Effect of air-sea temperature difference on ocean microwave brightness temperature estimated from AMSR,SeaWinds, and buoys

The effect of air-sea temperature differences on the ocean microwave brightness temperature (Tb) was investigated using the Advanced Microwave Scanning Radiometer (AMSR) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) during a period of seven months. AMSR Tb in the global ocean was combined with wind data supplied by the scatterometer SeaWinds aboard ADEOS-II and air temperature given by a weather forecast model. Tb was negatively correlated with air-sea temperature difference, its ratio lying around −0.4K/°C at the SeaWinds wind speed of 14 m/s for the 6 GHz vertical polarization. Tb of AMSR-E aboard AQUA during 3.5 years was combined with ocean buoy data, and similar results were obtained.     

Features of ocean microwave emission changed by wind at 6 GHz

Ocean microwave emissions changed by the ocean wind at 6 GHz were investigated by combining data of the Advanced Microwave Scanning Radiometer (AMSR) and SeaWinds, both aboard the Advanced Earth Observation Satellite-II (ADEOS-II). This study was undertaken to improve the accuracy of the sea surface temperature (SST) retrieved from the AMSR 6 GHz data. Two quantities, 6V*(H*), were defined by the brightness temperature of the AMSR at 6 GHz with two polarizations (V-pol and H-pol), adjusted for atmospheric effects and with a calm ocean surface emission removed. These quantities represent a microwave emission change due to the ocean wind at 6 GHz. 6V* does not change in a region where 6H* is less than around 4 K (referred to as z0). Both 6V* and 6H* increase above z0. The 6V* to 6H* ratio, sp, varies with the relative wind directions. Furthermore, the sp values vary with the SST, between the northern and southern hemisphere, and seasonally. By specifying appropriate values for z0 and sp, the SST error between AMSR and buoy measurement became flat against 6H*, which is related to the ocean wind. Two extreme cases were observed: the Arabian Sea in summer and the Northwestern Atlantic Ocean in winter. The air-sea temperature difference in the former case was largely positive, while it was largely negative in the latter. The 6V* and 6H* relations differed from global conditions in both cases, which resulted in incorrect SSTs in both areas when global coefficients were applied.     

Difference characteristics of sea surface temperature observed by GLI and AMSR aboard ADEOS-II

This study compares infrared and microwave measurements of sea surface temperature (SST) obtained by a single satellite. The simultaneous observation from the Global Imager (GLI: infrared) and the Advanced Microwave Scanning Radiometer (AMSR: microwave) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) provided an opportunity for the intercomparison. The GLI-and AMSR-derived SSTs from April to October 2003 are analyzed with other ancillary data including surface wind speed and water vapor retrieved by AMSR and SeaWinds on ADEOS-II. We found no measurable bias (defined as GLI minus AMSR), while the standard deviation of difference is less than 1°C. In low water vapor conditions, the GLI SST has a positive bias less than 0.2°C, and in high water vapor conditions, it has a negative (positive) bias during the daytime (nighttime). The low spatial resolution of AMSR is another factor underlying the geographical distribution of the differences. The cloud detection problem in the GLI algorithm also affects the difference. The large differences in high-latitude region during the nighttime might be due to the GLI cloud-detection algorithm. AMSR SST has a negative bias during the daytime with low wind speed (less than 7 ms⁻¹), which might be related to the correction for surface wind effects in the AMSR SST algorithm.     

Evaluation of marine surface winds observed by SeaWinds and AMSR on ADEOS-II

Marine surface winds observed by two microwave sensors, SeaWinds and Advanced Microwave Scanning Radiometer (AMSR), on the Advanced Earth Observing Satellite-II (ADEOS-II) are evaluated by comparison with off-shore moored buoy observations. The wind speed and direction observed by SeaWinds are in good agreement with buoy data with root-mean-squared (rms) differences of approximately 1 m s⁻¹ and 20°, respectively. No systematic biases depending on wind speed or cross-track wind vector cell location are discernible. The effects of oceanographic and atmospheric environments on the scatterometry are negligible. Though the wind speed observed by AMSR also showed agreement with buoy observations with rms difference of 1.27 m s⁻¹, the AMSR wind speed is systematically lower than the buoy data for wind speeds lower than 5 m s⁻¹. The AMSR wind seems to have a discontinuous trend relative to the buoy data at wind speeds of 5–6 m s⁻¹. Similar results have been obtained in an intercomparison of wind speeds globally observed by SeaWinds and AMSR on the same orbits. A global wind speed histogram of the AMSR wind shows skewed features in comparison with those of SeaWinds and European Centre for Medium-range Weather Forecasts (ECMWF) analyses.     

Correction of the effect of relative wind direction on wind speed derived by advanced microwave scanning radiometer

The sea surface wind speed (SSWS) derived by a microwave radiometer can be contaminated by changes of the brightness temperature owing to the angle between the sensor azimuth and the wind direction (Relative Wind Direction effect: RWD effect). We attempt to apply the method proposed by Konda and Shibata (2004) to the SSWS derived by Advanced Microwave Scanning Radiometer (AMSR) on Advanced Earth Observing Satellite II (ADEOS-II), in order to correct for the RWD effect. The improvement of accuracy of the SSWS estimation amounts to roughly 60% of the error caused by the RWD effect. Comparison with in situ observation at the Tropical Atmosphere Ocean (TAO) array shows that the root mean square error of the corrected SSWS is 1.1 ms⁻¹. It is found that the impact of the RWD effect on the estimation of the latent heat flux can amount to about 30 Wm⁻² on average. We applied the method to the SSWS derived by AMSR for Earth Observing System (AMSR-E) and obtained a similar result.     

基于微波散射计观测的气候态海面风场和风应力场

收集了星载微波散射计NSCAT,QuikSCAT和SeaWinds on ADOES-II的全球海面风速和方向L2B数据,数据涉及的时间序列长度为11.5 a。通过对所收集数据的质量控制、Loess低通空间滤波和统计处理,构建了气候态的逐月全球海面风场、风应力场和风应力旋度场(简称为SCAT),其空间网格间距为0.25°×0.25°。SCAT资料与其他有关资料相比,包含了更丰富的海面风场中小尺度空间变化的信息,可广泛应用于海洋、气候、海气相互作用等方面的研究,特别适合应用于海洋中小尺度过程的研究。作为我国"海洋二号"("HY-2")卫星预研项目的成果之一,SCAT资料将由国家海洋局国家卫星海洋应用中心提供给有关用户。     

HY-2微波辐射计降雨条件下海面风速反演算法研究

由于降雨改变了海洋-大气的辐射/散射特性,长期以来星载遥感器在降雨条件下进行海面风速信息提取存在困难。本文针对自主海洋动力环境卫星海洋2号（HY-2）搭载的扫描微波辐射计,分析了不同频段亮温对降雨和海面风速敏感性,自此基础上获得了一种对降雨不敏感的亮温通道组合,该亮温通道组合对海面风速的敏感性甚至高于原有亮温通道。本文利用该亮温通道组合建立了降雨条件下的风速反演算法,并将反演结果与WindSat全天候风速产品、HY-2微波辐射计原有风速产品以及浮标实测数据进行了比较。结果表明本文算法在降雨条件下的反演误差小于2m/s,明显优于原有HY-2微波辐射计风速产品,验证了本文发展的算法在降雨条件下的风速反演能力。     

基于南太平洋的AMSR2L1R亮温数据质量评估

本文基于环境场较为稳定的南太平洋目标海区,以海洋大气微波辐射传输模型(Radiative Transfer Model,RTM)模拟亮温作为参考值,对2015年1月1日—2017年12月31日的高级扫描微波辐射计(Advanced Microwave Scanning Radiometer 2,AMSR2) L1R亮温数据产品进行了质量评估。结果表明AMSR2 L1R所有通道亮温数据总偏差和标准偏差的变化范围分别为1.466～6.352 K、0.270～1.693 K,其中标准偏差在水平极化通道较大的同时随着频率的增大而增大。相比同类遥感器如全球降水测量微波成像仪(Global Precipitation Measurement Microwave Imager,GMI)等的质量分析结果,AMSR2亮温数据的标准偏差较小,这表明AMSR2亮温数据精度较高。对AMSR2 L1R亮温数据3年长时间序列的变化趋势分析表明所有通道亮温偏差均在±0.5 K范围内波动但是存在微弱的季节性变化,标准偏差随时间的变化较小,这表明AMSR2 L1R亮温数据质量较为稳定。     

Neural network-based method for the estimation of the rain rate over oceans by measurements of the satellite radiometer AMSR2

The rain rate (RR) retrieval method for the RR estimation over ice-free areas of the ocean is presented. Measurements of the Japanese Advanced Microwave Scanning Radiometer 2 (AMSR2) on board the satellite GCOM-W1 are used. The method is based on the results of the numerical modeling of brightness temperatures of the outgoing microwave radiation of the ocean–atmosphere system and their subsequent conversion into the RR using neural networks. A simplified form of the transfer equation is used. Its errors for the considered wavelengths do not exceed 1 K at an RR of less than 20 mm/h. The method is verified by comparison with the Tropical Rainfall Measuring Mission’s (TRMM) Microwave Instrument (TMI) RR product. As a result of the comparison, the rain rate retrieval error within the range of 20 mm/h is found to be 1 mm/h.     

Algorithm and validation of sea surface temperature observation using MODIS sensors aboard terra and aqua in the western North Pacific

A regional algorithm to estimate SST fields in the western North Pacific, where small oceanographic disturbance are often found, has been developed using Moderate Resolution Imaging Spectroradiometers (MODIS) aboard Terra and Aqua. Its associated algorithm, which includes cloud screening and SST estimation, is based on an algorithm for the Global Imager (GLI) aboard Advanced Earth Observing Satellite-II (ADEOS-II) and is tuned for MODIS sensors. For atmospheric correction, we compare Multi-Channel SST (MCSST), Nonlinear SST (NLSST), Water Vapor SST (WVSST) and Quadratic SST (QDSST) techniques. For NLSST, four first-guess SSTs are investigated, including the values for MCSST, climatology with two different spatial resolutions, and near-real-time objective analysis. The results show that the NLSST method using high-resolution climatological SST as a first-guess has both good quality and high efficiency. The differences of root-mean-square error (RMSE) between the NLSST models using low-resolution climatology and those using high-resolution climatology are up to 0.25 K. RMSEs of the new algorithm are 0.70 K/0.65 K for daytime (Aqua/Terra) and 0.65 K/0.66 K for nighttime, respectively. Diurnal warming and the stratification of the ocean surface layer under low wind are discussed.     

Radiometric observations of sea temperature at 2.65 GHZ over the chesapeake bay

The present work describes the various corrections necessary in order to deduce ocean surface temperature fromS-band microwave radiometer measurements and applies these results to a series of data obtained with a high absolute accuracy radiometer. Measurements made with a 2.65 GHz radiometer from an aircraft flown over the Chesapeake Bay area are presented and compared in detail with accurately obtained sea truth data. For the calm sea, it was found that the observed brightness temperature agreed well with that calculated from the known sea surface and atmospheric properties over a fairly wide range of surface salinity values (0.2 per mille to 25 per mille). For cases where the surface wind speeds are of the order of 7 to 15 knots, an excess brightness temperature was observed which is attributable to surface roughness and microscale surface disturbances. The excess brightness temperature dependence on wind speed was found to correlate to a certain extent with the rms wave slope dependence on wind speed.     

基于一维综合孔径微波辐射计的大气海洋环境参数敏感性分析

相比于实孔径微波辐射计,一维综合孔径微波辐射计具有高空间分辨率和多入射角观测特点。本文提出采用观测频率为6.9,10.65,18.7,23.8和36.5 GHz,且入射角范围为0°~65°的一维综合孔径微波辐射计遥感大气海洋环境要素。基于构建的微波大气海洋辐射传输正演模型,分析了辐射计亮温对大气海洋环境要素的敏感性,为辐射计关键指标确定和大气海洋环境要素反演算法设计提供技术支撑。结果表明：一维综合孔径微波辐射计的垂直和水平极化亮温对大气海洋环境要素的敏感性表现出不同特性,且敏感性随入射角的改变而变化显著;6.9和10.65 GHz对海面温度的敏感性较大,且随着入射角的增大,垂直极化亮温的敏感性增大,水平极化亮温的敏感性减小;10.65和18.7 GHz对海面风速的敏感性相对较大,且敏感性最大的风速区间位于10~20 m/s;23.8 GHz对大气水汽含量最敏感,且水汽含量较低、入射角较大时,敏感性越大;36.5 GHz对云液态水含量最敏感,随着入射角的增大,垂直极化亮温的敏感性减小,水平极化的敏感性增大,但两者均在液态水含量较小时表现出较大的敏感性。     

利用机载GNSS反射信号反演海面风速的研究

全球卫星导航定位系统的反射信号(GNSS-R)遥感技术作为一种新型的、低成本的、高机动性的海面微波遥感测风技术,与其他测风手段优势互补,可以增加测风手段的多样性,弥补局部测风手段不足的状况。研究了接收机在机载高度时,GPS反射信号功率理论模型四部分函数的性质,在此基础之上,数值模拟了机载高度下理论相关功率波形,基于海面风速对波形峰值与后沿的影响,提出了一种能够兼顾所有理论波形信息的二维插值风速反演方法。利用该方法,结合实测机载数据对海面风速进行反演,反演的风速均值与附近测站风速均值相差为1.4 m/s,与浮标数据相一致。     

Microwave Remote Sensing of Tropical Cyclones from Space

This article reviews several microwave instruments employed in research and analysis of tropical cyclones (TCs), typhoons, and hurricanes. The instruments discussed include scatterometers, microwave radiometers, synthetic aperture radars (SARs), and rain radar from space. Examples of the particular contribution by one or more of these instruments in analysis of several storms illustrate the comprehensive new views provided by the SeaWinds scatterometers, the detailed high-resolution wind field provided by RADARSAT-1 SAR, particularly inside and in the vicinity of hurricane “eyes,” and the presence of secondary flows in the region between rainbands in TCs. The high spatial resolution of precipitation data from the Tropical Rainfall Measuring Mission's rain radar, combined with scatterometer or SAR data, give a significant improvement in the details that can be seen from space, at the surface, and in the precipitating areas of TCs. The microwave instruments provide a penetrating view below the upper level cirrus clouds. This revised version was published online in August 2006 with corrections to the Cover Date.     

各向异性海面全极化微波双站散射的仿真与分析

为了解各向异性随机粗糙海面的微波双站散射机制及其特性，本文利用解析近似的积分方程模型以及一种改进的半经验海浪谱模型实现了对各向异性随机粗糙海面的全极化微波散射仿真模拟，并与卫星观测数据、经验的地球物理模式函数及已有的解析近似散射模型仿真结果进行了对比，验证了仿真结果的可行性和准确性。利用该模型分析了入射波频率、入射角、极化方式、海面风速及风向等参数对各向异性海面双站散射的影响。模拟结果表明，在不同的入射角、散射角及方位角等观测几何条件下，海面不同波段的双站散射表现出不同的空间散射特性，且对风速、风向等海面动力学参数表现出不同的敏感性，以L波段为例，海面向后半球双站散射在各个极化方式下都对风速较为敏感，而在同极化方式下，其对风向的响应在中低风速和高风速条件下相反，整体而言，低风速下海面双站散射对风向更为敏感。这表明对于海面动力参数的反演，双站散射可以提供比传统单站雷达后向散射更丰富的物理信息。本文探讨了各向异性海面微波双站散射特性，为基于主动式及分布式微波传感器的海洋动力参数遥感反演提供了理论分析基础。     

HY-2B卫星载荷联合观测海面阵风的一种反演方法

国内外对海上阵风的研究并不多,且大多集中在阵风预报和应用研究方面,对于海洋阵风数据的获取技术未见文献系统论述。本文利用HY-2B卫星雷达高度计观测的后向散射系数,结合校正微波辐射计观测的亮度温度信息,提出联合反演阵风风速的方法。两个遥感载荷联合反演得到的阵风风速与2019–2021年美国国家浮标数据中心（NDBC）浮标数据进行真实性检验,结果显示:阵风风速均方根误差（RMSE）为0.98 m/s,相关系数为0.82;基于本方法利用国外同类卫星Jason-3得到的阵风风速与2016–2018年NDBC浮标数据的RMSE为0.96 m/s,相关系数为0.88。本文在HY-2B卫星雷达高度计海面风速观测的基础上,纳入同一卫星平台校正微波辐射计的同步观测信息联合实现了海面阵风的观测,数据的比对结果证明文中方法具有较高的观测精度。同时,该方法对于具有相同观测体制的国内外卫星也适用。     

六种遥感海表温度产品的比对分析

海表温度(sea surface temperature, SST)产品是研究全球海洋大气系统的重要数据源, 在海洋相关领域的研究和应用方面具有重要价值。对2007年1和7月的六种不同SST产品(AVHRR-only, AMSR+AVHRR, NCODA, RSS, RTG-HR和OSTIA)在南大洋阿古拉斯回流(Agulhas Return Current, ARC)与绕极环流交汇区域的产品特性进行了比对统计分析, 包括SST分析、SST梯度分析、统计参数分析和波数谱分析。分析结果表明产品之间SST时空变化分布的整体趋势一致, RTG-HR在空间分布上过于平滑, OSTIA解析的大洋锋面最弱, RSS包含噪声较多, NCODA相对其他产品存在较大偏差。发现在AVHRR数据的覆盖率较好的情况下与以红外数据构建的AVHRR-only相比, AMSR数据并不能提供更多的SST信息, 反而会降低产品的空间解析能力。     

Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite

HY-2 satellite is the first satellite for dynamic environmental parameters measurement of China,which was launched on 16th August 2011.A scanning microwave radiometer（RM） is carried for sea surface temperature（SST）,sea surface wind speed,columnar water vapor and columnar cloud liquid water detection.In this paper,the initial SST product of RM was validated with in-situ data of National Data of Buoy Center（NDBC） mooring and Argo buoy.The validation results indicate the accuracy of RM SST is better than 1.7 C.The comparison of RM SST and WindSat SST shows the former is warmer than the latter at high sea surface wind speed and the difference between these SSTs is depend on the sea surface wind speed.Then,the relationship between the errors of RM SST and sea surface wind speed was analyzed using NDBC mooring measurements.Based on the results of assessment and errors analysis,the suggestions of taking account of the affection of sea surface wind speed and using sea surface wind speed and direction derived from the microwave scatteromter aboard on HY-2 for SST product calibration were given for retrieval algorithm improvement.     

基于C-2PO模型和CMOD5.N地球物理模式函数的SAR风速反演性能评估

本文选取142幅RADARSAT-2全极化合成孔径雷达（SAR）影像，在没有入射角输入的情况下，首先利用C-2PO模型进行海面风速反演。随后，将同一时空下的ASCAT散射计风向作为初始风向，提取相应雷达入射角，利用地球物理模式函数（GMF） CMOD5.N对142幅SAR影像进行风速计算。反演结果与美国国家资料浮标中心海洋浮标风速数据对比，结果显示:CMOD5.N GMF和C-2PO模型均可反演出较高精确度的海面风速，其均方根误差分别为1.68 m/s和1.74 m/s。此外，研究发现，在低风速段，CMOD5.N GMF的风速反演精度要明显优于C-2PO模型。针对这一现象，本文以SAR系统成像机理为基础，以低风速SAR图像为具体案例，给出了3种造成这一现象的原因。     

A study of a new retrieval algorithm for measurement of oceanic windvectors field using satellite microwave scatterometer

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