中国南海海域Jason-1卫星回波波形分析

介绍了卫星雷达高度计回波波形形成原理,并对Jason-1卫星经过中国南海海域的回波波形进行了分析.分析结果说明在近海海域的部分回波波形受到地形严重影响,需要通过波形重构进行误差修正.     

基于波形重定技术的杭州湾平均海面高模型建立

利用AVISO提供的SARAL卫星杭州湾周年的WAVEFORM数据,通过对卫星波形分析,提出了一种新的波形重定方法,该方法在顾及波形物理机制基础上,根据各波形的特征进行重定。对重定前后的波形数据进行粗差剔除、共线平均,分析了重定后数据质量。通过交叉点平差,结合验潮站数据建立杭州湾平均海面高模型,所建模型与验潮站平均海面高差值的平均值为0.006m,标准差为0.038m。结果表明,利用本文提出的方法能显著提高卫星测高数据的精度与质量。     

卫星测高不同波形重构方法的偏差特性分析

利用我国近海4条轨迹、40个周期EnviSat-1的卫星测高波形数据,采用OCOG、Threshold、5-β参数算法以及Ocean法进行波形重构计算。根据不同轨迹和周期的波形数据,由上述四种方法重构海面高并计算相互之间的偏差及其中误差。结果表明,OCOG、Threshold、5-β参数算法与Ocean方法之间的偏差分别为88.46cm、35.90cm和25.83cm,相应的中误差分别为2.11cm、1.96cm和0.41cm,而且该偏差量对于不同的轨迹和周期是不变的。因此,只要对系统偏差进行改正,就能融合不同波形重构方法求得海面高,充分发挥不同波形重构方法在不同海区的优势,为近岸海域海平面变化,大地水准面的研究提供高精度的资料。     

GM测高数据反演中国近海及邻域精细重力场

综合对比4种波形重跟踪算法,选择改进阈值法处理Jason-1GM数据,联合波形重跟踪后的Geosat和ERS-1GM数据,沿轨2Hz重采样以提高数据空间分辨率。通过数据质量控制剔除粗差数据,考虑海表面地形的影响,基于移去-恢复法和维宁-曼齐兹公式反演了中国近海及邻近海域(0°~45°N,100°~140°E)1′×1′的精细重力场。船测数据检核表明反演结果在开阔海域精度约4mGal,近岸浅水区约10mGal,均优于DTU10和V21.1模型。     

HY-2A卫星高度计不同重跟踪方案对反演海浪有效波高的影响

本文基于Amarouche的二阶理论回波模型,导出了带有偏度系数的二阶理论回波模型;针对HY-2A卫星高度计波形特点,引入了奇异值分解滤波,并根据最大似然估计算法反演参数的不同得到6种重跟踪方案;利用其中的五参数方案处理该波形数据,获得海面散射点高度概率密度函数中偏度的合理取值为0.15;将结果分别与浮标、Jason-1和HY-2AIDR有效波高对比,分析6种方案反演有效波高的准确度,确定了MLE4_SVD(波形重跟踪之前进行滤波)对HY-2A高度计重跟踪更适合反演有效波高。     

海洋测高卫星三频体制设计及电离层误差分析

针对海洋测高卫星未来发展趋势,提出了Ku/Ka/C三频高度计进行组合测距的设想。给出了高度计相位中心至海面距离的随机误差模型,分析表明电离层延迟改正是影响海面高测量分辨率和精度的重要因素。其次利用典型电离层参数计算表明电离层2阶以上项对高度计测距的影响在毫米级以下,可忽略其影响。通过计算分析,在1 Hz采样且不滤波条件下,Ka/C组合改正电离层1阶项精度可优于3 mm,基本消除电离层的影响,测距总精度达到3.5 cm。通过Ku/C/Ka三频组合测距误差分析,三频电离层改正残余误差比双频改正更大,因此如果采用三频组合测距体制,则建议在数据处理中采取Ku/C、Ka/C组合形式改正电离层,这种体制可充分利用各频段特点,进一步提高宽阔海域、冰区、近海区域的海面测量精度和有效数据比例。     

HY-2卫星精密轨道拟合与外推的两种方法比较

分别采用切比雪夫曲线和最小二乘曲线拟合HY-2(海洋二号)卫星精密轨道,并进一步解算速度场与预报轨道。结果表明:最小二乘曲线拟合结果明显优于切比雪夫曲线拟合结果,拟合轨道精度为1～2cm,拟合速度场精度为1～2cm/s,且可以进行轨道短期预报,预报轨道精度与拟合轨道精度相当。     

基于现场观测数据的HY-2A卫星有效波高校正研究

Significant wave height(SWH) can be computed from the returning waveform of radar altimeter, this parameter is only raw estimates if it does not calibrate. But accurate calibration is important for all applications, especially for climate studies. HY-2a altimeter has been operational since April 2012 and its products are available to the scientific community. In this work, SWH data from HY-2A altimeters are calibrated against in situ buoy data from the National Data Buoy Center(NDBC), Distinguished from previous calibration studies which generally regarded buoy data as "truth", the work of calibration for HY-2A altimeter wave data against in situ buoys was applied a more sophisticated statistical technique—the total least squares(TLS) method which can take into account errors in both variables. We present calibration results for HY-2A radar altimeter measurement of wave height against NDBC buoys. In addition, cross-calibration for HY-2A and Jason-2 wave data are talked over and the result is given.     

基于HY-2B波形特征的北极海冰分类算法

海冰类型识别对进行全球气候研究至关重要,利用高度计进行北极海冰监测是目前研究的热点。本文通过利用2019年12月和2020年3月的HY-2B高度计数据,探索了国产卫星高度计在海冰类型识别中的可用性,提取了HY-2B的波形功率最大值、脉冲峰值(Pulse Peakiness,PP)、前缘宽度(Leading Edge Width,LEW)和后向散射系数(Sigma0)4个波形特征,分析了HY-2B卫星高度计精确识别薄一年冰(Thin First-year ice,TFYI)、一年冰(First-year ice,FYI)、多年冰(Multi-year ice,MYI)、冰间水道(LEAD)和开阔水域(Open Water,OW)的能力。通过与俄罗斯北极和南极研究所(Arctic and Antarctic Research Institute,AARI)冰况图产品和MODIS冰间水道产品对比发现,综合PP、LEW及Sigma0和K最近邻法(K-Nearest Neighbor,KNN),平均最高海冰分类精度可达到91.96%。     

HY-2卫星散射计热带气旋自动识别算法

对基于HY-2卫星散射计风矢量产品的热带气旋自动识别算法进行了研究。算法分为粗搜索与精搜索两部分。粗搜索利用热带气旋风场的风速与风向分布直方图特征确定搜索的阈值,快速剔除比较容易识别的非热带气旋区域。在此基础上,精搜索利用热带气旋风向的螺旋状分布特征,通过搜索目标区域内是否存在螺旋状流线的方法,确定目标区域的风向是否存在螺旋状流线特征,从而实现对热带气旋的准确自动识别。作为示例,将该方法应用到对HY-2散射计观测到的2012年6号强热带风暴"杜苏芮"的自动识别,结果表明,本文提出的算法可以从HY-2散射计风场数据中准确有效的自动识别出热带气旋。     

Retracking of Jason-1 Data

We present the results of retracking 18 cycles (15 from the Jason-TOPEX collinear period) of Jason-1 data. We used the retracking method of Rodriguez which simultaneously solves for all relevant waveform parameters using a 26 Gaussian model of the altimeter point target response. We find significant differences from the Jason-1 Project retracking in the key parameters of range and significant wave height (SWH) in the second version of the Project SGDRs. The differences from the Jason-1 data have a strong dependence on off-nadir angle and some dependence on SWH. The dependence of range on SWH is what is called sea state bias. The retracking technique also estimates surface skewness. For Jason-1 with its very clean waveforms we make the first direct estimates of the skewness effect on altimeter data. We believe that the differences found here and thus in overall sea surface height are the result of the standard project processing using a single Gaussian approximation to the Point Target Response (PTR) and not solving simultaneously for off nadir angle. We believe that the relatively large sea state bias errors estimated empirically for Jason-1 during the cal/val phase result from sensitivity of quantities, particularly SWH, in project GDRs to off nadir angle. The TOPEX-Jason-1 bias can be determined only when a full retracking of Jason-1 is done for the collinear period.     

Assessment of Radar Waveform Retracked Jason-2 Altimetry Sea Surface Heights Near Taiwan Coastal Ocean

This study focuses on assessing the accuracy of 20-Hz waveform retracked Jason-2 (J-2) altimetry sea surface heights (SSHs) in the vicinity of Taiwan by comparisons with the TOPEX/Poseidon (T/P) 10-Hz SSHs and sea level data from the Anping tide gauge. The study areas exhibit high, medium, and low amplitudes of ocean tides and contain diverse bathymetries with depths of 0–4000 m. The performance of Offset Center of Gravity (OCOG), threshold, modified threshold, and ice retrackers was examined by comparing the retracked SSHs with Earth Gravitational Model 2008 (EGM08) geoid via the use of the improvement percentages (IMPs). The results indicate that both altimetry measurements are significantly improved by waveform retracking techniques, with a maximum IMP of 46.6% for T/P and 82.0% for J-2, and the optimal achievement of retrackers is influenced by the characteristics of the study areas. In addition, valid retracked J-2 SSHs are much closer to shorelines than T/P. A comparison of retracked J-2 data with Anping tide gauge records reveals that applying the optimal retracking algorithms reduces the root mean squares of differences and increases the number of valid measurements.     

Retracking of Jason-1 Data

We present the results of retracking 18 cycles (15 from the Jason-TOPEX collinear period) of Jason-1 data. We used the retracking method of Rodriguez which simultaneously solves for all relevant waveform parameters using a 26 Gaussian model of the altimeter point target response. We find significant differences from the Jason-1 Project retracking in the key parameters of range and significant wave height (SWH) in the second version of the Project SGDRs. The differences from the Jason-1 data have a strong dependence on off-nadir angle and some dependence on SWH. The dependence of range on SWH is what is called sea state bias. The retracking technique also estimates surface skewness. For Jason-1 with its very clean waveforms we make the first direct estimates of the skewness effect on altimeter data. We believe that the differences found here and thus in overall sea surface height are the result of the standard project processing using a single Gaussian approximation to the Point Target Response (PTR) and not solving simultaneously for off nadir angle. We believe that the relatively large sea state bias errors estimated empirically for Jason-1 during the cal/val phase result from sensitivity of quantities, particularly SWH, in project GDRs to off nadir angle. The TOPEX-Jason-1 bias can be determined only when a full retracking of Jason-1 is done for the collinear period.     

The Inflection-Point Retracking Algorithm: Improved Jason-2 Sea Surface Heights in the Strait of Hormuz

In this study, a waveform retracking algorithm based on finding the inflection-point of the waveform is proposed. After two-steps pre-processing procedure, we employ this method for 145 cycles of Jason-2 data for two tracks 81 and 16 over the Strait of Hormuz. Moreover, we obtain the corrected SSH by the common empirical methods namely Offset Centre of Gravity, Beta and Threshold as well as the ALES. We compare the SSH time series from proposed algorithm with those from common empirical methods. Results are validated against three nearby tide-gauges in the case study. The correlation coefficient and RMSE between the corrected SSH and tide-gages data were computed for three distance classes from the coastline: 0～5, 5～10 and 10～15 kilometer. Our method improves the averaged RMSE of raw SSH up to 41%, 41% and 24%, for these classes over track 81 and 51%, 38% and 41% over track 16, respectively. The averaged correlation values of the proposed method indicate 33%, 11% and 2% improvement over track 81 and are 29%, 14% and 3% over track 16 for three distance groups, respectively. Our method leads to slightly better results than the successful ALES method, especially within the range of 0～5 km.     

Improving the Jason-1 Ground Retracking to Better Account for Attitude Effects

After two years of verification and validation activities of the Jason-1 altimeter data, it appears that all the mission specifications are completely fulfilled. Performances of all instruments embarked onboard the platform meet all the requirements of the mission. However, the star tracker system has shown some occasional abnormal behavior leading to mispointing angles out of the range of Jason-1 system specification which states that the altimeter antenna shall be pointed to the nadir direction with an accuracy below 0.2 degree (3 sigma). This article discusses the platform attitude angle and its consequences on the altimetric estimates. We propose improvements of the Jason-1 retracking process to better account for attitude effects.

The first star tracker anomalies for the Jason-1 mission were detected in April 2002. The Poseidon-2 algorithms were specified assuming an antenna off-nadir angle smaller than 0.3 degree. For higher values, the current method to estimate the ocean parameters is known to be inaccurate. Thus, the algorithm has to be reviewed, and more specifically, the present altimeter echo model has to be modified to meet the desired instrument performance.

Therefore, we derive a second order analytical model of the altimeter echo to take into account attitude angles up to 0.8 degree, and consequently, we adapt the retracking algorithm. This new model is tested on theoretical simulated data using a maximum likelihood estimation. Biases and noise performance characteristics are computed for the different estimated parameters. They are compared to the ones obtained with the current algorithm. This new method provides highly improved estimations for high attitude angles. It is statistically validated on real data by applying it on several cycles of Poseidon-2 raw measurements. The results are found to be consistent with those obtained from simulations. They also fully agree with the TOPEX estimates when flying along the same ground track. Finally, the estimates are also in agreement with the ones available in the current I/GDR (Intermediate Geophysical Data Record) products when mispointing lies in the mission specifications.     

Improving the Jason-1 Ground Retracking to Better Account for Attitude Effects

After two years of verification and validation activities of the Jason-1 altimeter data, it appears that all the mission specifications are completely fulfilled. Performances of all instruments embarked onboard the platform meet all the requirements of the mission. However, the star tracker system has shown some occasional abnormal behavior leading to mispointing angles out of the range of Jason-1 system specification which states that the altimeter antenna shall be pointed to the nadir direction with an accuracy below 0.2 degree (3 sigma). This article discusses the platform attitude angle and its consequences on the altimetric estimates. We propose improvements of the Jason-1 retracking process to better account for attitude effects.

The first star tracker anomalies for the Jason-1 mission were detected in April 2002. The Poseidon-2 algorithms were specified assuming an antenna off-nadir angle smaller than 0.3 degree. For higher values, the current method to estimate the ocean parameters is known to be inaccurate. Thus, the algorithm has to be reviewed, and more specifically, the present altimeter echo model has to be modified to meet the desired instrument performance.

Therefore, we derive a second order analytical model of the altimeter echo to take into account attitude angles up to 0.8 degree, and consequently, we adapt the retracking algorithm. This new model is tested on theoretical simulated data using a maximum likelihood estimation. Biases and noise performance characteristics are computed for the different estimated parameters. They are compared to the ones obtained with the current algorithm. This new method provides highly improved estimations for high attitude angles. It is statistically validated on real data by applying it on several cycles of Poseidon-2 raw measurements. The results are found to be consistent with those obtained from simulations. They also fully agree with the TOPEX estimates when flying along the same ground track. Finally, the estimates are also in agreement with the ones available in the current I/GDR (Intermediate Geophysical Data Record) products when mispointing lies in the mission specifications.     

Retracking of SARAL/AltiKa Radar Altimetry Waveforms for Optimal Gravity Field Recovery

The accuracy of the marine gravity field derived from satellite altimetry depends on dense track spacing as well as high range precision. Here, we investigate the range precision that can be achieved using a new shorter wavelength Ka-band altimeter AltiKa aboard the SARAL spacecraft. We agree with a previous study that found that the range precision given in the SARAL/AltiKa Geophysical Data Records is more precise than that of Ku-band altimeter by a factor of two. Moreover, we show that two-pass retracking can further improve the range precision by a factor of 1.7 with respect to the 40 Hz-retracked data (item of range_40 hz) provided in the Geophysical Data Records. The important conclusion is that a dedicated Ka-band altimeter-mapping mission could substantially improve the global accuracy of the marine gravity field with complete coverage and a track spacing of <6 km achievable in ～1.3 years. This would reveal thousands of uncharted seamounts on the ocean floor as well as important tectonic features such as microplates and abyssal hill fabric.     

基于Jason-2校正辐射计的降雨率估计算法研究

采用Jason-2校正辐射计的亮温数据与GPM Ku波段测雨雷达的降雨率数据,开展基于Jason-2校正辐射计的降雨率估计算法研究。为避免波束填充效应,对Ku波段测雨雷达降雨率数据进行网格化处理,分别构建3×3,5×5及7×7网格的建模数据集和验证数据集,通过建模数据集建立了3种基于校正辐射计的降雨率估计算法研究,并通过验证数据集进行检验。结果表明:对GPM Ku波段测雨雷达的降雨数据进行3×3,5×5及7×7的网格化处理,可以在降雨率估计算法研究时有效避免波束填充效应,7×7网格化处理方法效果最优。对3种不同的算法比对,发现利用校正辐射计3个通道亮温信息的线性组合形式估计降雨率效果最优,相对偏差可达42.33%。     

Extension of Satellite Altimetry Jason-2 Sea Level Anomalies Towards the Red Sea Coast Using Polynomial Harmonic Techniques

Satellite altimetry data are facing big challenges near the coasts. These challenges arise due to the fundamental difficulties of correction and land contamination in the foot print, which result in rejection of these data near the coast. Several studies have been carried out to extend these data towards the coast. Over the Red Sea, altimetry data consist of gaps, which extend to about 30–50 km from the coast. Two methods are used for processing and extending Jason-2 satellite altimetry sea level anomalies (SLAs) towards the Red Sea coast; Fourier Series Model (FSM), and the polynomial sum of sine model (SSM). FSM model technique uses Fourier series and statistical analysis reflects strong relationship with both the observation and AVISO data, with strong and positive correlation. The second prediction technique, SSM model, depends on the polynomial sum of sine, and does not reflect any relationship with the observations and AVISO data close to the coast and the correlation coefficient (CC) is weak and negative. The FSM model output results in SLA data significantly better and more accurate than the SSM model output.