The LOWTRAN-7 code was used to simulate remote sensing of water vapor over 20 different surface covers. The simulation was used to optimize the water vapor channel selection and to test the accuracy of the remote sensing method. The channel selection minimizes the uncertainty in the derived water vapor due to variations in the spectral dependence of the surface reflectance. The selection also minimizes the sensitivity of the selected channels to possible drift in the channel position. The use of additional MODIS channels reduces the errors due to the effect of haze, subpixel clouds and uncertainties in the temperature profile. Remote sensing of the variation of water vapor from day to day will be more accurate, because the surface reflectances vary slowly with time. The method was applied to Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data.

文中讨论了利用全球定位系统探测水汽的原理。为了反演出大气垂直积分水汽或可降水,需要计算加权“平均温度”<i>T</i>_m.<i>T</i>_m与对流层温度廓线和水汽垂直分布有关,但从北京气象台1992年探空资料分析表明,它与表面温度存在着很好的线性关系。文中应用中尺度气象模式,给出了适合于中国东部地区和不同季节的关于<i>T</i>_m和表面温度<i>T</i>_s的线性回归方程。

本文利用ECMWF再分析资料ERA40和中国160站的降水资料，分析了我国华北地区1958年1002年夏季的大气水汽含量和水汽输送的基本气候特征，研究了华北夏季旱涝年的大气水汽含量和水汽输送异常情况，最后利用线性回归的方法探讨了该地区大气水汽含量和水汽输送的变化趋势。结果表明：华北地区夏季降水的大气水汽来源主要有3支：来自孟加拉湾的水汽、来自我国南海和西太平洋的水汽以及中高纬西风带的水汽输送。华北地区对流层低层以经向水汽输送通量为主，到了中高层则以纬向输送通量为主；与华北地区夏季旱涝密切相关的异常水汽输送主要是南海和西太平洋以及西风带水汽输送异常，华北地区南边界水汽输入异常和东边界水汽输出异常是造成华北夏季旱涝年水汽收支异常的主要原因；近半个世纪以来，伴随着华北干旱化的加剧，华北地区南边界输入的大气水汽呈现显著的减少趋势。

全球定位系统(GPS)卫星信号穿过大气层时发生的偏折和延迟, 可以用来反演信号传播路径上的大气水汽总量。为 获取区域高精度的大气水汽三维分布, 借助分布密集的地基GPS观测网及其斜路径水汽观测, 建立新的观测约束层析模型, 提出以高斯函数为水平约束, 区域逐月多年探空观测为垂直约束, 即以平均量为先验值, 以标准偏差为权重矩阵的新方法;并 在层析算法中引入地面观测, 以提高整体尤其是低层反演精度。三维水汽层析网格模型基于长江中游鄂东区域的22站地基 GPS加密网搭建, 实时解算系统可逐时输出三维水汽产品。三维湿折射度和水汽密度可以分别由斜路径的湿延迟总量和水 汽总量观测反演获得。以2010年开展的汛期联合加密探空观测为参照, 对三维层析的总体反演精度、低层反演精度、层析区 域中心与边缘反演精度进行了对比和分析。结果显示:整体样本检验三维水汽密度平均偏差为-0.63g/m³,标准偏差为 1.22g/m³,与探空相关系数为0.98;水汽密度与探空资料的相关比湿折射度与探空资料的相关好;对于不同层析区域, 中心 区域观测元数量较为丰富, 使得位于中心的层析精度好于整体和边缘;加入低层观测的层析结果与探空的相关比未加低层观 测时的好, 低层观测的加入提高了层析与探空的相关, 减小了低层层析标准差、区域中心和2km 以上层析的均差, 有效提高 了反演精度;低层观测的加入对整体标准差的影响, 可能与加剧观测方程中长度矩阵元素间的量级差异有关。

<p>基于高光谱遥感图像数据的大气参数反演和一体化辐射校正具有重要研究意义和应用价值。首先,通过6S模型辐射传输计算分析了EO\|1/Hyperion遥感影像在940和1 130 nm附近水汽吸收区域的光谱吸收特点。其次,采用两通道比值法和三通道比值法,比较了不同波段组合的大气含水量高光谱遥感反演精度并进行了敏感性分析,模拟实验结果表明采用三波段比值算法的相关系数和均方根误差均优于对应的两波段算法。最后,利用张掖地区2008年3景EO\|1 Hyperion高光谱遥感影像,反演了大气含水量,并与地基CE-318太阳分光光度计测量数据进行对比验证,结果表明:1 124 nm水汽吸收通道反演精度优于940 nm,两通道和三通道比值法的均方根误差分别为0.369和0.128 g/cm2,三通道比值方法优于两通道比值方法,与地面观测结果一致。</br>&nbsp;</p>

This study mainly discusses atmospheric water vapor retrieval over cloud cover area on land with the help of a newly developed surface emissivity parameter estimation method in microwave bands. In the retrieval method, the atmospheric water vapor sensitivity parameter-ratio of brightness temperature polarization difference at frequencies 18.7 and 23.8 GHz (ΔTb1.87/ΔTb23.8)-is used to retrieve water vapor, and the surface emissivity parameter-ratio of surface emissivity polarization difference at frequencies 18.7 and 23.8 GHz (Δε18.7/Δε23.8) that corresponds to ΔTb18.7/ΔTb23.8 is a key parameter that affects the final precision of retrieved atmosphere water vapor. In order to estimate Δε18.7/Δε23.8 in cloudy condition, we first estimated the value of Δε18.7/Δε23.8 in clear condition using Advanced Microwave Scanning Radiometer for EOS (AMSR-E) brightness temperature and related MODIS atmospheric products. At the same time, it was found that gradient information derived separately from ΔTb18.7/ΔTb23.8 and Δε18.7/Δε23.8 and very good correlation with each other. Based on this good correlation, the Δε18.7/Δε23.8 in cloudy condition was estimated using corresponding==and adjacent 8 days Δε18.7/Δε23.8 in clear condition. With the estimated Δε18.7/Δε23.8, we retrieved atmospheric column water vapor using lookup table method in cloudy condition over land. As a validation source data, the SuomiNet GPS-retrieved precipitable water (PW) vapor is used to validate the retrieved water vapor in this study. According to validation, the correlation coefficient of the two is 0.94 and the root-mean-square-error (RMSE) is 4.85 mm. It is a great improvement in water vapor retrieval using microwave in cloud cover area on land.

The water vapor amount is simulated through its statistical relation to the ratios of reflectance in several channels, which are selected and grouped from the 940 nm weak water vapor absorption band and the vicinal window region. The simulation results of water vapor amount have an average relative error of 6% by compared with the independent radiosonde observation.

主要介绍通过遥感影像来反演大气水汽的算法 ,两通道比值法和三通道比值法。并用环渤海地区的MODIS影像对该地区的水汽进行了反演

本文讨论了利用差分吸收法来遥感大气中的水汽。水汽透过率用辐射计测量，水汽含量由我们自行编制的红外辐射大气透过率计算程序计算。在此同时还观测了气象参数，以确定光路上的水汽含量。结果表明，水汽长度的计算值和测量值非常吻合，回归曲线的相关系数达０．９７，均方根偏差为０．０１５ｇ／ｃｍ２。文中最后讨论误差来源和改善精度的途径，并指出对其它气体分子的吸收和气溶胶的消光进行修正的必要性。

利用太阳辐射计CE318近红外940nm水汽吸收通道和监近窗 区通道反演大气柱水汽总量，由于大气在940nm附近有水汽吸收，该通道不能采用通常Langley法处理，而采用改进的Langley法。利用 MODTRAN3.7模式模拟出太阳辐射计940nm通道透过率与水汽量关系常数，考虑了通道的光谱响应函数和不同大气模式的影响，模拟结果表明窄通道 （小于10nm）上述关系常数受大气模式影响不大。总消光剔除气溶胶和分子散射，就得出水汽的透过率，从透过率反演水汽量。处理了敦煌和青海湖辐射校正 场，1999年7月场地大气特性测量兼FY-1C辐射定标期间的数量，给出了同步观测6天卫星过顶前后15min平均水汽量，该水汽量用于FY-1C卫星 遥感器辐射定标时辐射传输模式的输入参数。结果表明太阳辐射计是一种便携有效测量水汽量仪器。

<FONT face=Verdana>根据MODIS卫星第18和19波段的波段特征， 首先从理论上证明从这两个波段表观反射率的比值反演大气可降水量的可行性， 其次利用MODTRAN模型按照中纬度冬季和夏季两种大气模式对该比值与大气水汽的关系进行模拟， 并建立了反演大气水汽的公式。利用贵州地区高空探测数据对反演公式进行验证， 并与EOS发布的MODIS近红外水汽反演结果进行比较， 发现该公式的反演结果更接近实际探测的结果。由于在反演过程中不必考虑地表覆盖和反射率的差异， 摆脱了传统的根据查找表反演水汽的方式， 并且直接由18、 19波段表观反射率的比值计算大气可降水量， 相对于传统算法更易于业务化运行。</FONT>

该文介绍了利用搭载在FY3A卫星上的中分辨率光谱成像仪（MERSI）的近红外(NIR)通道反演大气水汽总量（PWV）的方法。根据预先建立的查找表，大气水汽总量可以通过水汽通道与窗区通道的卫星测值相比反演得到。对MERSI近红外水汽通道灵敏度进行估算，结果表明：处于吸收带两翼的905 nm和980 nm通道对不同水汽量的敏感性表现比较接近，对较大水汽含量最为敏感；当水汽较弱时，强吸收的940 nm通道非常敏感。基于这3个通道对水汽含量敏感性的不同表现，采用3个通道水汽总量的加权平均值作为PWV产品的最终反演值。文中设计了水汽总量业务算法反演流程，并基于FY3A/MERSI最新观测资料进行晴空大气水汽总量的业务处理生成试验，顺利生成MERSI单轨道水汽总量产品及日拼图中国区域产品和全球产品，同时生成多天合成产品，产品反映出MERSI具有较好的近红外水汽探测能力。将卫星反演结果与探空数据进行初步比对检验，显示卫星反演值有20%～30%系统性偏低，需要进一步改进反演查找表。

The annual cycle of precipitable water vapour is inferred from the MODIS thermal infrared (IR) and near-infrared (NIR) satellite products under clear-sky conditions for the period 2002-2008 at 18 sites in the Iberian Peninsula, with the aim to evaluate the capabilities of both algorithms. The article presents these results in relation to ground observations using different techniques (GPS, sunphotometer, radiosounding), with a special emphasis on GPS. At all sites the annual cycle presents the typical shape with low values in winter (minimum approximate to 1 cm) and high values in summer (maximum approximate to 3 cm), and a smaller cycle amplitude at continental sites than at coastal sites. The satellite results clearly depict the north-south gradient, as well as singular patterns such as the July minimum characterizing the most southern stations. The differences in the monthly means with respect to ground observations are mostly underestimations, ranging between a few percent to 40%, being generally larger in winter than in summer. Overall, NIR performs better than IR, especially in the wintertime. However, NIR presents overestimations in summer that can reach up to 30%. The comparison results of the annual cycle appear much more heterogeneous within coastal than continental areas, in particular for the Mediterranean region. It was found that the performance of IR algorithm is strongly influenced by the seasonal variations, a dependence which is much weaker in NIR retrievals. The time-coincident comparison shows that best MODIS/GPS agreement is found for continental regions (r.m.s.approximate to 0.3) for both methods. The largest regression biases and rms differences are found at the Mediterranean sites. The influence of sampling in the evaluation of the MODIS annual cycle was shown to affect mainly winter values. Errors induced by the retrieval accuracy and those induced by sampling deficiencies sometimes add up or compensate each other partially or totally.

Atmospheric water vapor validation needs simultaneous, well-defined, and independent information which are not easily available causing limitations in the development of remote sensing water vapor retrieval algorithms. This study is concerned with the retrieval of total atmospheric water vapor content and its validation. A band ratio method has been used to estimate the water vapor content based on Moderate Resolution Imaging Spectroradiometer (MODIS) Near InfraRed (NIR) data. The method uses MODIS bands 17, 18, and 19 as NIR bands and band 2 to remove the land cover reflectance. Furthermore, the Atmospheric Infrared Sounder (AIRS) has been used for both algorithm development and analysis of the results. The method has been modified to take into account the dry condition of the central parts of Iran. Using some various datasets, the method is implemented and evaluated quantitatively. The validation of the water vapor estimates has been undertaken by an analysis of AIRS data. The validation results shows error as low as 9 % for the estimated water vapor using the MODIS NIR band ratio method.

[1] In this paper, the atmospheric precipitable water (PW) was estimated by means of Advanced Very High Resolution Radiometer (AVHRR) thermal channels brightness temperature difference (0200T), over the broader area of Greece. The AVHRR derived 0200T was calculated in a grid of 5 0103 5 km cells; the corresponding PW value in each grid cell was extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 product (near infrared algorithm). MODIS derived PW values were adjusted to the AVHRR overpass time by using PW rates of change. These rates were estimated from time series of radiosonde measurements, provided by four synoptic meteorological stations located in Athens, Thessaloniki, Heraklion and Izmir. Next, to estimate the relationship between adjusted PW and 0200T, a robust linear regression algorithm was applied. Since regression coefficients corresponded to the broader area of Greece, the regression relationship was applied to AVHRR data for the period 20010900092005, to predict the annual and seasonal variability of PW over the study area. Radiosonde derived PW values at the above synoptic stations were used to validate the AVHRR derived PW spatiotemporal distribution. A very good agreement between radiosonde and AVHRR derived PW values was observed since a RMSE of 0.46 cm was calculated using a validation data set that covered a five years period.

城市化发展，特别是下垫面特征的改变，对大气环境的外强迫是当前大气环境领域研究的热点问题。下垫面特征变化导致不同尺度气象场发生变化，而气象条件又决定着大气污染物的迁移转化。为了深入探讨这个问题，文章首先从3个方面总结了相关研究：1）城市气候的基本特征及其形成的内在机制；2）不同尺度下的城市污染气象学特征；3）定量描述城市下垫面地-气作用模式的相关进展。之后进一步综述了利用数值模式方法模拟城市化过程中下垫面变迁对大气环境（包括气象条件及空气质量）影响方面的研究进展。最后利用中尺度大气模式WRF/Chem和过程分析方法研究了中国东部地区城市下垫面扩张对臭氧（O3）和一氧化碳（CO）空间分布的影响。模拟结果显示：在人为源排放不变的情况下，城市下垫面扩张使得近地面和1~3 km高处的O3，以及距地面1~2 km高处的CO体积分数增大；但近地CO体积分数下降。

利用2008年6-8月的MOD IS数据,通过两通道比值法和三通道比值法反演了东北地区的大气水汽含量,为了对比研究这两种方法,本文结合探空实测数据对反演结果进行了精度验证。结果表明,两通道比值法更适合东北地区的大气水汽含量反演,反演结果与探空实测数据线性方程的决定系数为0.81。进一步比较代表林地、农田、草地的探空站的反演值与实测值,发现两通道比值法均优于三通道比值法,其中林地的反演精度最高(方程的R2=0.92)。最后,利用两通道比值法的反演结果和土地利用分类数据对大气水汽含量的空间分布状况进行了分析,表明在其他条件相似时,大气水汽含量与土地利用类型之间有密切联系,各土地利用类型平均大气水汽含量的大小顺序在不同时间大致相同,除旱田外,均表现出水体>水田>湿地>林地>草地>未利用地的变化规律,这与下垫面蒸散情况一致。

Experience with the first 2 years of high quality data from the Moderate Resolution Imaging Spectroradiometer (MODIS) through quality control and validation has suggested several improvements to the original MODIS active fire detection algorithm described by Kaufman, Justice et al. [Journal of Geophysical Research 103 (1998) 32215]. In this paper, we present an improved replacement detection algorithm that offers increased sensitivity to smaller, cooler fires as well as a significantly lower false alarm rate. Performance of both the original and improved algorithm is established using a theoretical simulation and high-resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes. In general, the new algorithm can detect fires roughly half the minimum size that could be detected with the original algorithm while having an overall false alarm rate 10鈥100 times smaller.

<p>遥感反演大气水汽含量对进行天气预报、遥感大气校正、气候变化及水循环等研究具有重要意义。首先，通过对大气辐射传</p><p>输方程的推导，改进了三通道算法； 然后，模拟了在不同传感器视角条件下，大气水汽含量与MODIS 17、18、19通道大气透过率之</p><p>间的关系，解决了传感器视角问题，提出了针对MODIS数据的大气水汽含量计算方法； 最后，在IDL 6.0环境下，编程实现了该方法</p><p>，并对2003年6月14日的一景图像进行了反演，结果表明，本文提出的方法是可行的。</p>

High spatial resolution column atmospheric water vapor amounts were derived from spectral data collected by the airborne visible-infrared imaging spectrometer (AVIRIS), which covers the spectral region from 0.4 to 2.5 0204m in 10-nm bands and has a ground instantaneous field of view of 20010320 m from an altitude of 20 km. The quantitative derivation is made by curve fitting observed spectra with calculated spectra in the 1.14-0204m and 0.94-0204m water vapor band absorption regions using an atmospheric model, a narrowband spectral model, and a nonlinear least squares fitting technique. The derivation makes use of the facts that (1) the reflectances of many ground targets vary approximately linearly with wavelength in the 0.94- and 1.14-0204m water vapor band absorption regions, (2) the scattered radiation near 1 0204m is small compared with the directly reflected radiation when the atmospheric aerosol concentrations are low, and (3) the scattered radiation in the lower part of the atmosphere is subjected to the water vapor absorption. The technique is directly applicable for retrieving column water vapor amounts from AVIRIS spectra measured on clear days with visibilities 20 km or greater. The precision of the retrieved column water vapor amounts from several data sets is 5% or better. Based on the analyses of an AVIRIS data set that was acquired within an hour of radiosonde launch, it appears that the accuracy approaches the precision. The derived column water vapor amounts are independent of the absolute surface reflectances. It now appears feasible to derive high spatial resolution column water vapor amounts over land areas from satellite altitude with the proposed high resolution imaging spectrometer (HIRIS). Curve fitting of spectra near 1 0204m from areas covered with vegetation, using an atmospheric model and a simplified vegetation reflectance model, indicates that both the amount of atmospheric water vapor and the moisture content of vegetation can be retrieved simultaneously because the band centers of liquid water in vegetation and the atmospheric water vapor are offset by approximately 0.05 0204m.

利用两通道比值法、三通道比值法和姜立鹏等改进的三通道算法,应用MODIS影像资料进行黑龙江省大气水汽含量的反演,并结合探空实测数据进行反演精度验证。结果表明,两通道比值法的反演结果最好,计算结果与实测数据间相关系数为0.9664,三通道比值法的反演结果次之,相关系数为0.939,姜立鹏等改进的三通道算法的反演结果最差,相关系数仅为0.8385;用两通道算法反演的大气水汽含量的时间变化特征与黑龙江省季节性气候变化特征相符,空间变化特征与水体上空水汽总量大于陆地上空水汽总量的实际情况相一致。由此可见,两通道比值法是适合黑龙江省大气水汽含量遥感反演的方法。

本文以大气水汽反演为中心,将双通道和三通道反演算法应用于实际的黑龙江省MODIS影像中,通过对多个通道多组数据反演结果的分析和验证,证实利用该算法反演大气水汽是切实可行的,所获结果反映了实际水汽分布的大致规律。

2004年夏季,选择天气状况较好的时段在金塔县施放探空气球,采集高空温、压、湿等气象要素计算整层大气水汽含量。同时选取EOS-MODIS遥感资料近红外波段,反演整层大气水汽含量。反演结果与实测结果对比表明:最大相对误差为8.02%、最小相对误差为0.70%,平均相对误差为4.5%,反演结果可信。从绿洲上空水汽含量区域分布及沿着探空站南北向和东西向剖面看,水汽含量在空间分布上存在较大差异。戈壁沙漠上空水汽含量相对较少,绿洲上空水汽含量相对较大;绿洲边缘或通过沙漠的窄长护林带、河流以及水渠附近,存在着影响绿洲稳定和发展的“晒衣绳效应”。