HY-2B卫星散射计海面风场产品质量分析 *

星载微波散射计是获取全球海面风场信息的主要手段, HY-2B卫星散射计的成功发射为全球海面风场数据获取的持续性提供了重要保障。本文利用欧洲中期天气预报中心(European Center for Medium-Range Weather Forecasts, ECMWF)再分析风场数据、热带大气海洋观测计划(Tropical Atmosphere Ocean Array, TAO)和美国国家数据浮标中心(National Data Buoy Center, NDBC)浮标获取的海面风矢量实测数据, 对HY-2B散射计海面风场数据产品的质量进行统计分析。分析表明, HY-2B风场与ECMWF再分析风场对比, 在4~24m·s^-1风速区间内, 风速和风向均方根误差(root mean square error, RMSE)分别为1.58m·s^-1和15.34°; 与位于开阔海域的TAO浮标数据对比, 风速、风向RMSE分别为1.03m·s^-1和14.98°, 可见HY-2B风场能较好地满足业务化应用的精度要求(风速优于2m·s^-1, 风向优于20°)。与主要位于近海海域的NDBC浮标对比, HY-2B风场的风速、风向RMSE分别为1.60m·s^-1和19.14°, 说明HY-2B散射计同时具备了对近海海域风场的良好观测能力。本文还发现HY-2B风场质量会随风速、地面交轨位置等变化, 为用户更好地使用HY-2B风场产品提供参考。     

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。     

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。     

基于神经网络的卫星高度计海面风速反演算法

通过对TOPEX/Poseidon高度计资料与NDBC浮标实测数据进行时空匹配处理,得到同步数据集,利用人工神经网络方法试验得到海面风速反演算法,并与业务运行的M CW算法进行分析比较,指出考虑波浪状态影响因素的神经网络算法在均方根误差和对称性方面的优越性。研究表明利用神经网络方法反演海面风速是可行的。     

降雨条件下全极化微波辐射计海面风场校正

为提高降雨条件下星载全极化微波辐射计海面风场精度,通过匹配WindSat海面风场和降雨率数据以及美国国家浮标中心浮标观测数据,得到18 996组匹配样本,深入分析了降雨对海面风场反演精度的严重影响,构建了风场校正模型。试验结果表明,降雨导致海面风速被严重高估,风向误差随着降雨率的增大而增大。校正后的风速精度在低风速段提升明显。无论降雨率多大,校正后风速精度均比校正前高。风速均方根误差由原来的2.9 m/s降低到了2.1 m/s,风向均方根误差由原来的26.9°降低到了26.3°。     

基于浮标数据的卫星雷达高度计海浪波高数据评价与校正

卫星雷达高度计是海浪有效波高（significant wave height,SWH）观测的重要手段之一,本文利用时空匹配方法对T/P、Jason-1、Envisat、Jason-2、Cryosat-2和HY-2A共6颗卫星雷达高度计SWH数据与NDBC（National Data Buoy Center,NDBC）浮标SWH数据进行对比验证,并对雷达高度计SWH数据进行校正。全部卫星雷达高度计SWH数据时间跨度为1992年9月25日到2015年9月1日,对比验证NDBC浮标共53个,包括7个大洋浮标。精度评价发现除T/P外,各卫星雷达高度计SWH的RMSE都在0.4~0.5 m之间,经过校正后,RMSE都有显著下降,下降程度最大为13.82%;对于大洋浮标,评价结果RMSE在0.20~0.28 m之间,结果明显优于全部NDBC浮标的精度评价结果;HY-2A卫星雷达高度计SWH在经过校正后数据质量与国外其他5颗卫星雷达高度计SWH数据质量差异较小。     

两种ASCAT 散射计风产品的比较及评估

基于浮标和步进频率微波辐射计(SFMR,Stepped-Frequency Microwave Radiometer)数据对NASA JPL(Jet Propulsion Laboratory)和RSS(Remote Sensing Systems)公司分别发布的已广泛应用于全球海面风场观测的ASCAT(Advanced SCATterometer)散射计风产品进行了比较和分析。结果表明,两者风速在中低风速(15 m/s)时基本一致;高风速(15 m/s)时RSS风速整体高于JPL风速。通过浮标数据对比,风速15 m/s时两者风速精度一致;风速15 m/s时两者风速RMS相当,但JPL和RSS风速分别低估和高估。利用SFMR数据检验表明RSS风速与SFMR风速一致性更好。两者风向精度在低风速(5 m/s)时较低,但随风速增加而提高并趋于稳定。该研究结果对相关科研人员的ASCAT散射计风产品选择具有重要的指导意义。     

基于SMOS卫星数据的BP神经网络盐度反演模型

海表面盐度SSS(Sea Surface Salinity)是研究大洋环流和海洋对气候影响的重要参量、是决定海水基本性质的重要因素之一。卫星微波遥感可以满足盐度研究过程中大范围、连续观测的需要。目前,由欧洲空间局设计开发的SMOS(Soil Moisture and Ocean Salinity)卫星于2009年发射成功,并且根据它的观测数据和物理机制反演出了海表面盐度的相关产品。但结果显示,在某些近海岸区域(如中国南海海域)受陆地RFI等诸多因素的影响,基于卫星遥感物理机制反演得到的盐度产品的精度较低。本文的主要目的是利用中国海洋大学"东方红2"科学考察船的走航数据、SMOS卫星数据,针对中国南海海域提出了用BP神经网络预测海表面盐度的方法,并用实测Argo浮标、WOA13的盐度数据对模型进行适应性评估。结果表明,模型产品相对于"东方红2"实测盐度数据的均方根误差(RMSE)是0.21,而SMOS的SSS1产品、SSS2产品和SSS3产品的精度分别为1.90、1.93和1.91。同时,在验证数据集中,模型预测数据相对于Argo浮标实测盐度数据的均方根误差(RMSE)是0.50,而SMOS的SSS1产品、SSS2产品和SSS3产品的精度分别为1.83、1.83和1.84。此模型具有良好的适应性和泛化能力,为海表面盐度的反演和预测提供了一个不依赖于物理机制的新方法。     

基于雷达高度计增益自动控制数据的风速反演算法研究

基于Jason-1卫星雷达高度计与NDBC(National Data Buoy Center)浮标的时空匹配数据集,利用BP(Back Propagation)神经网络方法建立了基于后向散射系数σ₀与有效波高(Significant Wave Height,SWH,)的双参数(σ₀-H_sw)风速反演模型,并探讨利用AGC(Automatic Gain Control)来代替σ₀对风速反演的可行性进行研究。结果表明,所建立的σ₀-SWH风速反演均方根优于0.3 m/s(风速范围为0.5~20 m/s); AGC-SWH模型反演精度偏低(1.3 m/s),但在星星交叉定标的基础上,模型精度提高了0.9 m/s。这个研究工作尤其是交叉定标基础上的AGC-SWH模型反演流程对"HY-2"海面风速反演有一定的借鉴意义。     

利用遗传算法反演实时近海面气温和比湿

使用Advanced Microwave Scanning Radiometer for EOS(AMSR-E)的海洋产品数据海表温度、风速,大气水蒸气、云液态水,通过遗传算法建立其与近海面气温和比湿之间的经验关系,进行近海面气温和比湿的实时反演.反演结果与The Tropical Ocean-Atmosphere(TAO)和The National Data Buoy Center(NDBC)的浮标实测资料进行比较,实时近海面气温和比湿的均方根误差分别为1.18℃和1.36 g/kg.分析结果表明,利用遗传算法采用AMSR-E海洋产品数据可以较好地反演近海面气温和比湿.     

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.     

First six months quality assessment of HY-2A SCAT wind products using in situ measurements

The first Chinese microwave ocean environment satellite HY-2A, carrying a Ku-band scatteromenter （SCAT）, was successfully launched in August 2011. The first quality assessment of HY-2A SCAT wind products is presented through the comparison of the first 6 months operationally released SCAT products with in situ data. The in situ winds from the National Data Buoy Center （NDBC） buoys, R/V Polarstern, Aurora Australis, Roger Revelle and PY30-1 oil platform, were converted to the 10 m equivalent neutral winds. The temporal and spatial differences between the HY-2A SCAT and the in situ observations were limited to less than 5 min and 12.5 km. For HY-2A SCAT wind speed products, the comparison and analysis using the NDBC buoys yield a bias of-0.49 m/s, a root mean square error （RMSE） of 1.3 m/s and an increase negative bias with increasing wind speed observation above 3 m/s. Although less accurate of HY-2A SCAT wind direction at low winds, the RMSE of 19.19° with a bias of 0.92° is found for wind speeds higher than 3 m/s. These results are found consistent with those from R/Vs and oil platform comparisons. Moreover, the NDBC buoy comparison results also suggest that the accuracy of HY-2A SCAT winds is consistent over the first half year of 2012. The encouraging assessment results over the first 6 months show that wind products from HY-2A SCAT will be useful for scientific community.     

The validation of the significant wave height product of HY-2 altimeter-primary results

The HY-2 satellite was successfully launched on 16 August 2011. The HY-2 significant wave height （SWH） is validated by the data from the South China Sea （SCS） field experiment, National Data Buoy Center （NDBC/ buoys and Jason-1/2 altimeters, and is corrected using a linear regression with in-situ measurements. Com- pared with NDBC SWH, the HY-2 SWH show a RMS of 0.36 m, which is similar to Jason- 1 and Jason-2 SWH with the RMS of 0.35 m and 0.37 m respectively; the RMS of corrected HY-2 SWH is 0.27 m, similar to 0.27 m and 0.23 m of corrected Jason-1 and Jason-2 SWH. Therefore the accuracy of HY-2 SWH products is close to that of Jason-1/2 SWH, and the linear regression function derived can improve the accuracy of HY-2 SWH products.     

An algorithm for the quality checking of wind speeds measured at sea against measured wave spectral energy

The purpose of this study is to provide a quality-checking tool for the evaluation of wind-wave data from buoys deployed by the National Data Buoy Center (NDBC). In particular, an algorithm is sought that will compare measured wind speed with spectral data in a chosen range. In the past, anemometers have been known to fail without failing completely, returning data that are bad, but not obviously bad. The aim here is to provide an automated test that will flag such data, as well as detecting certain malfunctions of the wave-measuring system. Towards this end, large quantities of data are studied and several approaches to the problem are described before an algorithm is finally recommended. The algorithm takes account of physical properties of the ocean (as observed from this data set) as well as the statistical relationships determined between wind speed and wave energy. The implementation and testing of the algorithm are described.     

Derivation of Parametric Tropical Cyclone Models for Storm Surge Modeling

In this paper, the parametric tropical cyclone models for storm surge modeling are further developed. Instead of tangential wind speed via cyclostrophic balance and radial wind speed using a simple formulation of defection angle, the analytical expressions of tangential and radial wind speed distribution are derived from the governing momentum equations based on the general symmetric pressure distribution of Holland and Fujita. The radius of the maximum wind is estimated by tropical cyclone wind structure which is characterized by the radial extent of special wind speed. The shape parameter in the pressure model is estimated by the data of several tropical cyclones that occurred in the East China Sea. Finally, the Fred cyclone (typhoon 199417) is calculated, and comparisons of the measured and calculated air pressures and wind speed are presented.     

4种表层风场资料在北半球海域的适用性评估

为进行海洋表层风场的物理结构重建与基础理论溯源,需选用可靠准确且通过检验的高时空分辨率风场资料。本文利用NDBC、TAO和嵊泗站现场观测资料,在全面比较分析的基础上,对其中应用较广泛的CFSR/CFSv2、ERA-Interim、FNL和CCMP四种风场产品在北半球海域(北太平洋、北大西洋)进行了检验评估,得出结论:1)4种资料的风速都不同程度地低估了实际观测风速;在低风速区的风向偏差较大,风速越低,偏差越多;产品资料在远岸地区比近岸地区更接近实测资料,在高纬地区的效果优于低纬地区。2)通过比较4种产品资料与浮标实测资料的风向和风速的偏差、均方根误差、误差标准差和相关系数,发现CCMP资料是4种资料中整体效果最好的一种,而CFSR/CFSv2资料是较差的一种。3)嵊泗站观测平台资料与浮标观测资料验证的结论略有差异,结果显示:FNL资料是4种资料产品中效果最好的产品,ERA-Interim资料的效果仅次于FNL,而用浮标验证效果较好的CCMP资料在嵊泗站点效果却较差,CFSR/CFSv2资料是4种资料中效果最差的。4)通过分析4种风场资料的偏差分布发现,CCMP与ERA-Interim风场资料的偏差较小,而CFSR/CFSv2与FNL风场资料的偏差较小。CCMP资料与其他3种资料的纬向风偏差在海洋上以负偏差为主,陆地以及沿岸地区的偏差较大,且分布不均匀;经向风偏差分布中,南半球的正偏差区较为明显,而北半球的负偏差区则较为明显,但偏差程度要小于纬向风偏差。     

Evaluating the efficacy of SVMs,BNs, ANNs and ANFIS in wave height prediction

Wave Height (WH) is one of the most important factors in design and operation of maritime projects. Different methods such as semi-empirical, numerical and soft computing-based approaches have been developed for WH forecasting. The soft computing-based methods have the ability to approximate nonlinear wind–wave and wave–wave interactions without a prior knowledge about them. In the present study, several soft computing-based models, namely Support Vector Machines (SVMs), Bayesian Networks (BNs), Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used for mapping wind data to wave height. The data set used for training and testing the simulation models comprises the WH and wind data gathered by National Data Buoy Center (NDBC) in Lake Superior, USA. Several statistical indices are used to evaluate the efficacy of the aforementioned methods. The results show that the ANN, ANFIS and SVM can provide acceptable predictions for wave heights, while the BNs results are unreliable.