Exploring the potential of Sentinel-3 delay Doppler altimetry for enhanced detection of coastal currents along the Northwest Atlantic shelf

In this study, we evaluate Sentinel-3A satellite synthetic aperture radar (SAR) altimeter observations along the Northwest Atlantic coast, spanning the Nova Scotian Shelf, Gulf of Maine, and Mid-Atlantic Bight. Comparisons are made of altimeter sea surface height (SSH) measurements from three different altimeter data processing approaches: fully-focused synthetic aperture radar (FFSAR), un-focused SAR (UFSAR), and conventional low-resolution mode (LRM). Results show that fully-focused SAR data always outperform LRM data and are comparable or slightly better than the nominal un-focused SAR product. SSH measurement noise in both SAR-mode datasets is significantly reduced compared to LRM. FFSAR SSH 20-Hz noise levels, derived from 80-Hz FFSAR data, are lower than 20-Hz UFSAR SSH with 25% noise reduction offshore of 5 km, and 55–70% within 5 km of the coast. The offshore noise improvement is most likely due to the higher native along-track data posting rate (80 Hz for FFSAR, and 20 Hz for UFSAR), while the large coastal improvement indicates an apparent FFSAR data processing advantage approaching the coastlines. FFSAR-derived geostrophic ocean current estimates exhibit the lowest bias and noise when compared to in situ buoy-measured currents. Assessment at short spatial scales of 5–20 km reveals that Sentinel-3A SAR data provide sharper and more realistic measurement of small-scale sea surface slopes associated with expected nearshore coastal currents and small-scale gyre features that are much less well resolved in conventional altimetric LRM data.     

Conditional sea surface statistics and their impact on geophysical sea surface parameters retrieved from SAR altimetry signals

In this study we present an analytical formulation of synthetic-aperture radar (SAR) altimetry signals including narrow banded nonlinear wave fields and conditional statistics between wave elevation displacements, horizontal wave slopes and vertical wave particle velocities. Considering the wave elevation displacements coskewness with respect to horizontal slopes leads to an analytical formulation of the electromagnetic bias within a SAR-mode altimeter stack. This formulation can be either parametrized by the significant wave height (SWH) and mean wave steepness, or in terms of the variance of vertical wave velocities. The effect of conditional vertical wave particle velocity variances with respect to the observed horizontal wave slopes close to nadir incidence angles leads to an effective reduction of the azimuth blurring of SAR-mode stacks. We present here a formulation of this effect by examining JONSWAP ocean wave spectra. In most cases this effect reduces the azimuth blurring by 10% to 30%. Additionally we investigate the effect of a nonlinear wave elevation displacement probability density function (PDF) on estimated geophysical parameters. We were able to show that including an elevation displacement skewness of 0.13 improves significantly the SWH consistency between altimetry and ECMWF Reanalysis v5 ERA5 results.All of these effects are validated with respect to ERA5 model data in the North East Atlantic region and in situ data located in the German Bight and Baltic Sea.The developed model can be used in both SAR and conventional altimetry retrackers.     

Exploiting the Sentinel-3 tandem phase dataset and azimuth oversampling to better characterize the sensitivity of SAR altimeter sea surface height to long ocean waves

Being the very first SAR mode altimeter tandem phase, the Sentinel-3 A/B tandem phase has provided an unprecedented opportunity to better characterize the sensitivity of SAR altimetry retrievals to high-frequency processes, such as long ocean waves. In this paper, we show that for some sea-state conditions, that are still to be precisely characterized, long ocean waves are responsible for high-frequency (spatial and temporal) coherent Sea Level Anomaly (SLA) signals. It is found that the peak wavelength corresponds to the dominant swell wavelength. Furthermore, the short time lag between S3-A and S3-B acquisitions allows performing cross-spectral analyses that reveal phase shifts consistent with waves travelling according to the wave dispersion relation. It is also demonstrated that the classical 20 Hz sampling frequency is insufficient to properly sample most swell-induced SLA signals and that aliasing can generate errors over the entire frequency spectrum, including at long wavelengths. These results advocate for the use of azimuth oversampling (40 Hz or 80 Hz). Low-pass filtering should be applied prior to any down-sampling to 20 Hz, in order to prevent long-wavelength errors induced by spectral leakage.     

Validity assessment of SAMOSA retracking for fully-focused SAR altimeter waveforms

We demonstrate in this work how we can take advantage of known unfocused SAR (UF-SAR) retracking methods (e.g. the physical SAMOSA model) for retracking of fully-focused SAR (FF-SAR) waveforms. Our insights are an important step towards consistent observations of sea surface height, significant wave height and backscatter coefficient (wind speed) with both UF-SAR and FF-SAR. This is of particular interest for SAR altimetry in the coastal zone, since coastal clutter may be filtered out more efficiently in the high-resolution FF-SAR waveform data, which has the potential to improve data quality. We implemented a multi-mission FF-SAR altimetry processor for Sentinel-3 (S3) and Sentinel-6 Michael Freilich (S6), using a back-projection algorithm, and analysed ocean waveform statistics compared to multilooked UF-SAR. We find for Sentinel-3 that the averaged power waveforms of UF-SAR and FF-SAR over ocean are virtually identical, while for Sentinel-6 the FF-SAR power waveforms better resemble the UF-SAR zero-Doppler beam. We can explain and model the similarities and differences in the data via theoretical considerations of the waveform integrals. These findings suggest to use the existing UF-SAR SAMOSA model for retracking S3 FF-SAR waveforms but the SAMOSA zero-Doppler beam model for S6 FF-SAR waveforms, instead. Testing the outlined approach over short track segments, we obtain range biases between UF-SAR and FF-SAR lower than 2 mm and significant wave height biases lower than 5 cm.     

An improved,near real time water vapor path delay correction of Cryosat-2 sea surface height measurements

This paper presents improvements of a method (Stum et al., 2011) aimed at computing the water vapor path delay correction of altimeter sea surface height, using total precipitable water measurements from scanning microwave radiometers. The main interest of this improved method is for the Cryosat-2 mission over the ocean. Focus is made on the applicability of the method in near real time. An experiment to produce an operational path delay correction for Jason-2 and Cryosat-2 Interim Geophysical Data Records (IGDR) has been set up. Results confirm that the new correction, although less accurate than the one attainable with an embarked radiometer, improves the Cryosat-2 sea surface height accuracy.     

Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.     

First quality assessment of the Cryosat-2 altimetric system over ocean

This paper presents the results of a Calval analysis performed for the Cryosat-2 mission over ocean. The data set used in this analysis consists of products generated by the Cryosat-2 Processor Prototype developed by CNES (Center National d’Etudes Spatiales). This data set has been analysed focusing on LRM (Low Resolution Mode) mode only. One major objective of this paper is to illustrate the potential of Cryosat-2 data over ocean, mainly for waves and Sea Level Anomaly applications. All the results indicate very good performances of the SIRAL (SAR/Interferometric Altimeter) altimeter over ocean. Crossover standard deviation is close to 6.5 cm over the analysed period (3 months) which is close to the Jason-2 and ENVISAT performance. All these results confirm that Cryosat’s altimeter can provide data almost as valuable as other flying altimetric missions, and that it has the potential to contribute to oceanography (e.g. multi-mission climate record, mesoscale monitoring in near real time) and to geodesy (e.g. mean sea surface, bathymetry).     

An improved focusing method for geosynchronous SAR

More and more attention is paid to Geosynchronous Orbit (GEO) Synthetic Aperture Radar (SAR) in recent years due to its fine temporal resolution and large coverage, so that GEO SAR will play an important role in monitoring natural disasters, but its imaging is more difficult compared to lower Earth orbit (LEO) SAR because of the increase of orbit height. This paper mainly studies the coverage property and focusing method in GEO SAR. As is known to us, the coverage of a GEO SAR satellite can reach 1/3 of the whole Earth, and the revisiting time can reduce to 2 h, which will remarkably improve the capability in ocean applications, earth dynamics and natural hazards management and so on. Compared with the imaging in LEO SAR, a problem in GEO SAR is that the linear trajectory model can bring a big error due to the long synthetic aperture time, so that the classical imaging algorithms in LEO SAR cannot be directly applied in GEO SAR. Using the Norm method and Taylor expansion method, this paper gains an accurate slant range model, which can resolve the big error of the linear trajectory at perigee and collapse of the linear trajectory at apogee. Furthermore, this paper deduces a novel imaging algorithm for GEO SAR by means of series reversion, which realizes the focusing on large scene under the synthetic aperture time of 100 s. Finally, the simulation results at apogee and perigee prove the correction of the slant range model and imaging algorithm.     

An improved altimeter-derived gravity anomaly from shipborne gravity based on the mean sea surface height constraint factors method

Coastal marine gravity modeling faces challenges due to the degradation of the quality and poor coverage of altimeter data in coastal regions. The effective fusion of shipborne gravity data and altimeter-derived marine gravity data can make shipborne gravity data more useful for the accurate estimation of altimeter-derived coastal marine gravity. A mean sea surface height constraint factor (MSSHCF) method based on the ordinary kriging method and the remove-restore technique is proposed to fuse altimeter-derived gravity model with shipborne gravity data. In this method, all data are standardized during the interpolation process to reduce the error and mean sea surface as a vertical variable is added to the semi-variance function in ordinary kriging to obtain the residual shipborne gravity as corrected data source. The coastal marine gravity models V2.1 and V3.1 which fused altimeter-derived gravity data with shipborne gravity data and V1.1 without shipborne gravity data at a spatial resolution of 1′×1′ can be obtained. Validation experiments show that the accuracy of the gravity model V3.1 obtained by the MSSHCF method more closely agrees with the validated gravity model DTU17 and SS V31 than the model V2.1 obtained by the ordinary kriging interpolation method and the V1.1 model. Our results were validated against shipborne gravity data; the accuracy of model V3.1 was 4.95 % higher than the model V1.1 in South China Sea area A and 2.48 % higher in South China Sea area B. Meanwhile, the accuracy of model V3.1 was 2.07 % higher than model V2.1 in South China Sea area A and 2.42 % higher in South China Sea area B. The effects of distance from the coast and sea depth on the marine gravity model were also evaluated. The results show that the gravity model V3.1 has higher accuracy with the change in ocean distance and depth than the V2.1 and V1.1 gravity models. Thus, our study shows that the MSSHCF method effectively refines coastal altimeter-derived gravity using shipborne gravity data.     

Sea state parameters retrieval from cross-polarization Gaofen-3 SAR data

Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) acquired in wave mode (WV) and quad-polarization stripmap (QPS) mode default operates in quad-polarization (vertical–vertical (VV), vertical-horizontal (VH), horizontal-horizontal (HH) and horizontal-vertical (HV)) modes. To date, more than GF-3 SAR vignettes following about 110 orbits acquired in WV and QPS mode have been recorded during the mission from April 2016 to December 2017. In the vignettes, ocean surface waves signatures, that are wave-look patterns, are visible in cross-polarization (basically VH). These vignettes are collocated with surface sea state parameters simulated from numerical WAVEWATCH-III (WW3) wave model using a 0.1° grid. There are 11,269 matchups available for studying the relation between sea state parameters and SAR-derived parameters in VH-polarization. A well-known empirical CWAVE model, herein renamed as CPCWAVE_GF3, is adopted for sea state parameter retrieval from GF-3 SAR vignettes with the SAR parameters in the cross-polarization channel. The method yielded a significant correlation coefficient (COR) of 0.79 for wave height (SWH) and 0.72 for second-order cross-zero mean wave period (MWP). Validation against 76 moored buoys resulted in a 0.49 m RMSE of SWH with a 0.21 m scatter index (SI) and validation against 71 moored buoys resulted in a 1.01 s RMSE of MWP with a 0.13 s SI. The comparison of SWH with 116 footprints from the altimeter of Jason-2 also shows a 0.46 m RMSE of SWH with a 0.19 m SI. Our work demonstrates the feasibility of wave retrieval from GF-3 SAR using cross-polarization channels parameters.     

Mapping mean lake surface from satellite altimetry and GPS kinematic surveys

Lake water height is a key variable in water cycle and climate change studies, which is achievable using satellite altimetry constellation. A method based on data processing of altimetry from several satellites has been developed to interpolate mean lake surface (MLS) over a set of 22 big lakes distributed on the Earth. It has been applied on nadir radar altimeters in Low Resolution Mode (LRM: Jason-3, Saral/AltiKa, CryoSat-2) in Synthetic Aperture Radar (SAR) mode (Sentinel-3A), and in SAR interferometric (SARin) mode (CryoSat-2), and on laser altimetry (ICESat). Validation of the method has been performed using a set of kinematic GPS height profiles from 18 field campaigns over the lake Issykkul, by comparison of altimetry’s height at crossover points for the other lakes and using the laser altimetry on ICESat-2 mission. The precision reached ranges from 3 to 7 cm RMS (Root Mean Square) depending on the lakes. Currently, lake water level inferred from satellite altimetry is provided with respect to an ellipsoid. Ellipsoidal heights are converted into orthométric heights using geoid models interpolated along the satellite tracks. These global geoid models were inferred from geodetic satellite missions coupled with absolute and regional anomaly gravity data sets spread over the Earth. However, the spatial resolution of the current geoid models does not allow capturing short wavelength undulations that may reach decimeters in mountaineering regions or for rift lakes (Baikal, Issykkul, Malawi, Tanganika). We interpolate in this work the geoid height anomalies with three recent geoid models, the EGM2008, XGM2016 and EIGEN-6C4d, and compare them with the Mean Surface of 22 lakes calculated using satellite altimetry. Assuming that MLS mimics the local undulations of the geoid, our study shows that over a large set of lakes (in East Africa, Andean mountain and Central Asia), short wavelength undulations of the geoid in poorly sampled areas can be derived using satellite altimetry. The models used in this study present very similar geographical patterns when compared to MLS. The precision of the models largely depends on the location of the lakes and is about 18 cm, in average over the Earth. MLS can serve as a validation dataset for any future geoid model. It will also be useful for validation of the future mission SWOT (Surface Water and Ocean Topography) which will measure and map water heights over the lakes with a high horizontal resolution of 250 by 250 m.     

Preliminary gravity recovery from CryoSat-2 data in the Baffin Bay

A number of geophysical phenomenons in the open ocean are still unresolved by conventional altimetry, but could be resolved through the potential improvements offered by Synthetic Aperture Radar (SAR), also called Delay-Doppler, altimetry. The SAR altimeter offers the following benefits with respect to conventional satellite altimetry: factor of 20 improvements in the along-track resolution, the along-track footprint length which does not vary with wave height (sea state), and improved precision in sea surface height measurements or sea surface slope measurements.     

An improved real-time cycle slip correction algorithm based on Doppler-aided signals for BDS triple-frequency measurements

Doppler, which is an instantaneous GNSS observable signal, has been proven effective in determining velocity and acceleration due to its high availability and accuracy. We propose a real-time triple-frequency cycle slip correction (CSC) method based on Doppler-aided signals because Doppler shift is time-independent and immune to cycle slips. When the sampling interval is less than 1 s, cycle slips on triple-frequency can be detected and repaired using pure Doppler data with high reliability; however, this method cannot be used when the sampling interval exceeds 1 s because the integral cumulative error of Doppler increases significantly. For such cases, a modified triple-frequency CSC approach has been developed based on the raw phase and smoothed code data that was refined using the Doppler signal. To suppress the effect of the integral Doppler error, a balance factor is introduced to adjust the contributions of the raw code and Doppler observables. After the refinement of the GNSS data, three independent combinations need be selected to detect and repair cycle slips with triple-frequency observations. Four constrained criteria have been proposed to select optimal combinations that can reduce the residual ionospheric delay (RID) and measurement noise to a low level. Finally, experiments were carried out to test the performance of the new method using real triple-frequency BDS observations (GPST: 3:15:00–5:55:00, March 23, 2018). The results show that pure Doppler can detect and repair cycle slips effectively with small intervals, and modified Hatch-Melbourne-Wübbena (HMW) method based on Doppler-aided signals can achieve 99.7% success rate in cycle slip correction with large intervals (up to 30 s).     

Regional in situ validation of satellite altimeters: Calibration and cross-calibration results at the Corsican sites

The in situ validation of the satellite altimeter sea surface heights is generally performed either at a few local points directly flown over by the satellites or using the global tide gauge network. A regional in situ calibration method was developed by NOVELTIS in order to monitor the altimeter data quality in a perimeter of several hundred kilometres around a given in situ calibration site. The primary advantage of this technique is its applicability not only for missions flying over dedicated sites but also for missions on interleaved or non repetitive orbits. This article presents the altimeter bias estimates obtained with this method at the Corsican calibration site, for the Jason-1 mission on its nominal and interleaved orbits as well as for the Jason-2 and Envisat missions. The various regional bias estimates (8.2 cm and 7.4 cm for Jason-1 respectively on the nominal and interleaved orbits in Senetosa, 16.4 cm for Jason-2 in Senetosa and 47.0 cm for Envisat in Ajaccio, with an accuracy between 2.5 cm and 4 cm depending on the mission) are compared with the results obtained by the other in situ calibration teams. This comparison demonstrates the coherency at the centimetre level, the stability and the generic character of the method, which would also be of benefit to the new and future altimeter missions such as Cryosat-2, SARAL/AltiKa, Sentinel-3, Jason-3, Jason-CS.     

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.     

A comparative analysis of SLR,MLR, ANN,XGBoost and CNN for crop height estimation of sunflower using Sentinel-1 and Sentinel-2

Sustainable monitoring and determining the biophysical characteristics of crops is of global importance due to the increase in demand for food. In this context, remote sensing data provide valuable information on crops. This study investigates the relationship between the variables determined from both Synthetic Aperture Radar (SAR) and optical images and crop height. For this purpose, backscatter (σVH, σVV, σVH / σVV) and coherence (?VH, ?VV) of multi-temporal dual-polarized Sentinel-1 and vegetation indices of multi-temporal Sentinel-2 data are analyzed. Two indices, namely, Normalized Difference Vegetation Index (NDVI) and NDVI with the red-edge band (NDVIred), are interpreted to identify the contribution of the red-edge band over the near-infrared band. The Zile District of Tokat province in Turkey where dominantly sunflower cultivation is carried out, was selected as the study area. In the analysis of the data, Simple Linear Regression (SLR), Multiple Linear Regression (MLR), Artificial Neural Network (ANN), EXtreme Gradient Boosting (XGBoost), and Convolutional Neural Network (CNN) were used. In the results of the study, ANN showed the lowest RMSE = 3.083 cm (RMSE%= 11.284) in the stem elongation period. The CNN followed the lowest RMSE for the Inflorescence development and flowering stages 19.223 cm (RMSE%=15.458) and 8.731 cm (RMSE%=5.821), respectively. In the ripening period, XGBoost achieved the lowest RMSE = 8.731 cm (RMSE%=6.091). All the best models in four methods were created using common variables of σVH, σVV, ?VH, ?VV and NDVIred, except ANN which exclude coherence variables. The results concluded that NDVIred contributed more than NDVI which is widely interpreted in previous studies.     

An Integer Precise Point Positioning technique for sea surface observations using a GPS buoy

GPS data dedicated to sea surface observation are usually processed using differential techniques. Unfortunately, the precision of resulting kinematic positions is baseline-length dependent. So, high precision sea surface observations using differential GPS techniques are limited to coasts, lakes, and rivers. Recent improvements in GPS satellite products (orbits, clocks, and phase biases) make phase ambiguity fixing at the zero difference level achievable and opens up the observation of the sea surface without geographical constraints. This paper recalls the concept of the Integer Precise Point Positioning technique and discusses the precision of GPS buoy positioning. A sequential version of the GINS software has been implemented to achieve single epoch GPS positioning. We used 1 Hz data from a two week GPS campaign conducted in the Kerguelen Islands. A GPS buoy has been moored close to a radar gauge and 90 m away from a permanent GPS station. This infrastructure offers the opportunity to compare both kinematic Integer Precise Point Positioning and classical differential GPS positioning techniques to in situ radar gauge data. We found that Precise Point Positioning results are not significantly biased with respect to radar gauge data and that horizontal time series are consistent with differential processing at the sub-centimetre precision level. Nevertheless, standard deviations of height time series with respect to radar gauge data are typically [4–5] cm. The dominant driver for noise at this level is attributed to errors in tropospheric estimates which propagate into position solutions.     

面向综合环境监测的星载SAR技术发展

针对中国微波遥感对地观测在信息维度、反演精度、观测效率和体系架构等方面存在的问题,基于国家重点研发计划“星载新体制SAR综合环境监测技术”的研究内容与成果,探讨了面向综合环境监测的若干未来星载SAR技术发展。在超大幅宽成像方面,提出分段渐变重频时序设计方案和基于最优线性无偏估计的低过采样变重频数据处理算法,实现了跨盲区大幅宽星载SAR成像;在宽幅星载SAR高灵敏度成像方面,提出中频数字波束合成高效星上实时处理架构和加权因子快速生成算法,采用16通道机载飞行试验数据验证,图像信噪比提升约112dB;在多极化星载SAR成像方面,分别提出一种简缩极化分解算法及混合全极化方位模糊抑制方法,在P/L波段机载飞行试验中得到验证;在高精度干涉SAR技术方面,提出基于改进相位补偿方案的层析SAR处理方法,利用P波段全极化层析SAR数据验证,获得优于0.9m的森林高度反演精度;在综合环境监测星座架构设计方面,针对广域地表高程、地表形变、海浪谱能量、洋流速度和生物量应用,完成品质因数达100的高分宽幅SAR卫星方案,其观测效能和观测维度较目前在轨SAR卫星有大幅提升。     

GPS-based sea level measurements to help the characterization of land contamination in coastal areas

The Corsica site has been established in 1996 to perform altimeter calibration on TOPEX/Poseidon and then on its successors Jason-1 and Jason-2. The first chosen location was under the #85 ground track that overflight the Senetosa Cape. In 2005, it was decided to develop another location close to Ajaccio, to be able to perform the calibration of Envisat and in a next future of SARAL/AltiKa that will flight over the same ground tracks. Equipped with various instruments (tide gauges, permanent GPS, GPS buoy, weather station…) the Corsica calibration site is able to quantify the altimeter Sea Surface Height bias but also to give an input on the origin of this bias (range, corrections, orbits, …). Due to the size of Corsica (not a tiny island), the altimeter measurement system (range and corrections) can be contaminated by land. The aim of this paper is to evaluate this land contamination by using GPS measurements from a fixed receiver on land and from another receiver onboard a life buoy. Concerning the altimeter land contamination, we have quantify that this effect can reach 8 mm/km and then affects the Sea Surface Height bias values already published in the framework of the Corsica calibration site by 5–8 mm for TOPEX and Jason missions. On the other hand, the radiometer measurements (wet troposphere correction) are also sensitive to land and we have been able to quantify the level of improvement of a dedicated coastal algorithm that reconciles our results with those coming from other calibration sites. Finally, we have also shown that the standard deviation of the GPS buoy sea level measurements is highly correlated (∼87%) with the Significant Wave Height derived from the altimeters and can be used to validate such parameter.