利用全极化微波辐射计资料反演台风境内海面风场

作为一种新兴的被动遥感技术,全极化微波辐射计不仅可以提供海面风速产品,还可以提供海面风向产品.以往利用全极化微波辐射计观测亮温进行海面风场反演仅在晴空条件下进行,本文通过对观测亮温结合台风区域海面风场的分布特征进行分析,验证了全极化微波辐射计具有在台风等恶劣天气条件下进行海面风场观测的能力.基于敏感性分析实验,确定使用6.8 GHz和10.7 GHz等低频通道组合可进行台风区域内海面风场反演.其中,海面风速反演使用基于统计的多元线性回归算法,同时对海面温度、大气水汽含量、云中液态水含量及降水强度等物理量进行反演计算,为海面风向反演做准备.海面风向反演使用物理统计法进行,借鉴散射计风向反演使用的最大似然估计法.通过在全极化辐射传输前向模型中加入降水对大气透过率的影响、设计第三和第四Stokes通道亮温环境影响修正函数,在实现台风区域内海面风向反演的同时减小了反演误差.通过对“云娜”台风境内海面风场进行数值计算,验证了本文反演算法的可行性,并对反演误差的空间分布特征进行了分析.将2004年各台风过程的海面风场反演结果与散射计风场产品进行对比,海面风速和海面风向反演的均方根误差分别为1.64 m·s^-1和18.02°.     

Variability of GPS derived water vapor and comparison with MODIS data over the Indo-Gangetic plains

The water vapor is one of the important constituents of the atmosphere that affects the thermodynamics of the atmosphere and has direct impact on the weather conditions. The total column atmospheric water vapor, obtained from Global Positioning System (GPS) and Moderate Resolution Imaging Spectroradiometer (MODIS), is found to be very dynamic over the Indo-Gangetic (IG) plains. In this paper, we present an analysis of GPS data recently deployed (as of May 2007) on the campus of Banaras Hindu University, Varanasi (latitude 25°15′N, longitude 82°59′E). Further, we have compared the variability of water vapor from Kanpur GPS, AERONET and MODIS water vapor data for the year 2007. The monthly variability of water vapor shows characteristic features and dynamics of water vapor between two closely spaced GPS stations, found to be controlled by monsoon dynamics and wind pattern.     

利用ENVISAT/AATSR资料反演黄土高原陇东地区地表温度

由于ENVISAT/AATSR资料不同角度热辐射亮度值之间存在较高的相关性从而导致较大误差的产生,本文尝试避开这种误差源,只选取天底观测数据对黄土高原陇东地区整层大气水汽含量及地表温度进行反演.与MODIS整层大气水汽含量产品对比验证表明,本文结果与MODIS产品有一定差异,但是可以直接用于大气透过率的估算.结合野外观测数据对地表温度反演结果的检验表明,最大绝对误差为4.0 ℃,平均相对误差为5.0％,因此,该算法在黄土高原陇东地区应用比较成功.     

MODIS影像的大气校正及在太湖蓝藻监测中的应用

MODIS 数据有免费、波段丰富、时间分辨率高等优点,是进行太湖蓝藻监测的重要数据源,由于MODIS传感器接收的是地物反射太阳辐射的信号,太阳辐射与地球大气的相互作用会引起传感器接收到的信号失真,为了提高利用MODIS数据监测太湖蓝藻的精度,必须对其进行大气校正.本文介绍了FIAASH大气校正模型的基本原理,并对2007年4月25日MODIS数据的前七个波段进行试验,对比分析了影像大气校正前后的NDVI值以检测大气校正的效果;分析表明,大气校正前后NDVI的变化趋势基本上相同,但大气校正后的NDVI动态范围更大,校正后NDVI的平均值和标准差增大,大气校正在一定程度上有效地降低了大气对遥感影像的影响,达到了增强信息的目的;最后,利用大气校正获取的地表真实反射率数据的第二波段与第一波段的比值,运用阈值法提取蓝藻信息,经试验当阈值为1.9时提取出来的蓝藻分布图基本上与实际相符.利用MODIS影像可以快速、及时地监测蓝藻爆发的位置及爆发程度.     

利用独立分量分析进行火山灰云遥感检测

火山灰云不但引起全球气候和环境系统的重大变化,而且还会威胁航空安全。热红外遥感技术为检测火山灰云提供了新手段,但是遥感数据自身的冗余和波段相关性大大降低了火山灰云的检测精度。独立分量分析(Independent Component Analysis,ICA)能够实现遥感数据的去相关和消除冗余,在火山灰云检测中具有一定的潜力。通过探索火山灰云的物理、化学性质,文中以2010年4月19日冰岛艾雅法拉(Eyjafjallajokull)火山灰云MODIS图像为数据源,在对MODIS数据进行主成分分析处理的基础上,利用ICA进行火山灰云检测。结果表明:ICA能够较好地从MODIS图像中获取火山灰云信息,所得结果与美国地质调查局标准光谱数据库和火山灰云SO2浓度分布具有较好的一致性,取得了较好的检测效果。     

基于GPS和MODIS的ENVISAT ASAR数据干涉测量中大气改正方法研究

GPS数据用于改正InSAR中大气延迟误差的方法受GPS站点密度的限制,只利用有限的几个站点所观测到的大气数据来生成干涉图的大气改正图,往往达不到很好的效果.本文研究利用GPS与MODIS数据的联合使用来生成大气改正图,首先用GPS数据对MODIS水汽产品进行分块校准,并且对MODIS水汽数据进行了空间结构函数分析,得到研究区域内水汽场的空间分布规律.然后把这种区域水汽场的空间分布信息结合到Kriging内插法中生成更为合理的水汽图.通过上海地区ENVISAT ASAR数据的实验发现,这种加以改正的GPS和MODIS数据联合改正法不仅可以对长波大气信号有明显的消弱,还能消弱一些短波的大气信号,特别是一些幅度较强的短波信号;经过GPS+MODIS算法改正后,短波信号占优和长波信号占优的两幅差分大气延迟图的整体RMS分别降低了32.74%和38.82%,去除幅度较大.与GPS+ATM(大气传输模型)算法比较,我们发现,在上海地区有限的数据条件下（即研究区域内只有6个GPS点）,GPS+MODIS法在大气去除效果或者说大气信号重现能力方面优于GPS+ATM算法.GPS+MODIS算法在捕获短波大气信号方面要比GPS+ATM更有优势,因此也可以改正短波大气误差.     

Meteorological fields from remote infrared sensing

Modern numerical weather prediction techniques require global observations of the atmospheric state and structure parameters. The current meteorological observing system, which is based on radiosonde balloon observations, has extensive gaps. Remote sensing of the Earth atmosphere emission spectrum from satellites can fill these gaps. The physical basis for extracting information on meteorological fields from such remote observations is explained. The problem reduces to that of solving a linear Fredholm equation of the first kind in the presence of noisy data. There is no unique solution to such a problem. The mathematical techniques-inversion techniques-that are currently used to solve the problem are reviewed. Examples are given of meteorological fields obtained from remote infrared sensing from satellites. Results indicate that meteorological parameters such as temperature and geopotential height of constant pressure surfaces can be measured-in conditions of clear skies-to accuracies approaching that of the radiosonde system. Other meterological variables, e.g., water vapor and ozone, can be determined to a lesser degree of accuracy. Applications of the remotely sensed fields are described. Problem areas and suggested solutions are discussed.     

Removing sun glint from optical remote sensing images of shallow rivers

Sun glint is the specular reflection of light from the water surface, which often causes unusually bright pixel values that can dominate fluvial remote sensing imagery and obscure the water‐leaving radiance signal of interest for mapping bathymetry, bottom type, or water column optical characteristics. Although sun glint is ubiquitous in fluvial remote sensing imagery, river‐specific methods for removing sun glint are not yet available. We show that existing sun glint‐removal methods developed for multispectral images of marine shallow water environments over‐correct shallow portions of fluvial remote sensing imagery resulting in regions of unreliable data along channel margins. We build on existing marine glint‐removal methods to develop a river‐specific technique that removes sun glint from shallow areas of the channel without over‐correction by accounting for non‐negligible water‐leaving near‐infrared radiance. This new sun glint‐removal method can improve the accuracy of spectrally‐based depth retrieval in cases where sun glint dominates the at‐sensor radiance. For an example image of the gravel‐bed Snake River, Wyoming, USA, observed‐versus‐predicted R² values for depth retrieval improved from 0.66 to 0.76 following sun glint removal. The methodology presented here is straightforward to implement and could be incorporated into image processing workflows for multispectral images that include a near‐infrared band. Copyright © 2016 John Wiley & Sons, Ltd.     

基于MODTRAN模型对高分五号卫星断层逸出气体探测能力的辐射模拟

地下流体监测数据和地表断层调查都显示构造活动强烈期和大地震前后活动断裂带会伴有大量气体逸出。 中国即将发射的高分五号(GF-5)卫星搭载的大气环境红外甚高光谱分辨率探测仪及全谱段光谱成像仪两个传感器, 主要以大气气体的探测为应用目标。 本文基于两个传感器的参数设置, 使用大气辐射传输模型, 对断层逸出气体中的水汽、 CH₄和CO₂三种气体在大气中的含量变化对卫星传感器的辐射影响进行了仿真模拟, 分析了两个传感器对水汽、 CH₄和CO₂气体异常的探测能力。 结果表明, GF-5卫星两个红外传感器特定的光谱通道对大气水汽、 CH₄和CO₂气体异常变化均有不同程度的敏感性, 可以期待发展具有较高精度的相关气体遥感反演模型, 用于地震的监测及预测。     

Genetic inverse algorithm for retrieval of component temperature of mixed pixel by multi-angle thermal infrared remote sensing data

After carefully studying the results of retrieval of land surface temperature(LST) by multi-channel thermal infrared remote sensing data, the authors of this paper point out that its accuracy and significance for applications are seriously damaged by the high correlation coefficient among multi-channel information and its disablement of direct retrieval of component temperature. Based on the model of directional radiation of non-isothermal mixed pixel, the authors point out that multi-angle thermal infrared remote sensing can offer the possibility to directly retrieve component temperature, but it is also a multi-parameter synchronous inverse problem. The results of digital simulation and field experiments show that the genetic inverse algorithm (GIA) is an effective method to fulfill multi-parameter synchronous retrieval. So it is possible to realize retrieval of component temperature with error less than 1K by multi-angle thermal infrared remote sensing data and GIA.     

analysis on modis satellite thermal infrared information before and after the jinggu ms6.6 earthquake

Continuous MODIS/Terra satellite thermal infrared remote sensing data of the Jinggu M_S6.6 earthquake area from July 2014 to January 2015 is collected, and after cloud-removing, the thermal infrared data between 5:00a.m.-7:00a.m. Beijing Time, which is the best period for observation, is selected to perform land surface temperature data retrieval and analyze the temporal evolution of land surface temperature anomalies before and after the earthquake, as well as the relationship between abnormal spatial distribution and active fault. The impacts of non-structural factors such as topography, landform and seasonal weather of the earthquake zone on land surface temperature anomalies are discussed. The result shows that: a)there was thermal infrared anomalous temperature increase appearing near the epicenter two months before the M_S6.6 Jinggu earthquake and there was a certain correspondence between the anomalous temperature increase and earthquake occurrence time. The significant temperature increase happened in the first half of the month, reached its peak 7 days before the earthquake, and dropped rapidly after the earthquake. At the same time, there was also anomalous temperature increase to a certain extent appearing about half month before the strong aftershocks of magnitude 5.8 and 5.9; b)Through the correlation analysis of non-structural factors such as topography, landform and seasonal weather of the earthquake zone, it is found that the structural "temperature increase" before the Jinggu M_S6.6 earthquake was the information indicating the anti-season change of temperature increase in the earthquake zone; c)The anomalous temperature increase was cross-developed from the epicenter along the NS-NE trending conjugate faults, which is consistent roughly with the NNE-SSW predominant direction of the maximum principal stress of the regional tectonic stress field. After full consideration of the influence of non-structural factors such as topography, landform and seasonal weather on the abnormal temperature increase, it is inferred that this thermal infrared temperature increase is possibly a short-imminent anomaly before the earthquake.     

应用地基GPS遥感倾斜路径方向大气水汽总量

应用地基GPS沿倾斜路径方向遥测大气水汽总量,是获得测站周围水汽三维空间分布信息(水汽层析)的基础.本文介绍了地基GPS沿倾斜路径方向遥感大气水汽总量的原理和方法;首先用湿梯度、后处理残差联合计算接收机上空不同方位上大气水汽各向异性成分,在此基础上重构倾斜路径水汽总量.为验证GPS观测结果精度,用微波辐射计（WVR）与GPS一起进行了联合观测,不同观测地点和时间的对比结果表明,二者root mean square (RMS)误差小于4mm,证明应用此种方法地基GPS可较精确地反演出倾斜路径方向大气水汽总量,而且这种反演方法适合于近实时大气遥感探测.地基GPS测量具有全天候可连续观测等优点,可以弥补常规观测的不足,为气候研究提供高精度且连续的水汽数据资料;组网观测可以为数值天气预报提供好的初始场,提高模式预报精度.     

A case study of relationship between GPS PWV and solar variability during the declining phase of solar cycle 23

Water vapor plays an important role in the global climate system. A clear relationship between water vapor and solar activity can explain some physical mechanisms of how solar activity influences terrestrial weather/climate changes. To gain insight of this possible relationship, the atmospheric precipitable water vapor (PWV) as the terrestrial climate response was observed by ground-based GPS receivers over the Antarctic stations. The PWV changes analyzed for the period from 2003 to 2008 coincided with the declining phase of solar cycle 23 exhibited following the solar variability trend. Their relationship showed moderate to strong correlation with 0.45 < R ² < 0.93 (p < 0.01), on a monthly basis. This possible relationship suggests that when the solar-coupled geomagnetic activity is stronger, the Earth’s surface will be warmer, as indicated by electrical connection between ionosphere and troposphere.     

Combining MODIS and AMSR‐E observations to improve MCD43A3 short‐time snow‐covered Albedo estimation

Land surface albedo plays an important role in the radiation budget and global climate models. NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) provide 16‐day albedo product with 500‐m resolution every 8 days (MCD43A3). Some in‐situ albedo measurements were used as the true surface albedo values to validate the MCD43A3 product. As the 16‐day MODIS albedo retrievals do not include snow observations when there is ephemeral snow on the ground surface in a 16‐day period, comparisons between MCD43A3 and 16 day averages of field data do not agree well. Another reason is that the MODIS cannot detect the snow when the area is covered by clouds. The Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) data are not affected by weather conditions and are a good supplement for optical remote sensing in cloudy weather. When the surface is covered by ephemeral snow, the AMSR‐E data can be used as the additional information to retrieve the snow albedo. In this study, we developed an improved method by using the MODIS products and the AMSR‐E snow water equivalent (SWE) product to improve the MCD43A3 short‐time snow‐covered albedo estimation. The MODIS daily snow products MOD10A1 and MYD10A1 both provide snow and cloud information from observations. In our study region, we updated the MODIS daily snow product by combining MOD10A1 and MYD10A1. Then, the product was combined with the AMSR‐E SWE product to generate new daily snow‐cover and SWE products at a spatial resolution of 500 m. New SWE datasets were integrated into the Noah Land Surface Model snow model to calculate the albedo above a snow surface, and these values were then utilized to improve the MODIS 16‐day albedo product. After comparison of the results with in‐situ albedo measurements, we found that the new corrected 16‐day albedo can show the albedo changes during the short snowfall season. For example, from January 25 to March 14, 2007 at the BJ site, the albedo retrieved from snow‐free observations does not indicate the albedo changes affected by snow; the improved albedo conforms well to the in‐situ measurements. The correlation coefficient of the original MODIS albedo and the in‐situ albedo is 0.42 during the ephemeral snow season, but the correlation coefficient of the improved MODIS albedo and the in‐situ albedo is 0.64. It is concluded that the new method is capable of capturing the snow information from AMSR‐E SWE to improve the short‐time snow‐covered albedo estimation. Copyright © 2012 John Wiley & Sons, Ltd.     

Review of snow water equivalent microwave remote sensing

Accurate quantitative global scale snow water equivalent information is crucial for meteorology, hydrology, water cycle and global change studies, and is of great importance for snow melt-runoff forecast, water resources management and flood control. With land surface process model and snow process model, the snow water equivalent can be simulated with certain accuracy, with the forcing data as input. However, the snow water equivalent simulated using the snow process models has large uncertainties spatially and temporally, and it may be far from the needs of practical applications. Thus, the large scale snow water equivalent information is mainly from remote sensing. Beginning with the launch of Nimbus-7 satellite, the research on microwave snow water equivalent remote sensing has developed for more than 30 years, researchers have made progress in many aspects, including the electromagnetic scattering and emission modeling, ground and airborne experiments, and inversion algorithms for future global high resolution snow water equivalent remote sensing program. In this paper, the research and progress in the aspects of electromagnetic scattering/emission modeling over snow covered terrain and snow water equivalent inversion algorithm will be summarized.     

A review of the estimation of downward surface shortwave radiation based on satellite data: Methods,progress and problems

The estimation of downward surface shortwave radiation(DSSR) is important for the Earth's energy budget and climate change studies. This review was organised from the perspectives of satellite sensors, algorithms and future trends,retrospects and summaries of the satellite-based retrieval methods of DSSR that have been developed over the past 10 years. The shortwave radiation reaching the Earth's surface is affected by both atmospheric and land surface parameters. In recent years,studies have given detailed considerations to the factors which affect DSSR. It is important to improve the retrieval accuracy of cloud microphysical parameters and aerosols and to reduce the uncertainties caused by complex topographies and high-albedo surfaces(such as snow-covered areas) on DSSR estimation. This review classified DSSR retrieval methods into four categories:empirical, parameterisation, look-up table and machine-learning methods, and evaluated their advantages, disadvantages and accuracy. Further efforts are needed to improve the calculation accuracy of atmospheric parameters such as cloud, haze, water vapor and other land surface parameters such as albedo of complex terrain and bright surface, organically combine machine learning and other methods, use the new-generation geostationary satellite and polar orbit satellite data to produce highresolution DSSR products, and promote the application of radiation products in hydrological and climate models.     

基于太湖气溶胶类型分区的环境一号卫星CCD大气校正

由两颗卫星组成的环境卫星星座系统所提供的CCD数据具有较高的时间分辨率,使其在内陆湖泊水环境遥感监测中具有较大的应用潜力,对其有效的大气校正方法的研究则是其定量化参数反演的前提.基于准同步的MODIS数据辅助,根据气溶胶的差异性,将太湖划分为北部湖区、其他湖区两块区域,利用辐射传输模型,研究太湖环境一号CCD数据大气校正的方法,并对2009年4月17、21、25日数据进行大气校正.研究结果表明,该大气校正方法直接使用较为成熟的MODIS各类产品,克服了传统大气校正中依赖于现场同步测量大气参数的缺陷,能够快速、有效地完成环境一号CCD数据的大气校正.基于气溶胶类型对太湖进行分区后,所求算的遥感反射率精度高于6S模型和暗像元等大气校正方法得到的结果.     

MODIS亮温增温异常点比值的时序分析方法及其在台湾一些5级以上地震前的异常变化

首次提出了MODIS卫星遥感数据用于地震预测研究的MODIS亮温增温异常点比值定量化方法以及尽量减少云层干扰的初步方案。结合近期台湾地区一系列中强地震的震例研究,归纳了分析区域内中强地震前的MODIS亮温增温异常的量化指标。研究表明,大部分研究震例在地震发生前1~20天都出现了突跳性质的增温异常比值(活跃度)增强的情况,而正常情况下增温异常比值都在零值附近波动。利用在一定程度上排除了云层影响的MODIS卫星遥感热红外信息得到的亮温增温异常点比值的变化,在一些多震地区有针对性地系统开展研究,有望找到识别地震短临前兆的一种新方法     

Aerosol retrieval over land by exploiting the synergy of TERRA and AQUA MODIS DATA

Aerosol particles over land mainly come from man- made source such as biomass burning, industrial de-bris and natural source such as soil dust, sea salt parti-cles, etc. More and more research results show that, aerosols impact global and regional energy radiative budget; aerosol particles also modify the cloud mi-crophysics, as a result, aerosol particles may change the cloud radiative properties. Aerosol particles also play an important role in many biogeochemical cycles. All the above-menti…     

The Representation of Tropospheric Water Vapor Over Low-Latitude Oceans in (Re-)analysis: Errors,Impacts, and the Ability to Exploit Current and Prospective Observations

This paper addresses the representation of lower tropospheric water vapor in the meteorological analyses—fully detailed estimates of atmospheric state—providing the wide temporal and spatial coverage used in many process studies. Analyses are produced in a cycle combining short forecasts from initial conditions with data assimilation that optimally estimates the state of the atmosphere from the previous forecasts and new observations, providing initial conditions for the next set of forecasts. Estimates of water vapor are among the less certain aspects of the state because the quantity poses special challenges for data assimilation while being particularly sensitive to the details of model parameterizations. Over remote tropical oceans observations of water vapor come from two sources: passive observations at microwave or infrared wavelengths that provide relatively strong constraints over large areas on column-integrated moisture but relatively coarse vertical resolution, and occultations of Global Positioning System provide much higher accuracy and vertical resolution but are relatively spatially coarse. Over low-latitude oceans, experiences with two systems suggest that current analyses reproduce much of the large-scale variability in integrated water vapor but have systematic errors in the representation of the boundary layer with compensating errors in the free troposphere; these errors introduce errors of order 10% in radiative heating rates through the free troposphere. New observations, such as might be obtained by future observing systems, improve the estimates of water vapor but this improvement is lost relatively quickly, suggesting that exploiting better observations will require targeted improvements to global forecast models.