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。     

利用MODIS卷云通道对长江中游一次大雾过程的监测

利用MODIS卫星通道的红外特征,对2009年1月8—11日长江中游地区的一次大雾过程进行了分析。结果表明,由于云、雾、地表所处高度不同,位于水汽的强吸收带的MODIS卷云通道(1.38μm),在辐射传输过程中对水汽吸收的程度有一定的差异,从而导致MODIS接收到这些目标物的反射率差异较明显。其中雾与地表在1.38μm波段的反射率近似相等,而与云则有明显的差别。另外,通过31波段与20波段辐射亮温差的光谱廓线分析,发现云雾的亮温差要明显小于地表。     

气象卫星高空间分辨率数据的云量计算与检验

该文利用国家卫星气象中心1998—2008年NOAA卫星的存档数据,在再定标和精定位等数据再处理基础上,利用自行研发的云检测算法及云量计算方法,生成空间分辨率为0.01°×0.01°、时间尺度为10年的逐日云量数据,并利用ISCCP和地面观测数据对计算得到的云参数进行数据质量评估。评估结果显示:利用NOAA数据的抽样云检测结果与ISCCP-DX数据相比,晴空像元检测率具有0.70左右的一致性;有云像元检测率具有60%左右的一致性。卫星计算的总云量与地面观测总云量间的月平均相关系数大于0.70。     

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.     

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。     

A CASE STUDY OF NUMERICAL SIMULATION OF SEA FOG ON THE SOUTHERN CHINA COAST

This study uses numerical simulations to examine a case of sea fog that was observed from 20 to 22 March2011 on the southern China coast. The observation dataset includes observatory data, cloud-top temperature from MODIS, GPS sonde, and data from the Integrated Observation Platform for Marine Meteorology(IOPMM). The simulations are based on the Weather Research and Forecasting(WRF) model with four distinct parameter settings.Both the observations and simulations focus on the characteristics of the fog extent, boundary layer structure, and meteorological elements near the air-sea interface. Our main results are as follows:(1) The extent of mesoscale sea fog can be well simulated when the sea surface temperature has at least 0.5 ×0.5 horizontal resolution.(2) To accurately model the vertical structure of the sea fog, particularly the surface-based inversion, vertical levels must be added in the boundary layer.(3) When these model conditions are met, the simulations faithfully reproduce the measured downward shortwave radiation, downward longwave radiation, and surface sensible heat flux during the sea fog period.     

丹东附近海域海雾产生的条件及天气学预报方法

使用常规气象观测资料和NOAA-17,EOS/ODIS卫星遥感影像资料,应用个例分析与合成分析相结合的方法,分析了2001～2005年37个海雾个例,揭示了丹东附近海域海雾的变化规律和海雾形成期间的大气、海洋背景条件,研制出了天气学预报方法并对其预报能力进行了检验。     

云辐射效应在华北持续性大雾维持和发展中的作用

观测研究发现华北地区的持续性大雾天气通常伴随高层云的存在,具有云-雾共存结构特征,为揭示云在持续性大雾维持和发展中的作用,利用中尺度数值模式WRF,结合华北雾霾观测试验期间的卫星、探空、地面观测、系留气艇、微波辐射计等观测资料,研究了2011年12月3—6日和2013年1月28—31日两次华北持续性大雾天气形成和发展演变过程。在模拟与观测对比检验研究的基础上,重点开展了云辐射效应在大雾维持和发展中作用的探讨。研究结果表明:两次大雾过程持续时间超过48 h,近地面具有偏南暖湿平流,在持续性大雾发展过程中,均出现了由单层雾发展为云-雾共存结构,一般是雾形成24 h以后有中高云移到雾层之上,云底高度在3 km以上,云厚超过3.5 km,云中以冰晶和雪晶为主。白天云-雾共存结构出现后,云-雾的反照率效应使地表接收的短波辐射减少71%—84%,地面增温效应显著减小,从而阻碍了大雾的消散过程,使大雾天气得以维持,同时由于云-雾产生的温室效应,湍流过程加强,使地面雾向上扩展,雾在稳定层内维持;夜晚云-雾共存时,由于云-雾温室效应使地表净长波辐射增大超过70 W/m2,导致地面长波辐射冷却过程减弱,并不利于雾的加强,但云对雾的增温效应有利于混合层内的湍流扩散过程,促使雾在更高的空间内得以维持。可见,在云-雾共存结构中,云辐射效应有利于低层大雾的长时间维持,对持续性大雾的形成和发展产生了重要作用。      

Analysis and high-resolution modeling of a dense sea fog event over the Yellow Sea

A ubiquitous feature of the Yellow Sea (YS) is the frequent occurrence of the sea fog in spring and summer season. An extremely dense sea fog event was observed around the Shandong Peninsula in the morning of 11 April 2004. This fog patch, with a spatial scale of several hundreds kilometers and lasted about 20 h, reduced the horizontal visibility to be less than 20 m in some locations, and caused a series of traffic collisions and 12 injuries on the coastal stretch of a major highway. In this paper, almost all available observational data, including Geostationary Operational Environmental Satellite (GOES)-9 visible satellite imagery, objectively reanalyzed data of final run analysis (FNL) issued by the National Center for Environmental Prediction (NCEP) and the sounding data of Qingdao and Dalian, as well as the latest 4.4 version of Regional Atmospheric Modeling System (RAMS) model, were employed to investigate this sea fog case. Its evolutionary process and the environmental conditions that led to the fog formation were examined by using GOES-9 visible satellite imagery and sounding observations. In order to better understand the fog formation mechanism, a high-resolution RAMS modeling of 4 km × 4 km was designed. The modeling was initialized and validated by FNL data. A 30-h modeling that started from 18 UTC 10 April 2004 reproduced the main characteristics of this fog event. The simulated lower horizontal visibility area agreed reasonably well with the sea fog region identified from the satellite imagery. Advection cooling effect seemed to play a significant role for the fog formation.     

Improved fog detection from satellite in the presence of clouds

This study analyzes radiative effect of the higher clouds over the fog layer and presents the improvement of fog detection over the Korean peninsula, utilizing satellite data of the Multi-functional Transport SATellite (MTSAT)-1R and the MODerate resolution Imaging Spectroradiometer (MODIS) and the Look-Up Table (LUT) based on Radiative Transfer Model (RTM) simulations. Fog detection utilizing the satellite data from visible (0.68 µm) and infrared (3.75 µm and 10.8 µm) channels has been evaluated in comparison with ground-based observations over 52 meteorological stations in the Korean Peninsula from March 2006 to February 2007. The threshold values for fog sensing have been derived from the difference (i.e., T_3.7–11) in brightness temperature between 3.75 µm (T_3.7) and 10.8 µm (T₁₁) during day and night, and also from the reflectivity at 0.68 µm (R_0.68) in the daytime. In the twilight, however, the difference between the temperature values at 10.8 µm and their maximum within previous 15 days (i.e., T_11max-11) are used instead, because the 3.75 µm channel is inaccurate for the fog detection at dawn/dusk. The sensitivity of the T_3.7–11 values with respect to the clouds is investigated based on the cloud variables such as its height, optical thickness, and amount. The values of T_3.7–11 are the most sensitive to cloud height, followed by cloud optical thickness and effective radius, while R0.68 is insensitive to cloud height. The sensitivity is examined with various conditions of cloud phases and day/night. Sixteen cases among eighteen fog occurrences, which have been unable to be sensed by using only the conventional threshold values, are successfully detected with the additional LUT corrections, indicating a significant improvement. The method of fog detection in this study can be useful to the Communication, Ocean, and Meteorological Satellite (COMS) Meteorological Data Processing System (CMDPS) by reducing the cloud effect on fog sensing.     

风云三号微波观测资料的海雾同化模拟

数值模式边界层物理过程和初值场条件的欠缺是海雾模拟准确率偏低的主要原因。本文为改进模式初始场,开展针对海雾模拟的卫星观测资料同化试验,将质量控制和偏差订正后的FY-3A卫星微波湿度计（MWHS）和微波温度计（MWTS）的优选通道数据,经3DVar（Three-dimensional variational data assimilation）进入WRF模式以试验其对黄、渤海海雾模拟的影响。通过分析静止气象卫星检测到的海雾区模拟大气温、湿场同化分析增量,发现代表环境场条件的海雾类型及模式对其模拟能力的差异,显著影响了同化效果,表现为同化对模式模拟能力较强的平流冷型海雾改进明显,对模拟效果不甚理想的非典型混合过程中的暖型海雾阶段则基本没有改进效果。为寻找原因,对包括海雾区低层大气模拟场逆温结构在内的温湿度场与邻近探空观测进行了对比,分析了随时间演变的海雾格点温、湿场同化分析增量,发现冷型海雾区格点同化分析增量能弥补观测—模拟差异,使气温调减,相对湿度调增,同时水汽和液态水也出现负相关的变化,边界层相关热力动力场同化分析增量在垂直方向也有配合迹象,相比而言,主体是暖型海雾的非典型过程则未见此类现象和其他的有益调整迹象。     

A comparison of MODIS-derived cloud amount with visual surface observations

Two main sources for global cloud climatologies are visual surface observations and observations made by spaceborne sensors. Satellite observations compared with surface data show in most cases differences ranging from − 15% up to − 1%, depending on sensor and observation conditions. These differences are partially controlled by sensors' cloud detection capabilities — a higher number of spectral bands and higher spatial resolution are believed to allow discrimination of clouds from land/ocean/snow background. A Moderate-Resolution Imaging Spectroradiometer (MODIS) produces images of the atmosphere in 36 spectral bands with a spatial resolution of 250–1000 m, thus having a capacity for cloud detection far more advanced than other operating sensors. In this study, instantaneous MODIS cloud observations were compared with surface data for Poland for January (winter) and July (summer) 2004. It was found that MODIS observed 4.38% greater cloud amount in summer conditions and 7.28% in winter conditions. Differences were greater at night (7–8%) than in daytime (0.5–7%) and correlations ranged between 0.577 (winter night) and 0.843 (winter day, summer day and night).     

西藏林芝地区混合像元MODIS地表温度产品验证

西藏林芝地区地形复杂、土地覆盖类型多样,MODIS地表温度 (land surface temperature,LST) 产品验证面临处理混合像元的难题,为获得与像元尺度 (1 km) 相匹配的地表温度数据,该文提出采用多点同时观测结合面积加权的方法,将该方法应用于验证林芝地区2013年6月10日夜间晴空MODIS/LST产品。结果显示:单点观测对像元的代表性不足,容易低估产品精度 (10个样本均方根误差为2.2 K),面积加权法可获得综合性更好的地面LST信息,对MODIS/LST产品的精度给出更高的评价 (30个样本均方根误差为1.40 K)。对于地表类型混杂程度高且地势较为平坦的像元,面积加权法的优势更为明显,可将卫星LST产品与地面LST之间的差异由3 K降至1 K以内。     

Comparison between MODIS-derived Day and Night Cloud Cover and Surface Observations over the North China Plain

Satellite and human visual observation are two of the most important observation approaches for cloud cover. In this study, the total cloud cover(TCC) observed by MODIS onboard the Terra and Aqua satellites was compared with Synop meteorological station observations over the North China Plain and its surrounding regions for 11 years during daytime and7 years during nighttime. The Synop data were recorded eight times a day at 3-h intervals. Linear interpolation was used to interpolate the Synop data to the MODIS overpass time in order to reduce the temporal deviation between the satellite and Synop observations. Results showed that MODIS-derived TCC had good consistency with the Synop observations; the correlation coefficients ranged from 0.56 in winter to 0.73 in summer for Terra MODIS, and from 0.55 in winter to 0.71 in summer for Aqua MODIS. However, they also had certain differences. On average, the MODIS-derived TCC was 15.16%higher than the Synop data, and this value was higher at nighttime(15.58%–16.64%) than daytime(12.74%–14.14%). The deviation between the MODIS and Synop TCC had large seasonal variation, being largest in winter(29.53%–31.07%) and smallest in summer(4.46%–6.07%). Analysis indicated that cloud with low cloud-top height and small cloud optical thickness was more likely to cause observation bias. Besides, an increase in the satellite view zenith angle, aerosol optical depth, or snow cover could lead to positively biased MODIS results, and this affect differed among different cloud types.     

海雾历史检索数据库的设计和实现

针对我国海雾预报业务及科研需求,收集整理了中国近海最近10年海雾个例数据,开发了海雾个例数据库系统,实现了国家、省、市级预报员和科研人员对海雾个例相关数据的实时调阅和打包下载。系统提供不同检索条件的多功能查询和海雾个例的实时查阅以及历史数据、卫星监测产品等资料的下载功能。为预报员更有效地开展实时预报提供了便捷参考,也为科研人员从事海雾研究提供了详细和全面的观测数据和分析产品支撑。     

FY-2G卫星冬夏云量产品偏差分析

开展卫星反演云量的精度评估是业务应用的基础,也是充分发挥卫星观测效益的前提。利用同类卫星产品EOS Aqua/MODIS云产品,选取2015年6月和12月共80个个例,包括43个白天个例,37个夜间个例。采用交叉比对方法对FY-2G云量产品进行相对偏差分析。结果表明:FY-2G与Aqua/MODIS计算云量总体趋势相当,无论从时间分布（白天和夜间）还是季节分布（6月和12月）上看,FY-2G与Aqua云量相对偏差较为稳定,FY-2G反演云量小于Aqua/MODIS反演云量。匹配个例中FY-2G平均云量为72.81%,Aqua/MODIS平均云量是76.19%,两者相关系数为0.74。两者绝对偏差小于5%的像元比例为72.34%;云量偏差绝对值小于15%的像元比例为79.51%。FY-2G与Aqua/MODIS云量偏差主要来自各自卫星的观测能力与所采用的云检测算法。与具有36个探测通道、星下点最低空间分辨率为0.01°×0.01°的Aqua/MODIS观测数据相比,FY-2G所具有的5通道、星下点最高空间分辨率为0.05°×0.05°的观测数据会出现对云,尤其是破碎云和薄卷云的漏检。两种具有不同时空属性的数据在匹配处理时采用的不同算法也会在比对分析中引入偏差。     

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。     

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。      

一种基于卫星遥感和数值预报产品的雾预报方法

以气象卫星云图为基础, 应用云雾光谱特征和结构特征进行雾区的动态检测和提取;并利用地面自动气象站资料,采用诊断分析方法探讨雾区变化与多气象要素的关系。分析表明:雾区移动速度与地面风速有关,一定的相对湿度、地气温差和风速大小等要素阈值可以作为雾的排空条件。利用经修正的中尺度数值天气预报模式输出的气象要素产品,对卫星遥感雾区进行0~2 h的外延预报,进而建立了一个大雾短时临近预报业务平台,对2009年和2010年多雾季节的1—4月大雾过程应用统计结果表明,该方法对大雾短时临近预报具有一定的效果。     

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。