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。     

北黄海QuikSCAT 卫星风速与浮标风速的对比分析

对北黄海QuikSCAT散射计矢量风资料与黄海实测浮标站风速资料进行对比分析,结果表明:北黄海QuikSCAT卫星风速和浮标观测风速的大小基本吻合,二者平均偏差是0.26 m/s,相关系数是0.74;风向偏差较大,平均偏差是117.52°。根据卫星风速和浮标风速的对比分析结果,提出了修正方案。修正后的QuikSCAT风向与实测浮标站风向的平均偏差显著提高到20.44°。该修正方案实施简单,修正效果显著,为更准确地使用卫星资料提供了保证。     

基于海岛站探空资料的 WindSat海洋大气可降水量产品检验

利用时空匹配的15个海岛站的探空资料对WindSat 2007—2015年的海洋大气可降水量产品(total precipitable water,TPW)进行了检验,并分析了造成两者差异的原因。结果表明:WindSat反演的海洋大气可降水量产品与探空比对的一致性较好,两者平均偏差为-0.43mm,均方根误差为3.14mm,标准偏差为3.11mm,相关系数达到了0.98;WindSat在中高纬度地区反演效果较好,均方根误差在各个站点均小于3mm;在低纬度地区WindSat反演精度较差,均方根误差大于5mm。低风速对WindSat可降水反演精度影响较大;海面温度和云中液态水含量与大气可降水量产品之间无明显相关关系;WindSat反演精度随纬度降低下降明显;利用白天探空释放所得到的水汽数据存在干性偏差。     

基于极化SAR数据的海浪信息反演

基于C波段极化AIRSAR数据,采用性能较好、计算简便的圆极化法提取极化方位角,利用极化SAR数据的反演算法反演海浪参数。将反演的海浪参数与NDBC浮标测得数据进行比对,结果显示两者反演海浪参数较为一致,精度符合海浪观测要求。同时,对海岸岬角在海浪传播过程中的折射作用进行了分析,发现海浪由开放水域向近岸浅水域传播过程中受到海岸岬角折射影响较大,结果符合近岸海浪传播特征。     

中法海洋卫星散射计近海岸海面风场反演研究

中法海洋卫星散射计(CSCAT)使用扇形波束旋转扫描体制,能够以多角度测量同一海面的雷达后向散射系数,并具有空间分辨率较高的特点。这为近海岸海面风场反演提供了新的机遇。本文介绍了CSCAT近海岸海面风场处理的主要流程和关键技术。特别地,在风场反演之前,利用一种矩形窗算术平均的方法将L1B级的高分辨率条带数据组合平均到相应的风矢量单元中,从而实现近海岸风场反演的快速预处理。通过对比CSCAT、欧洲先进散射计(ASCAT)以及美国QuikSCAT的近海岸风场,发现CSCAT风场的质量在离岸40 km以外区域具有良好的一致性,而在离岸40 km以内显著恶化。分析表明,CSCAT近海岸区域风场统计特征恶化的原因可能是由潜在的海冰污染引起的。总体而言,CSCAT的近海岸风场与模式背景风场和浮标风场都具有良好的一致性。     

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°。     

西北太平洋多源微波辐射计海表温度数据交叉比对分析

海表温度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。以西北太平洋海域为研究区域,本文对2013年和2014年3个微波辐射计海表温度产品(AMSR-2,TMI和WindSat)的产品特性和Argo浮标进行了真实性检验,并对3个传感器数据进行了交叉比对分析,具体涉及海表温度分布、温度梯度分布、观测点分布、匹配点分布、平均偏差分布、均方根误差分布、统计分析结果的逐月演变和海表温度误差棒分析。结果表明,3个微波辐射计在空间尺度上都能比较一致地反映西北太平洋海域的海表温度变化趋势。但遥感数据与浮标数据却存在季节性变化和昼夜差异,其中冬季微波数据与浮标数据的平均偏差和均方根误差较小,降轨数据与浮标数据的结果更接近。AMSR-2的海表温度数据质量比TMI和WindSat的海表温度数据更接近Argo数据。相比于WindSat和TMI,AMSR-2和TMI的海表温度数据质量更为接近,但是由于受到近岸陆地信号干扰,AMSR-2和TMI离岸100 km以内海域的数据应当慎用。     

基于AMSR2微波辐射计的近海面气温反演算法研究

基于多元线性回归方法,利用2013-01-06的AMSR2辐射计亮温数据和红外-微波融合SST数据产品,开展了近海面气温反演算法研究,并用TAO,RAMA和PIRATA等浮标实测数据对近海面气温的反演结果进行检验。近海面气温反演结果误差情况:均方根误差为0.66℃,偏差为0.02℃,相关系数R为0.91,该误差结果表明所建立近海面气温反演算法较好的反映在60°S~60°N纬度范围内的近海面气温分布情况;同时为进一步确定不同纬度近海面气温反演的误差分布,将近海面气温反演结果与ECMWF再分析数据进行了对比分析,结果表明,从赤道起算,纬度每升高或降低1°,反演均方根误差约增大0.1℃。     

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.     

CYGNSS卫星风速产品的精度检验

针对 CYGNSS卫星风速产品的适用性问题,以美国国家数据浮标中心(NDBC)的实测风速与美国国家飓风中心(NHC)的最佳路径风速为参照,选取美国西南部海域为研究区,通过数据匹配和对比分析,评估了CYGNSS不同模型估算风速产品的精度。结果表明,CYGNSS FDS模型估算的中、低风速产品与NDBC浮标实测风速具有较好的一致性,CYGNSS风速与浮标风速的差异在春夏季稍高、秋冬季略低;CYGNSS YSLF模型估算的高风速产品与NHC最大风速存在较大差异,CYGNSS风速低于NHC最大风速;对于CYGNSS两种模型估算的风速产品,利用遥感观测量NBRCS反演出的风速都比LES反演出的风速具有更好的精度。总体而言,本研究验证了CYGNSS风速产品的真实有效性,对提高海洋数值预报能力具有一定的意义。     

基于浮标实测数据的WindSat海洋反演产品精度分析

To evaluate the ocean surface wind vector and the sea surface temperature obtained from Wind Sat, we compare these quantities over the time period from January 2004 to December 2013 with moored buoy measurements. The mean bias between the Wind Sat wind speed and the buoy wind speed is low for the low frequency wind speed product(WSPD_LF), ranging from –0.07 to 0.08 m/s in different selected areas. The overall RMS error is 0.98 m/s for WSPD_LF, ranging from 0.82 to 1.16 m/s in different selected regions. The wind speed retrieval result in the tropical Ocean is better than that of the coastal and offshore waters of the United States. In addition, the wind speed retrieval accuracy of WSPD_LF is better than that of the medium frequency wind speed product. The crosstalk analysis indicates that the Wind Sat wind speed retrieval contains some cross influences from the other geophysical parameters, such as sea surface temperature, water vapor and cloud liquid water. The mean bias between the Wind Sat wind direction and the buoy wind direction ranges from –0.46° to 1.19° in different selected regions. The overall RMS error is 19.59° when the wind speed is greater than 6 m/s. Measurements of the tropical ocean region have a better accuracy than those of the US west and east coasts. Very good agreement is obtained between sea surface temperatures of Wind Sat and buoy measurements in the tropical Pacific Ocean; the overall RMS error is only 0.36°C, and the retrieval accuracy of the low latitudes is better than that of the middle and high latitudes.     

基于浮标、NCEP2及OAFlux产品的新海表感热和潜热通量对比分析

New satellite-derived latent and sensible heat fluxes are performed by using Wind Sat wind speed, Wind Sat sea surface temperature, the European Centre for Medium-range Weather Forecasting(ECMWF) air humidity, and ECMWF air temperature from 2004 to 2014. The 55 moored buoys are used to validate them by using the 30 min and 25 km collocation window. Furthermore, the objectively analyzed air-sea heat fluxes(OAFlux) products and the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis 2(NCEP2) products are also used for global comparisons. The mean biases of sensible and latent heat fluxes between Wind Sat flux results and buoy flux data are –0.39 and –8.09 W/m~2, respectively. In addition, the rootmean-square(RMS) errors of the sensible and latent heat fluxes between them are 5.53 and 24.69 W/m~2,respectively. The RMS errors of sensible and latent heat fluxes are observed to gradually increase with an increasing buoy wind speed. The difference shows different characteristics with an increasing sea surface temperature, air humidity, and air temperature. The zonal average latent fluxes have some high regions which are mainly located in the trade wind zones where strong winds carry dry air in January, and the maximum value centers are found in the eastern waters of Japan and on the US east coast. Overall, the seasonal variability is pronounced in the Indian Ocean, the Pacific Ocean, and the Atlantic Ocean. The three sensible and latent heat fluxes have similar latitudinal dependencies; however, some differences are found in some local regions.     

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.     

Evaluation of ENVISAT ASAR data for sea surface wind retrieval in Hong Kong coastal waters of China

The C-band wind speed retrieval models, CMOD4, CMOD - IFR2, and CMOD5 were applied to retrieval of sea surface wind speeds from ENVISAT （European environmental satellite） ASAR （advanced synthetic aperture radar） data in the coastal waters near Hong Kong during a period from October 2005 to July 2007. The retrieved wind speeds are evaluated by comparing with buoy measurements and the QuikSCAT （quick scatterometer） wind products. The results show that the CMOD4 model gives the best performance at wind speeds lower than 15 m/s. The correlation coefficients with buoy and QuikSCAT winds are 0.781 and 0.896, respectively. The root mean square errors are the same 1.74 m/s. Namely, the CMOD4 model is the best one for sea surface wind speed retrieval from ASAR data in the coastal waters near Hong Kong.     

Comparison of Near Coastal Significant Wave Height Measurements from SARAL/AltiKa with Wave Rider Buoys in the Indian Region

Significant Wave Height (SWH) measurement data from the AltiKa Radar Altimeter (RA) for the first 13 cycles of satellite coverage are compared with the SWH from Wave Rider Buoys (WRB) located at nine stations along the Indian coast to assess the performance of the altimeter over the coastal region. AltiKa SWH observations within a 30-minute interval and 50 km distance from WRBs are found to be over estimated by 6%, the Root Mean Square Error (RMSE) is 0.36 m, the Scatter Index (SI) is 26%, and the correlation coefficient (r) is 0.91. Relaxing the distance criteria by 50 km leads to increase in RMSE and deterioration of r to 0.89. There is a marked difference in the statistics on the comparison pairs pooled separately for the buoys near west and east coasts, with the latter showing RMSE error 26% more than the former. The method of Cressman weights adopted to correct for the errors arising out of the temporal and spatial differences in altimeter and buoy data comparison pairs resulted in reduction of RMSE by 5% and 25%, respectively, for the 30-minute and 50 km criteria and 4% and 56% for the 30-minute and 100 km criteria.     

海浪成长状态对TOPEX/Poseidon高度计风速反演的影响

以墨西哥湾同步高度计、浮标资料为例,研究了海浪成长状态对高度计风速反演的影响。同步的高度计风速和浮标风速比较显示,在墨西哥湾地区,海浪成长状态对高度计风速反演有较大影响。在考虑海浪成长状态影响的条件下,利用谱模型反演高度计风速,取得了较好的效果。与目前TOPEX/Poseidon高度计风速反演业务化算法相比,在海浪未充分成长条件下,考虑海浪成长状态影响后,根据谱模型反演获得的风速与浮标风速之间的均方根误差减小了30%,平均误差减小了83%。在利用谱模型算法反演高度计风速时,谱模型中的波龄因子(表示海浪成长状态)可以根据高度计测得的有效波高和风速获得,因此该方法具有广泛的适用性。     

Evaluation of Vector Winds Observed by NSCAT in the Seas around Japan

In order to validate wind vectors derived from the NASA Scatterometer (NSCAT), two NSCAT wind products of different spatial resolutions are compared with observations by buoys and research vessels in the seas around Japan. In general, the NSCAT winds agree well with the wind data from the buoys and vessels. It is shown that the root-mean-square (rms) difference between NSCAT-derived wind speeds and the buoy observations is 1.7 ms^–1, which satisfies the mission requirement of accuracy, 2 ms^–1. However, the rms difference of wind directions is slightly larger than the mission requirement, 20°. This result does not agree with those of previous studies on validation of the NSCAT-derived wind vectors using buoy observations, and is considered to be due to differences in the buoy observation systems. It is also shown that there are no significant systematic trends of the NSCAT wind speed and direction depending on the wind speed and incidence angle. Comparison with ship winds shows that the NSCAT wind speeds are lower than those observed by the research vessels by about 0.7 ms^–1 and this bias is twice as large for data observed by moving ships than by stationary ships. This result suggests that the ship winds may be influenced by errors caused by ship's motion, such as pitching and rolling.     

Evaluation of reanalysis surface wind products with quality-assured buoy wind measurements along the north coast of the South China Sea

Three archived reanalysis wind vectors at 10 m height in the wind speed range of 2–15 m/s, namely, the second version of the National Centres for Environmental Prediction(NCEP) Climate Forecast System Reanalysis(CFSv2), European Centre for Medium-Range Weather Forecasting Interim Reanalysis(ERA-I) and NCEPDepartment of Energy(DOE) Reanalysis 2(NCEP-2) products, are evaluated by a comparison with the winds measured by moored buoys in coastal regions of the South China Sea(SCS). The buoy data are first quality controlled by extensive techniques that help eliminate degraded measurements. The evaluation results reveal that the CFSv2 wind vectors are most consistent with the buoy winds(with average biases of 0.01 m/s and 1.76°). The ERA-I winds significantly underestimate the buoy wind speed(with an average bias of –1.57 m/s), while the statistical errors in the NCEP-2 wind direction have the largest magnitude. The diagnosis of the reanalysis wind errors shows the residuals of all three reanalysis wind speeds(reanalysis-buoy) decrease with increasing buoy wind speed, suggesting a narrower wind speed range than that of the observations. Moreover, wind direction errors are examined to depend on the magnitude of the wind speed and the wind speed biases. In general, the evaluation of three reanalysis wind products demonstrates that CFSv2 wind vectors are the closest to the winds along the north coast of the SCS and are sufficiently accurate to be used in numerical models.