此次深厚浓雾过程的边界层结构特征和生消物理机制.结果表明,此次雾过程首先由地面辐射冷却形成贴地雾层,而后因低空平流冷却形成低云.在发展阶段,伴随低云不断下伸,贴地雾层不断抬升.在贴地雾层受到地面弱冷空气平流降温影响下,雾中微物理过程迅速发展,雾滴数密度、含水量、平均直径、最大直径等微物理参数在15 min内跃增,雾体爆发性升高,最终导致地面雾和低云上下贯通形成深厚雾层,地面能见度骤降至15 m以下.雾体爆发性增强时,地面垂直动量通量和向下长波辐射通量密度增大,净辐射趋于零.整个雾过程中,由于贴地层持续弱冷平流降温和上层雾阻碍了下层雾的辐射降温,二者的共同作用使贴地强逆温结构始终维持.