北极一年海冰表面积雪深度遥感反演与时序分析

北极海冰表面的积雪深度是重要的地球物理变量, 是研究物质与能量平衡、计算海冰厚度的重要参数。为减小不同被动微波传感器观测数据的系统误差, 对国防气象卫星计划(Defense Meteorological Satellite Program, DMSP)F17-SSMIS与F13-SSM/I重叠期亮度温度数据进行交叉定标, 建立4个频段48个月尺度定标模型, 并与传统年尺度定标模型进行比较和优选, 在此基础上估算并分析2003-2014年北极一年海冰表面积雪深度变化。结果表明:19H、19V、22V、37V频段1~5月的月尺度模型决定系数高于传统年尺度拟合模型; 2003-2014年, 北极一年海冰表面积雪深度总体呈现下降趋势, 同时积雪深度存在明显的周期性变化, 每年7月积雪深度最小, 9月最大; 东西伯利亚海、拉普捷夫海和巴伦支海海冰表面积雪深度呈现减少的趋势。     

业务化MODIS BRDF模型对冰雪BRDF/反照率的反演能力评估

全球MODIS冰雪反照率产品在定量遥感中有着广泛应用,但由于该产品的业务化算法是建立在表征植被—土壤系统基础上的罗斯表层(RT)李氏稀疏互易核(LSR)的二向性反射分布函数(BRDF)模型(简称为RTLSR),因此该模型对冰雪的二向性反射及反照率的反演能力有待评估。本文基于地球反射极化和方向测量仪(POLDER)的多角度冰雪反射率数据,综合评估了RTLSR模型在表征冰雪二向反射及反演反照率等方面的能力。为量化评估结果,本研究基于渐进辐射传输(ART)模型,从POLDER冰雪数据中筛选出高质量数据,使用ART模型拟合的高质量结果作为参考,比较结果表明:(1)在表征冰雪方向性散射方面,RTLSR模型整体拟合精度较低。在1020 nm波段,其均方根误差(RMSE)最大可达到0.0498,相较于ART模型的拟合结果偏高了约53.70%;(2)在反演冰雪反照率方面,RTLSR模型与ART模型反演结果也存在差别,其决定系数为0.529,均方根误差为0.0333,偏差为-0.0274,基于RTLSR模型的反演结果低估了ART模型的反演结果。为了使核驱动模型能更准确地表征冰雪BRDF特征和反演反照率,该模型需要针对冰雪散射特点进行进一步的发展。     

On the determination of surface emissivity from Satellite observations

Terrestrial brightness temperatures measured from satellites have been used to determine the surface emissivity. The results not only depend on surface temperature and on atmospheric properties, but also on the type of surface scattering. For otherwise identical conditions (same emissivity, same nonscattering atmosphere), the radiation above the Lambertian surface is larger than for a specular surface if the incidence angle is smaller than about 55/spl deg/. The opposite is true for larger angles. The effect leads to overestimates of emissivity for observations especially near nadir with the use of algorithms assuming specular reflection. The problem may be solved by the introduction of a specularity parameter to characterize realistic surfaces by a combination of specular and Lambert scattering. A simple solution lies in the use of conically scanning radiometers at a constant incidence angle near 55/spl deg/. Although the topic applies to all ranges of thermal radiation, the present discussion concentrates on the microwave spectrum in the Rayleigh-Jeans approximation.     

遥感理论模式研究的几个问题

本文简要地评论近年来微波遥感理论模式研究的进展,主要包括遥感对象理论模拟的随机离散散射粒子介质,连续随机介质,和随机粗糙表面的电磁散射和热辐射的理论,定量的数值求解方法,以及它们在地表植被、土壤、冰雪、大气云雨、海冰、风驱海面等主动和被动遥感中的应用。随着今后遥感技术的发展,要更为精细地模拟自然界中遥感对象及其环境,给出定量的数学物理学方法,进行定量的数据分析和遥感参数反演,还有大量的工作有待于研究。本文讨论了当今遥感理论模式研究中还存在的问题,提出了今后要予以研究的若干个方向性工作。     

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.     

High-resolution airborne infrared measurements of ocean skin temperature

Airborne measurements of ocean skin temperature T/sub s/ are presented from the Coupled Boundary Layers, Air-Sea Transfer in Low Winds (CBLAST-Low) Pilot Experiment in August 2001 off Martha's Vineyard, MA. We used an infrared (IR) camera with a spatial resolution of 1 m or less and temperature resolution of roughly 0.02/spl deg/C. Using subframe sampling of the IR imagery, we achieve lower noise and higher spatial resolution than reported by previous investigators using IR radiometers. Fine-scale maps of T/sub s/ exhibit horizontal variability over spatial scales ranging from O(10 km) down to O(1 m) that are related to atmospheric and subsurface phenomena under low to moderate wind conditions. Based on supporting measurements of wind and waves, we identify coherent ramp-like structures in T/sub s/ with stratification breakdown and meandering streaky features with internal waves. Regional maps of T/sub s/ show the standard deviation for the region is /spl plusmn/1.04/spl deg/C, while the meridional and zonal variability is 0.23/spl deg/C /spl middot/ km/sup -1/ and 0.27/spl deg/C /spl middot/ km/sup -1/, respectively. This temperature variability results in meridional and zonal scalar heat flux variability of 7.0 W /spl middot/ m/sup -2/ /spl middot/ km/sup -1/ and 7.6 W /spl middot/ m/sup -2/ /spl middot/ km/sup -1/, respectively. Our results demonstrate the potential for airborne IR imagery accompanied by high-quality ocean data to identify T/sub s/ features produced by subsurface circulation.     

Surface roughness signatures of summer arctic snow-covered sea ice in X-band dual-polarimetric SAR

ABSTRACT

Surface roughness of sea ice is primary information for understanding sea ice dynamics and air–ice–ocean interactions. Synthetic aperture radar (SAR) is a powerful tool for investigating sea ice surface roughness owing to the high sensitivity of its signal to surface structures. In this study, we explored the surface roughness signatures of the summer Arctic snow-covered first-year sea ice in X-band dual-polarimetric SAR in terms of the root mean square (RMS) height. Two ice campaigns were conducted for the first-year sea ice with dry snow cover in the marginal ice zone of the Chukchi Sea in August 2017 and August 2018, from which high-resolution (4 cm) digital surface models (DSMs) of the sea ice were derived with the help of a terrestrial laser scanner to obtain the in situ RMS height. X-band dual-polarimetric (HH and VV) SAR data (3 m spatial resolution) were obtained for the 2017 campaign, at a high incidence angle (49.5°) of TerraSAR-X, and for the 2018 campaign, at a mid-incidence angle (36.1°) of TanDEM-X 1–2 days after the acquisition of the DSMs. The sea ice drifted during the time between the SAR and DSM acquisitions. As it is difficult to directly co-register the DSM to SAR owing to the difference in spatial resolution, the two datasets were geometrically matched using unmanned aerial vehicle (4 cm resolution) and helicopter-borne (30 cm resolution) photographs acquired as part of the ice campaigns. A total of five dual-polarimetric SAR features―backscattering coefficients at HH and VV polarizations, co-polarization ratio, co-polarization phase difference, and co-polarization correlation coefficient ―were computed from the dual-polarimetric SAR data and compared to the RMS height of the sea ice, which showed macroscale surface roughness. All the SAR features obtained at the high incidence angle were statistically weakly correlated with the RMS height of the sea ice, possibly influenced by the low backscattering close to the noise level that is attributed to the high incidence angle. The SAR features at the mid-incidence angle showed a statistically significant correlation with the RMS height of the sea ice, with Spearman’s correlation coefficient being higher than 0.7, except for the co-polarization ratio. Among the intensity-based and polarimetry-based SAR features, HH-polarized backscattering and co-polarization phase difference were analyzed to be the most sensitive to the macroscale RMS height of the sea ice. Our results show that the X-band dual-polarimetric SAR at mid-incidence angle exhibits potential for estimation of the macroscale surface roughness of the first-year sea ice with dry snow cover in summer.     

基于卫星测高后向散射系数的极区海冰分布特性研究

海冰对气候变化非常敏感,了解极地海冰分布范围和表面属性不仅对于极地环境非常重要,对全球温度趋势估计和建立全球气候模型非常关键。ENVISAT卫星可覆盖至南北纬81.4°,其携带的RA2雷达高度计为极地海冰研究提供了周期性的主动微波海冰探测途径。本文用ENVISAT雷达高度计探测的Ku波段后向散射系数对2011年南极和北极各月份的海冰覆盖特征（范围和海冰表面属性）进行了详细研究,利用海水和海冰的不同散射特征,设置后向散射系数阈值为13db可成功分离海冰和海水。除夏季外,雷达高度计和美国冰雪数据中心基于辐射计获取的极区海冰覆盖边界高度符合。因北极中央区域（81.4°N以北）没有轨迹覆盖,本文只估计了南极海冰的覆盖面积,夏季海冰的覆盖范围面积比辐射计探测结果偏大,这和雷达高度计对离散薄冰较强的观测能力关,在海冰密集分布的其他季节结果则有很好的符合,其中冬季面积平均差异为0.17 Mkm2。分析了南极和北极海冰的分布特征差异,和南极相比北极冬季海冰表面较粗糙干燥,而夏季海冰表面湿度较大。本文研究结果表明ENVISAT雷达高度计可准确的探测包括海冰覆盖和海冰表面属性变化在内的海冰季节性演变过程,可在海冰监测、极地科考等领域中发挥重要作用。     

利用目标分解特征的全极化SAR海冰分类

特征提取及其选择是SAR海冰分类的重要步骤之一。在众多特征中选取有效特征,进而构建表达地物类型的特征空间是提高分类精度的关键。为此,本文提出一种基于目标分解特征的全极化SAR海冰分类算法。首先,对全极化SAR数据进行多视化处理及滤波操作,生成相干矩阵;其次,对相干矩阵进行目标分解,并针对分解结果提取散射特征参数,进而构建特征空间;再次,通过对所提取的特征进行统计相关性分析,并对高相关特征采用PCA降维,以优化特征组合;最后,设计BP神经网络分类器,并将所得的优化特征矢量作为输入,海冰类别为输出,实现海冰分类。本文以格陵兰中部海域作为研究试验区域,采用L波段ALOS PALSAR全极化数据。通过对本文算法与对比算法的分类结果进行定性定量分析,可以得出本文所选取的特征对海冰识别较好。此外,通过对利用各个不同特征海冰分类结果的性能分析,可以得出基于散射模型的目标分解比基于特征值的H/α/A分解更有助于海冰分类。     

Potential to estimate the canting angle of tilted structures in clouds from microwave radiances around 183 GHz

The effects of cloud structures on microwave radiances at frequencies from 89-190 GHz are investigated by simulations using the Goddard cumulus ensemble model data as input for a radiative transfer model. It was found that the brightness temperatures at these frequencies have different sensitivities to clouds with a tilted structure. The different sensitivities to altitude and amount of hydrometeors allow the estimation of the canting angle and tilt direction of tilted clouds using brightness temperatures at the water vapor channels at 183.3 /spl plusmn/ 1 and 183.3 /spl plusmn/ 7 GHz. The estimated canting angle and tilt direction are in agreement with the model situation. This method provides a potential to estimate tilted convective structures from microwave radiometric observations at 183.3 /spl plusmn/ 1 and 183.3 /spl plusmn/ 7 GHz. It is applied to a tilted storm observed from the National Aeronautics and Space Administration's ER-2 aircraft flying at about 20 km on August 26, 1998 during the third Convection and Moisture Experiment using the observed downlooking brightness temperatures at the water vapor channels of a Millimeter-wave Imaging Radiometer. The estimated results are in good agreement with the realistic storm situation obtained from the simultaneous observations of the ER-2 Doppler radar. This method also provides information about the vertical displacement of cloud structure and thereby to estimate the accurate location of surface rainfall. This is important when validating precipitation retrieval based on observations of the ice scattering above surface rainfall against surface rain observations using the microwave frequencies sensitive to high altitudes.     

Development of a snow wetness inversion algorithm using polarimetric scattering power decomposition model

In this paper, a new snow wetness estimation model is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. Surface and volume are the dominant scattering components in wet-snow conditions. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized surface and volume parameters are utilized to invert snow surface and volume dielectric constants using the Bragg coefficients and Fresnel transmission coefficients respectively. The snow surface and volume wetness are then estimated using an empirical relationship. The effective snow wetness is derived from the weighted averaged surface and volume snow wetness. The weights are derived from the normalized surface and volume scattering powers obtained from the generalized full-polarimetric SAR decomposition method. Six Radarsat-2 fine resolution full-polarimetric datasets acquired over Himachal Pradesh, India along with the near-real time in situ measurements were used to validate the proposed model. The snow wetness derived from the SAR data by the proposed model with in situ measurements indicated that the absolute error at 95% confidence interval is 1.3% by volume.     

基于NOAA/AVHRR数据的北极反照率反演及其变化研究

极地海冰反照率直接影响极区的热收支,反照率的变化对地气系统热量收支平衡及气候变化等的研究具有重要意义。本文采用由美国国家海洋与大气管理局NOAA (National Oceanic and Atmospheric Administration)发射的NOAA卫星携带的先进的甚高分辨率辐射仪AVHRR (Advanced Very High Resolution Radiometer) Level-1B (L1B) 数据,经宽带反射率转换、各向异性校正、大气订正、云检测等处理,得到4 km宽带晴空地表反照率产品。将AVHRR反照率与北冰洋地表热收支SHEBA (Surface Heat Budget of the Arctic Ocean)实验数据进行印证,印证结果显示在冰雪冻结期二者平均偏差为-0.07,标准偏差为0.05。本文处理了2008年—2010年的AVHRR数据,结合第4次北极科学考察现场观测数据研究了北极冰面月平均反照率的变化,从降雪和冰脊两个方面分析了反照率的变化,结果显示反照率在冰雪融化过程中变化约为0.3,变化较大且较为迅速,表面粗糙的多年冰海域和较为平滑的一年冰海域的反照率在雪融化时期变化约为0.2且变化相对缓慢。研究结果表明,由冰雪融化引起的反照率变化较为快速且幅度较大,是引起北极反照率变化的主导因素。     

Qualitative and quantitative analysis of snow parameters using passive microwave remote sensing

Snow cover is an important variable for climatic and hydrologic models due to its effect on surface albedo, energy, and mass balance. Satellite observations successfully provide a global and comprehensive hemispheric-scale record of the short-term, as well as inter-seasonal variations in snow cover. Passive microwave sensors provide an excellent method to monitor temporal and spatial variations in large-scale snow cover parameters, overcoming problems of cloud cover. Using microwave remote sensing data, snow parameters (snow surface temperature, snow water equivalence, scattering index, emissivity, snow depth) have been retrieved to integrate with the snow cover simulation model developed by SASE for avalanche risk assessment on regional basis. Multispectral and multitemporal brightness temperature data obtained from the Special Sensor Microwave Imager (SSM/I), flown onboard the DMSP satellites, for the period November 2000 to April 2001 and from November 2001 to February 2002 have been analysed. A comparative data set on snow measurements and meteorological observations of a region covering large area of Pir-Panjal and the Greater Himalayan range, available on near real time basis from SASE field observatories were also used. Model calculations were carried out to study the effects of atmospheric transmission on the microwave radiation emitted from the snow covered and snow free ground and atmosphere. The sensitivity of combinations of the SSM/I channels at 19, 37 and 85 GHz, in both horizontal and vertical polarizations, in respect to snow depth, surface temperature of the snowpack have been carried out. Decision rule based algorithms are developed to identify snow cover and non-snow area.     

一种使用卫星反射信号探测海冰分布新方法

利用TechDemoSat-1低轨道卫星采集的卫星反射信号生成的时延多普勒图（delay-doppler map,DDM）探测北极格陵兰岛（Greenland）地区的海冰分布。由于卫星散射信号在海冰和海水上分别遵循相干散射和漫散射模型,与海水相比,海冰的时延多普勒图扩散较少,所以从海水到海冰的过渡会导致时延多普勒图中高于一定能量值的像素数量减小。提出了一种基于相邻DDM像素数量比值的检测方法,通过采用一定阈值来区分海冰和海水的时延多普勒图,用于分析格陵兰岛地区海冰的分布情况。还利用多期数据分析了格陵兰岛地区海冰分布随时间的变化。通过与美国国家冰雪数据中心提供的数据比对,利用数学统计方法对本文提出的方法性能进行了评估。结果显示,该方法的判断成功率可以达到98.76%~99.21%,整体评估成功率约为99.09%。     

Digital elevation model of King Edward VII Peninsula, West Antarctica, from SAR interferometry and ICESat laser altimetry

We present a digital elevation model (DEM) of King Edward VII Peninsula, Sulzberger Bay, West Antarctica, developed using 12 European Remote Sensing (ERS) synthetic aperture radar (SAR) scenes and 24 Ice, Cloud, and land Elevation Satellite (ICESat) laser altimetry profiles. We employ differential interferograms from the ERS tandem mission SAR scenes acquired in the austral fall of 1996, and four selected ICESat laser altimetry profiles acquired in the austral fall of 2004, as ground control points (GCPs) to construct an improved geocentric 60-m resolution DEM over the grounded ice region. We then extend the DEM to include two ice shelves using ICESat profiles via Kriging. Twenty additional ICESat profiles acquired in 2003-2004 are used to assess the accuracy of the DEM. After accounting for radar penetration depth and predicted surface changes, including effects due to ice mass balance, solid Earth tides, and glacial isostatic adjustment, in part to account for the eight-year data acquisition discrepancy, the resulting difference between the DEM and ICESat profiles is -0.57/spl plusmn/5.88 m. After removing the discrepancy between the DEM and ICESat profiles for a final combined DEM using a bicubic spline, the overall difference is 0.05/spl plusmn/1.35 m.     

GNSS-MR技术用于雪深探测的初步研究

积雪是全球水循环中的重要组成部分,积雪深度与雪水当量的精确监测对全球气候变化研究极其重要。随着GNSS研究与应用的不断深入,基于多路径效应的GNSS-MR（GNSS multipath reflectometry）技术用于地表环境监测（植被、土壤湿度、雪深、海平面等）已成为一种新兴的遥感手段。分析了SNR（signal-to-noise ratio）信噪比值的变化特性,详细给出了基于SNR观测值的GNSS-MR技术探测雪深的基本原理及其计算流程图。为了验证算法的有效性,利用科罗拉多州17 d连续跟踪站NWOT的GPS数据反演了降雪厚度,其结果与实测的雪深记录数据吻合较好,误差均值为0.07 m。初步研究结果验证了GNSS-MR技术用于积雪深度探测的可行性,并为后续充分利用现有的全球密集GNSS跟踪站数据开展地表环境监测提供重要参考。     

小波变换与滑动窗口相结合的GNSS-IR雪深估测模型

GNSS干涉反射技术（GNSS interferometric reflectometry）是一种新型的地表雪深监测方式。针对当前信号分离不佳和随机估测偏差的问题,提出联合小波变换和滑动窗口构建一种多卫星融合的GNSS-IR雪深估测精化模型。该模型采用离散小波变换代替常用的多项式方法,获取高质量的信噪比序列。通过利用阈值约束下的滑动窗口筛选多卫星有效反射高度,并进行等权平均。以PBO H₂O和SNOTEL的雪深数据为参考值,利用2016—2017年雪季的GNSS观测数据建立模型并验证精度。结果表明：①GNSS-IR精化模型估测结果与实测数据在整体趋势上保持高一致性;②与单颗卫星结果相比,多卫星融合估测结果在精度和稳定性方面明显改善,其均方根误差（RMSE）为10 cm,相较于PBO H₂O减少了近50%。此外,考虑到地表粗糙度作为一种误差影响因素,采用新的反射高度基准修正的雪深估测相对RMSE误差约4 cm,同时估测值与实际值的相关系数达到0.98。     

高斯过程回归辅助下的GPS干涉反射积雪深度估测

本文对全球定位系统干涉反射技术进行了研究。以美国板块边界天文台计划提供的P101测站的GPS监测数据为基础,利用GPS卫星高度角低于某一角度时多路径效应明显的特点,构建高斯过程回归(GPR)辅助的GPS干涉反射积雪深度估测模型,并监测了测站周围的积雪深度。结果表明,GPR辅助的GPS干涉反射积雪深度估测模型输出的雪深估测值的精度,相比传统单星反演结果有不同程度的提高,并且更贴近实测雪深的变化,为地表雪深反演提供了新思路。     

ARGO upper salinity measurements: perspectives for L-band radiometers calibration and retrieved sea surface salinity validation

With the view of preparing the strategy for the calibration/validation of future L-band satellite radiometers, we examine the salinity variability recorded by Array for Real-Time Geostrophic Oceanography (ARGO) floats in the upper 10-m layer of the surface ocean. Using one year of ARGO measurements,we show that the surface salinity variability at ten days and 200-km scales is above /spl plusmn/0.1 psu for 30% of the drifters and that this variability is larger than 0.2 psu in tropical regions affected by strong river discharges and by precipitations, and in frontal areas characterized by strong mesoscale activity. Vertical gradient observed between 5-10-m depth is much lower than the horizontal variability but leads to systematic biases in the tropics. The South Pacific Ocean appears to be the less variable both vertically and horizontally.     

Snow permittivity retrieval inversion algorithm for estimating snow wetness

The environmental satellite (ENVISAT) advanced synthetic aperture radar (ASAR) offers the opportunity for monitoring snow parameters with dual polarization and multi-incidence angle. Snow wetness is an important index for indicating snow avalanche, snowmelt runoff modelling, water supply for irrigation and hydropower stations, weather forecasts and understanding climate change. We used a first-order scattering model that includes both volume and air/snow surface scattering based on a developed inversion model to estimate snow dielectric constant, which can be further related for estimating snow wetness. Comparison with field measurement showed that the correlation coefficient for snow permittivity estimated from ASAR data was observed to be 0.8 at 95% confidence interval and model bias was observed as 2.42% by volume at 95% confidence interval. The comparison of ASAR-derived snow permittivity with ground measurements shows the average absolute error 2.5%. The snow wetness range varies from 0 to 15% by volume.