印度洋及太平洋海表盐度时空特征分析

目前对印度洋和太平洋海表盐度变化的大尺度分析相对较少，Aquarius作为海表盐度的观测卫星，其观测数据在分析海表盐度时空特征时有着不可替代的优势。为了降低观测资料本身的误差对分析结果的影响，文本首先利用质量—距离双重加权方法生成新的高精度Aquarius网格化月均海表盐度场，并基于此盐度场和Argo资料对2011-09至2015-05印度洋及太平洋海表盐度的时空特征进行了分析。结果显示，盐度分布和纬度有明显的相关性，整体呈现低、高纬偏低，中纬偏高的态势，纬度极值随时间并没有很明显的变化，然而时间最大值随纬度的变化曲线呈现明显的以赤道为中心的近似中心对称分布特征。分析显示印度洋和太平洋盐度分布主要包括4个高盐区和4个低盐区，但每个盐度区的变化趋势与幅度不尽相同。     

海表面温度时空变异特征及对验证误差影响

海洋要素的变化存在明显的区域性和季节性的变化特性,本文选择海洋要素中最为突出的海表面温度(SST)要素作为主要分析参数,设计时空变异参数的计算指标,分析时空变异对验证误差影响的关系,通过研究及试验的数据精度验证,证明了时空变异是造成误差的直接原因之一。强烈的时空属性变异,在验证过程中会引入很大的验证误差,处于不同变异等级区划的数据,其验证结果相对误差可达13.08%,变异越剧烈的区域,精度验证效果越差,验证误差就越大,这些误差并非完全是遥感产品的误差,验证结果不具有代表性,不能真实的反映遥感产品的误差特征。对于SST等海洋遥感产品验证时,需要考虑时空变异对验证误差的影响和贡献,合理选择验证试验区域、代表性的评价数据集和科学的评价方法。     

FY-3C微波成像仪海面温度产品算法及精度检验

海洋表面温度(SST)是海洋学和气候学一个十分重要的物理因子,而卫星被动微波遥感能够穿透云层,实现全天候、大范围观测,因此利用中国FY-3C微波成像仪(MWRI)反演SST具有重要意义。FY-3C MWRI SST产品采用统计算法,首先利用MWRI降水和海冰产品剔除含降水和海冰的像元,之后选择时空间隔0.2 h和0.2°离海岸100 km以外的FY-3C MWRI观测亮温与浮标观测值进行匹配,再将全球在空间上分为4个纬度带,时间上分为12个月,并分升轨和降轨,分别建立浮标海温观测结果和MWRI亮温之间的统计关系,实现对SST的估算。将|估算海温-30年月平均海温|≥2.5 K的像元标识为51,发现这些像元基本分布在陆地边缘地区及大风速地区,剔除标识为51的像元后的精度验证结果表明:与全球浮标资料相比,FY-3C MWRI SST轨道产品升轨精度为–0.02±1.22 K,降轨精度为–0.15±1.28 K;与全球分析场日平均海温OISST相比,FY-3C MWRI SST日产品升轨精度为0.00±1.03 K,降轨精度为–0.09±1.08 K。微波辐射计的性能及其定位定标精度、上游卫星产品(降水检测和海冰检测)的精度、陆地的干扰及高风速对微波信号的影响均会造成SST估算误差,如何改进算法中风速大于12 m/s时的估算精度是下一步的工作重点。     

光源发散角对DPC偏振定标的影响分析及验证

多角度偏振成像仪(DPC)是一种多角度、多光谱具备偏振测量功能的大视场偏振遥感器。偏振定标光源的发散角与DPC像元对应的视场角匹配一致,是提升DPC实验室偏振定标精度的关键因素之一。通过比较实验室偏振定标与在轨定标的状态差异,参考DPC在轨运行光学系统的成像原理,通过微分运算方式,建立一种偏振定标光源的发散角与单像元视场角匹配的模型,分析结果给出了光源的发散角应大于0.14°才能满足DPC全视场的偏振定标要求。以490 nm偏振通道为例,设计了采用可调光谱积分球替代0.125°发散角扩束镜平行光源方案,验证所建立模型和分析结果的合理性。结果表明,DPC的线偏振度测量值和理论预测值间的平均差异由1.26×10–2减小至4.4×10–3,说明所建立模型和采用可调光谱积分球作为偏振定标光源方案可用于DPC的实验室偏振定标。     

Simultaneous measurements of ku- and ka-band sea surface cross sections by an airborne Radar

The dual-frequency Airborne Precipitation Radar-2 (APR-2) was deployed during the Wakasa Bay Experiment in 2003, for validation of the Advanced Microwave Scanning Radiometer-EOS. Besides providing extensive observations of diverse precipitating systems, this Ku-(13.4 GHz) and Ka-band (35.6 GHz) cross-track scanning radar measured sea surface backscatter simultaneously. While the characteristics of the normalized sea surface cross section /spl sigma//sup 0/ at Ku-band are well understood and widely published, the existing experimental data concerning /spl sigma//sup 0/ at Ka-band are scarce and results are inconsistent. In this letter, the Ku/Ka-band /spl sigma//sup 0/ measurements collected by APR-2, together with the estimated uncertainties, are discussed. In general, the measured /spl sigma//sup 0/ at Ka-band at around 10/spl deg/ incidence angle appears to be close to that at Ku-band /spl sigma//sup 0/, and Ka-band exhibits a nonnegligible difference in wind dependence with respect to Ku-band for moderate to high winds.     

Potential fish habitat mapping using MODIS-derived sea surface salinity,temperature and chlorophyll-a data: South China Sea Coastal areas,Malaysia

This paper demonstrates the use of moderate resolution imaging spectro-radiometer (MODIS) data for fish forecasting mapping of seasonal spatial distribution of sea surface salinity (SSS), temperature (SST) and chlorophyll-a in the ocean waters off the coast of Semporna, Malaysia. Multi-linear regression analysis was performed to estimate SSS and the Brown and Minnet algorithm was used for the SST. The extracted parameters were validated using in situ measurement taken with Hydro-Lab equipment. The extracted parameters from MODIS images reveal the signature values which establish the relationships between these parameters, and thus delineating the potential fish zonation (PFZ) map. These developed models will help for accurate monitoring of large coverage areas at low cost and within short period of time. Furthermore, such models will allow the prediction of the total fish catch in different seasons, thus contributing to fish industry management and marketing. This research recommends the use of PFZ map for mass scale fish harvesting in short time for larger areas. Finally, the research has developed a potential fish zone model amalgamating all the above parameters. The PFZ mapping was carried out off the coast of Semporna, Sabah as there were sufficient fish catch data for accuracy assessment. The R was computed as 0.93 and the higher fish catch areas have coincided very well with the higher PFZ values, meaning the tool is ready for use for operational near real-time fish forecasting.     

A case study for intercomparison of land surface temperature retrieved from GOES and MODIS

In recent years, algorithms have been developed to derive land surface temperature (LST) from geostationary and polar satellite systems. However, few works have addressed the intercomparison between Geostationary Operational Environmental Satellites (GOES) and the available suite of polar sensors. In this study, differences in LSTs between GOES and MODerate resolution Imaging Spectroradiometer (MODIS) have been compared and also evaluated against ground observations. Due to the lack of split-window (SW) channels in the GOES M (12)-Q era, a dual-window algorithm using a mid-infrared 3.9 µm channel is compared with traditional SW algorithm. It is found that the differences in LST between different platforms are bigger during daytime than those during nighttime. During daytime, LSTs from GOES with the dual-window algorithm are warmer than MODIS LSTs, while LSTs from the SW algorithm are close to MODIS LSTs. The difference during daytime is found to be related to anisotropy in satellite viewing geometry, and land surface properties, such as vegetation cover and especially surface emissivity at middle infrared (MIR) channel. When evaluated against ground observations, the standard deviation (precision) error (2.35 K) from the dual window algorithm is worse than that (1.83 K) from the SW algorithm, indicating the lack of split-window channel in the GOES M(12)-Q era may degrade the performance of LST retrievals.     

Preliminary validation of GLASS-DSSR products using surface measurements collected in arid and semi-arid regions of China

Global Land Surface Satellite-downward surface shortwave radiation (GLASS-DSSR) products have been routinely produced from 2008–2010 based on an improved look-up table algorithm, which explicitly accounts for the variations of cloud optical depth, water vapor content, and elevation. In this study, we validated and assessed the accuracy of these products in arid and semiarid regions of China. Toward this goal, observation data-sets provided by the Arid and Semiarid Region Collaborative Observation Project as well as four other metrological sites were collected, chosen, and preprocessed for the final validation. Due to the possible effect of spatial collocation and the strong adjacency pixel effect in instantaneous products, we used a more sophisticated validating scheme in order to reduce the impacts from these effects as much as possible. Evidences indicate that the GLASS-DSSR products are considerably accurate over most parts of arid and semiarid regions in China, but in complex terrain areas the products might need further refinements. The R² at all sites (except Naqu) was larger than 0.8 with a root mean square error (RMSE) range of about in 90–130 W/m². Linear regression analyses suggest that GLASS-DSSR products tend to overestimate DSSR in the interval of low surface-measured values and symmetrically underestimate DSSR in the interval of high values. This systematic error may result from inappropriate assumptions about clouds and aerosol loadings over the regions in the operational algorithm.     

近地表大气逆温条件下的地表温度遥感反演与验证

为了减少近地表大气逆温对地表温度遥感反演精度的影响,提出在晴空的地表温度"通用劈窗算法"模型中增加一个温度改正项来实现。在建立该误差改正项时,利用正常条件下的通用劈窗算法系数和具有不同逆温强度的逆温廓线,并结合大气辐射传输模型MODTRAN计算,得到近地表大气逆温条件下的地表温度反演误差,并在分析了该误差值与相应的逆温强度的关系后,发现该温度改正项可以表示为近地表大气逆温强度的二次项函数。为了进一步提高地表温度的反演精度,将地表温度和大气水汽含量进行分组,分别针对每个分组来确定温度改正项方程的系数。模拟结果表明,在逆温强度为1.7 K/100m时,该温度改正项可以使地表温度的反演精度提高0.44 K。利用内蒙古海拉尔试验站的实测数据对地表温度反演结果进行了验证,在近地表大气存在逆温的条件下,该方法能提高地表温度的遥感反演精度0.47K。但是,由于本文提出的方法需要已知大气温度廓线来计算大气逆温强度,因此在实际应用中该方法受到了一定的限制。     

Estimation and validation of snow surface temperature using modis data for snow-avalanche studies in NW-Himalaya

Snow avalanche studies require different snow-meteorological parameters for avalanche forecasting. Snow surface temperature is one of the major parameters, which is responsible for the evolution of snow pack characteristics. In the present paper, the snow surface temperature was estimated using TERRA satellite based — Moderate resolution imaging spectroradiometer (MODIS) sensor for NW-Himalayas. Ground data observed by automatic weather stations (AWS) was used to calibrate the brightness temperature obtained by MODIS thermal bands data into the actual snow surface temperature data through regression analysis. A split window technique has been implemented for the estimation of snow surface temperature. The multi-date satellite derived snow surface temperature was validated with ground data of winter 2004–05 and 2005–06 collected at various observation stations located in different ranges of NW-Himalaya. Good correlations were observed for Upper Himalaya (0.98, 0.98), Middle Himalaya (0.92, 0.96) and Lower Himalaya (0.88, 0.82) for 2004–05 and 2005–06 winter respectively. Further, estimated snow surface temperature was also verified with snow-cover information collected by manned observatories and area delineated by thematic maps of snow surface temperature was validated with the different snow climatic zones of NW-Himalaya.     

Investigation and validation of algorithms for estimating land surface temperature from Sentinel-3 SLSTR data

Land surface temperature (LST) is an important indicator of global ecological environment and climate change. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the recently launched Sentinel-3 satellites provides high-quality observations for estimating global LST. The algorithm of the official SLSTR LST product is a split-window algorithm (SWA) that implicitly assumes and utilizes knowledge of land surface emissivity (LSE). The main objective of this study is to investigate alternative SLSTR LST retrieval algorithms with an explicit use of LSE. Seventeen widely accepted SWAs, which explicitly utilize LSE, were selected as candidate algorithms. First, the SWAs were trained using a comprehensive global simulation dataset. Then, using simulation data as well as in-situ LST, the SWAs were evaluated according to their sensitivity and accuracy: eleven algorithms showed good training accuracy and nine of them exhibited low sensitivity to uncertainties in LSE and column water vapor content. Evaluation based on two global simulation datasets and a regional simulation dataset showed that these nine SWAs had similar accuracy with negligible systematic errors and RMSEs lower than 1.0 K. Validation based on in-situ LST obtained for six sites further confirmed the similar accuracies of the SWAs, with the lowest RMSE ranges of 1.57–1.62 K and 0.49−0.61 K for Gobabeb and Lake Constance, respectively. While the best two SWAs usually yielded good accuracy, the official SLSTR LST generally had lower accuracy. The SWAs identified and described in this study may serve as alternative algorithms for retrieving LST products from SLSTR data.     

Influence of surface and vegetation characteristics on C-band radar measurements for soil moisture content

Soil moisture estimation using microwave remote sensing faces challenges of the segregation of influences mainly from roughness and vegetation. Under static surface conditions, it was found that Radarsat C-band SAR shows reasonably good correlation and sensitivity with changing soil moisture. Dynamic surface and vegetation conditions are supposed to result in a substantial reduction in radar sensitivity to soil moisture. A C-band scatterometer system (5.2 GHz) with a multi-polarization and multi-angular configuration was used 12 times to sense the soil moisture over a tall vegetated grass field. A score of vegetation and soil parameters were recorded on every occasion of the experiment. Three radar backscattering models Viz., Integral Equation Model (IEM), an empirical model and a volume scattering model, have been used to predict the backscattering phenomena. The volume scattering model, using the Distorted Born Approximation, is found to predict the backscattering phenomena reasonably well. But the surface scattering models are expectedly found to be inadequate for the purpose. The temporal variation of soil moisture does show good empirical relationship with the observed radar backscattering. But as the vegetation biomass increases, the radar shows higher sensitivity to the vegetation parameters compared to surface characteristics. A sensitivity analysis of the volume scattering model for all the parameters also reveals that the radar is more sensitive to plant parameters under high biomass conditions, particularly vegetation water content, but the sensitivity to surface characteristics, particularly to soil moisture, is also appreciable.     

Atmospheric correction to IRS-P6 AWiFS data and its validation with ground measurements: A study over the semi-arid region

In this study, we have implemented a fast atmospheric correction algorithm to IRS-P6 advanced wide field sensor (AWiFS) satellite data for retrieving surface reflectance under different atmospheric and surface conditions. The algorithm is based on MODIS climatology products and simplified use of Second Simulation of Satellite Signal in Solar Spectrum (6S) radiative transfer code. The algorithm requires information on aerosol optical depth (AOD) for correcting the satellite dataset. The atmospheric correction algorithm has been tested for IRS-P6 AWiFS False colour composites covering the International Crops Research Institute for the Semi-Arid Tropics Farm, Patancheru, Hyderabad, India, under varying atmospheric conditions. Ground measurements of surface reflectance representing different land use/land cover, i.e. red soil, chick pea, groundnut and pigeon pea crops were conducted to validate the algorithm. Terra MODIS AOD₅₅₀ validated with Microtops-II sun photometer–derived AOD₅₀₀ over the urban region of Hyderabad exhibited very good correlation of ～0.92, suggesting possible use of satellite-derived AOD for atmospheric correction.     

A Ka-band backscatter model function and an algorithm for measurement of the wind vector over the sea surface

A Ka-band backscatter model and an algorithm for measurement of the wind speed and direction over the sea surface by a frequency-modulated continous-wave radar demonstrator system operated in scatterometer mode have been developed. To evaluate the proposed algorithm, a simulation of the wind vector retrieval has been performed.     

Global mean sea surface and marine gravity anomaly from multi-satellite altimetry: applications of deflection-geoid and inverse Vening Meinesz formulae

 Global mean sea surface heights (SSHs) and gravity anomalies on a 2^′×2^′ grid were determined from Seasat, Geosat (Exact Repeat Mission and Geodetic Mission), ERS-1 (1.5-year mean of 35-day, and GM), TOPEX/POSEIDON (T/P) (5.6-year mean) and ERS-2 (2-year mean) altimeter data over the region 0^∘–360^∘ longitude and –80^∘–80^∘ latitude. To reduce ocean variabilities and data noises, SSHs from non-repeat missions were filtered by Gaussian filters of various wavelengths. A Levitus oceanic dynamic topography was subtracted from the altimeter-derived SSHs, and the resulting heights were used to compute along-track deflection of the vertical (DOV). Geoidal heights and gravity anomalies were then computed from DOV using the deflection-geoid and inverse Vening Meinesz formulae. The Levitus oceanic dynamic topography was added back to the geoidal heights to obtain a preliminary sea surface grid. The difference between the T/P mean sea surface and the preliminary sea surface was computed on a grid by a minimum curvature method and then was added to the preliminary grid. The comparison of the NCTU01 mean sea surface height (MSSH) with the T/P and the ERS-1 MSSH result in overall root-mean-square (RMS) differences of 5.0 and 3.1 cm in SSH, respectively, and 7.1 and 3.2 μrad in SSH gradient, respectively. The RMS differences between the predicted and shipborne gravity anomalies range from 3.0 to 13.4 mGal in 12 areas of the world's oceans. Received: 26 September 2001 / Accepted: 3 April 2002 Correspondence to: C. Hwang Acknowledgements. This research is partly supported by the National Science Council of ROC, under grants NSC89-2611-M-009-003-OP2 and NSC89-2211-E-009-095. This is a contribution to the IAG Special Study Group 3.186. The Geosat and ERS1/2 data are from NOAA and CERSAT/France, respectively. The T/P data were provided by AVISO. The CLS and GSFC00 MSS models were kindly provided by NASA/GSFC and CLS, respectively. Drs. Levitus, Monterey, and Boyer are thanked for providing the SST model. Dr. T. Gruber and two anonymous reviewers provided very detailed reviews that improved the quality of this paper.     

Algorithm for Harmonic Tidal Analysis along T/P Tracks： Taking Differences of Observed Sea Surface Heights at Adjacent Points as Observations

An algorithm （differential mode） is presented for the improvement of harmonic tidal analysis along T/P tracks, in which the differences between the observed sea surface heights at adjacent points are taken as observations. Also, the observation equations are constrained with the results of the crossover analysis; the parameter estimations are performed at 0.1° latitude intervals by the least squares. Cycle 10 to 330 T/P altimeter data covering the China Sea and the Northwest Pacific Ocean （2°-50° N,105°-150° E） are adopted for a refined along-track harmonic tidal analysis, and harmonic constants of 12 constituents in 8 474 points are obtained, which indicates that the algorithm can efficiently remove non-tidal effects in the altimeter observations, and improve the precision of tide parameters. Moreover, parameters along altimetry tracks represent a smoother distribution than those obtained by traditional algorithms. The root mean squares of the fitting errors between the tidal height model and the observations reduce from 11 cm to 1.3 cm.     

Geoid and high resolution sea surface topography modelling in the mediterranean from gravimetry,altimetry and GOCE data: evaluation by simulation

The determination of local geoid models has traditionally been carried out on land and at sea using gravity anomaly and satellite altimetry data, while it will be aided by the data expected from satellite missions such as those from the Gravity field and steady-state ocean circulation explorer (GOCE). To assess the performance of heterogeneous data combination to local geoid determination, simulated data for the central Mediterranean Sea are analyzed. These data include marine and land gravity anomalies, altimetric sea surface heights, and GOCE observations processed with the space-wise approach. A spectral analysis of the aforementioned data shows their complementary character. GOCE data cover long wavelengths and account for the lack of such information from gravity anomalies. This is exploited for the estimation of local covariance function models, where it is seen that models computed with GOCE data and gravity anomaly empirical covariance functions perform better than models computed without GOCE data. The geoid is estimated by different data combinations and the results show that GOCE data improve the solutions for areas covered poorly with other data types, while also accounting for any long wavelength errors of the adopted reference model that exist even when the ground gravity data are dense. At sea, the altimetric data provide the dominant geoid information. However, the geoid accuracy is sensitive to orbit calibration errors and unmodeled sea surface topography (SST) effects. If such effects are present, the combination of GOCE and gravity anomaly data can improve the geoid accuracy. The present work also presents results from simulations for the recovery of the stationary SST, which show that the combination of geoid heights obtained from a spherical harmonic geopotential model derived from GOCE with satellite altimetry data can provide SST models with some centimeters of error. However, combining data from GOCE with gravity anomalies in a collocation approach can result in the estimation of a higher resolution geoid, more suitable for high resolution mean dynamic SST modeling. Such simulations can be performed toward the development and evaluation of SST recovery methods.     

Landsat 8地表温度反演及验证—以黑河流域为例

地表温度是区域和全球尺度地表物理过程的一个重要参数,目前已有的地表温度产品空间分辨率较低,缺乏高空间分辨率的地表温度产品。Landsat系列卫星提供了大量免费的高空间分辨率遥感数据,然而对应的高空间分辨率地表温度产品还未见到,为了获取长时间序列的高空间分辨率地表温度数据,针对Landsat 8 TIRS数据提出了一个物理单通道地表温度反演算法。该算法首先利用ASTER全球地表发射率产品(ASTER GED)结合Landsat 8地表反射率产品计算Landsat 8影像的地表发射率,然后利用快速辐射传输模型RTTOV结合MERRA大气廓线数据对热红外影像进行大气校正,最后利用物理单通道地表温度反演算法得到地表温度。利用黑河流域HiWATER试验2013年—2015年15个站点的实测地表温度数据对本文方法和普适性单通道算法进行了验证,同时对验证站点的空间异质性进行了分析。结果表明,本文方法和普适性单通道算法估算的地表温度整体精度均较高,能够获取高精度、高空间分辨率的地表温度数据,可以服务于城市热岛效应、地表蒸散发估算等相关研究。     

Atacama Field Campaign: laboratory and in-situ measurements for remote sensing applications

This work presents the preliminary results of the first field calibration campaign performed in the Atacama Desert, Chile, between the 18 and 22 August 2014, called the Atacama Field Campaign (ATAFIC 2014). In situ measurements were performed in order to spectrally characterize the surface reflectance spectra between 0.3 and 2.5?µm, radiometric temperature (8.0–14.0?µm) and atmospheric measurements. A soil sample was collected and analyzed using Fourier Transform Infrared Spectroscopy and X-Ray Diffraction techniques to characterize the surface reflectance spectra and mineralogical composition, respectively. ASTER land surface emissivity in addition to GOES, MODIS and Landsat-8 land surface temperature (LST) were also used. Results showed that the spectral features of the Atacama soil and the characteristics of this geographical zone, which is featured as the most hyper-arid and cloudless place in the world, make this area a potential target for surface reflectance characterization. Day and night LST comparison between field and remote sensing data are lower than 2?K and the Root Mean Square Error for land surface emissivity is close to 2%. This work opens the possibilities to consider the Atacama Desert as a reference target for calibration and validation activities for earth observation missions’ purposes.     

MSS93A: A new stationary sea surface combining one year upgraded ERS-1 fast delivery data and 1987 GEOSAT altimeter data

Summary At the German Processing and Archiving Facility (D-PAF) an off-line altimeter data processing system has been developed with the capability to handle different satellite missions. For combining data from different missions an algorithm has been implemented that processes a reference sea surface from altimeter data of one mission while other mission data is taken to improve the spatial resolution of this reference model. In this way a stationary sea surface (MSS93A) was computed by compiling upgraded ERS-1 fast delivery data of the first year of the 35 day repeat cycle together with Geosat T2 GDRs of 1987.MSS93A was validated by means of comparisons to external models, gradient method and visualization techniques.