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Satellite altimetry has become an important discipline in the development of sea-state forecasting or more generally in operational oceanography. Météo-France Marine and Oceanography Division is much involved in altimetry, in which it is also one of the main operational customers. Sea-state forecasts are produced every day with the help of numerical models assimilating Fast Delivery Product altimeter data from ESA ERS-2 satellite, available in real-time (3–5 h). These forecasts are transmitted to seamen as part of safety mission of persons and properties, or specific assistance for particular operations. With the launch of ENVISAT (from ESA, launched on 1 March 2002, to take over the ERS mission) and JASON-1 (from CNES/NASA, launched on 7 December 2001, successor of TOPEX/Poseidon), we have an unprecedented opportunity of improved coverage with the availability in quasi-real-time of data from several altimeters. The objective of this study is to evaluate the impact of using multisources of altimeter data in real-time, to improve wave model analyses and forecasts, at global scale. Since July 2003, Météo-France injects the wind/wave JASON-1 Operational Sensor Data Record on the WMO Global Transmitting System, making them available in near real-time to the international meteorological community. Similarly, fast delivery altimeter data of ENVISAT will improve coverage and contribute to the constant progress of marine meteorology. For this purpose, significant wave height time series were generated using the Wave Model WAM and the assimilation of altimeter wave heights from two satellites ERS-2 and JASON-1. The results were then compared to Geosat Follow-On (GFO, U.S. Navy Satellite) and moored buoy wave data. It is shown that the impact of data assimilation, when two (ERS-2 and JASON-1) or three (ERS-2 with JASON-1 and GFO) sources of data are used instead of one (ERS-2), in term of significant wave height, is larger in wave model analyses but smaller in wave model forecasts. However, there is no improvement in terms of wave periods, both in the analysis and forecast periods. 相似文献
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随着卫星高度计资料的不断丰富,通过对卫星高度计所得潮汐调和常数进行插值或拟合得到潮汐同潮图成为可能。本文拟对T/P(TOPEX/POSEIDON)、Jason-1和Jason-2卫星高度计数据进行分析,得到南海区域星下观测点处四个主要分潮(M2、S2、K1和O1分潮)的调和常数,进而利用双调和样条插值方法对其进行插值,获取南海同潮图。首先,以1992～2016年T/P和Jason卫星高度计所得海面高度数据为基础,利用调和分析方法计算了南海星下观测点处M2、S2、K1和O1四个主要分潮的调和常数,并与40个验潮站数据进行了对比,最大矢量均差为4.99cm,说明分析所得调和常数与利用验潮站资料提取的调和常数的误差较小。进而采用双调和样条插值方法对星下点调和常数进行插值,得到了南海四个主要分潮的同潮图,所得结果与全球潮汐模型TPXO7.2模式结果的矢量均差分别为4.69、2.46、3.13和2.42 cm,与141个验潮站处观测结果的矢量均差分别为22.59、10.26、10.24和8.51 cm。此外,插值所得四个主要分潮的无潮点位置与前人研究结果相近。上述实验结果表明:利用双调和样条插值方法对卫星高度计所得调和常数进行插值能够获取较为准确的同潮图。 相似文献
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Sirsendu Chatterjee Rudradeb Bhattacharyya Laju Michael Kolluru Sree Krishna Tapan Jyoti Majumdar 《Marine Geodesy》2007,30(3):197-216
Geoid and gravity anomalies derived from satellite altimetry are gradually gaining importance in marine geoscientific investigations. Keeping this in mind, we have validated ERS-1 (168 day repeat) altimeter data and very high-resolution free-air gravity data sets generated from Seasat, Geosat GM, ERS-1 and TOPEX/POSEIDON altimeters data with in-situ shipborne gravity data of both the Bay of Bengal and the Arabian Sea regions for the purpose of determining the consistencies and deviations. The RMS errors between high resolution satellite and ship gravity data vary from 2.7 to 6.0 mGal, while with ERS-1 data base the errors are as high as 16.5 mGal. We also have generated high resolution satellite gravity maps of different regions over the Indian offshore, which eventually have become much more accurate in extracting finer geological structures like 85° E Ridge, Swatch of no ground, Bombay High in comparison with ERS-1satellite-derived gravity maps. Results from the signal processing related studies over two specific profiles in the eastern and western offshore also clearly show the advantage of high resolution satellite gravity compared to the ERS-1 derived gravity with reference to ship gravity data. 相似文献
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The Jason-1 satellite altimeter mission represents a first step towards operational oceanography from satellite altimeter missions. An operational data product, the Operational Sensor Data Record (OSDR), provides measurements from the on-board altimeter and radiometer within 3-5 h of real time. This data product is a wind and wave product that is aimed towards near-real-time meteorological applications. A higher accuracy and more detailed data product, the Interim Geophysical Data Record (IGDR), that is better suited to detailed scientific studies of ocean topography, is available no sooner than 2-3 days from real time. The measurements reported on the OSDR primarily differ from those on the IGDR in that the OSDR reports measurements derived from on-board processing of the altimeter waveforms, while ground retracking of the waveforms is performed for the IGDR. The altimeter-derived measurements on the OSDR are validated through a statistical evaluation of the differences between data on the OSDR and IGDR. In doing so, the impact of ground retracking of the altimeter waveforms is also illustrated. 相似文献
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Michael P. Stewart Will E. Featherstone Jonathan F. Kirby Mark Dumville 《Marine Geodesy》2013,36(4):319-330
Sea surface height profiles derived from 2‐year, repeat track, Geosat altimeter data have been compared with a regional gravimetric geoid in the western North Sea, computed using a geopotential model and terrestrial gravity data. The comparison encompasses 18 Geosat profiles covering a 750 × 850 km area of the North Sea. After a second‐order polynomial was used to model the long‐wavelength differences which cannot be clearly separated over an area of this size, results show agreement to better than ±3 cm for wavelengths between approximately 20 and 750 km. In regions where terrestrial gravity data were not available to improve the geoid, similar comparisons with the OSU91A geopotential model alone show differences of up to ±6 cm. This illustrates the importance of incorporating local gravity data in regional geoid computations, and partly validates the regional gravimetric geoid solution and Geosat sea surface profiles in the western North Sea. It is concluded that, in marine areas where the sea surface topography is known to be small in magnitude, Geosat sea surface profiles can act as an independent control on gravimetric geoids in the medium‐wavelength range. 相似文献
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Water Level Retrieval Using SARAL/AltiKa Observations in the Braided Brahmaputra River,Eastern India
Amit Kumar Dubey Praveen Gupta Subashisa Dutta Raghvendra Pratap Singh 《Marine Geodesy》2015,38(3):549-567
In this study, water level retrieval over the Brahmaputra river was done using different retracking algorithms for the 40 Hz waveform data of SARAL/AltiKa satellite. Water level was retrieved at 10 different locations of the river to evaluate the performance and accuracy of Ka band altimeter over the braided river system. Different retracking algorithms such as ice-1, ice-2, threshold, and beta parameter were used to retrieve water levels. A correlation and error analysis between the in-situ and satellite altimetry derived river levels was carried out for all the stations. Performance and accuracy analysis has established that water level can be retrieved with less than 40 cm root mean square error (RMSE) for most of the braided reaches of the river. The statistical analysis have found that Beta parameter algorithm has performed best in most of the cases amongst the different retracking algorithms used in this study. The water levels derived from 10 different locations were used to generate water surface elevation profiles for the monsoon and nonmonsoon periods. The water levels and the water surface profiles derived from satellite altimetry indicate the potential use of altimeters for the parameterization and calibration of river hydrological, hydrodynamic and sediment transport models. 相似文献
8.
《Marine Geodesy》2013,36(3-4):187-199
The Jason-1 satellite altimeter mission represents a first step towards operational oceanography from satellite altimeter missions. An operational data product, the Operational Sensor Data Record (OSDR), provides measurements from the on-board altimeter and radiometer within 3–5 h of real time. This data product is a wind and wave product that is aimed towards near-real–time meteorological applications. A higher accuracy and more detailed data product, the Interim Geophysical Data Record (IGDR), that is better suited to detailed scientific studies of ocean topography, is available no sooner than 2–3 days from real time. The measurements reported on the OSDR primarily differ from those on the IGDR in that the OSDR reports measurements derived from on-board processing of the altimeter waveforms, while ground retracking of the waveforms is performed for the IGDR. The altimeter-derived measurements on the OSDR are validated through a statistical evaluation of the differences between data on the OSDR and IGDR. In doing so, the impact of ground retracking of the altimeter waveforms is also illustrated. 相似文献
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Marie Tharp 《Marine Geodesy》2013,36(1):63-65
Mixed layer depth (MLD) is an important parameter in the study of air‐sea interaction, acoustic propagation, and fisheries. With the onset of the southwest monsoon, a jetlike surface water flow develops from west to east along the equatorial Indian Ocean (EIO) creating an upward west to east sea surface slope. This in turn creates a slope in MLD in the opposing direction. In this paper, emphasis is placed on obtaining monthly coefficients between MLD and sea level for three regions across the EIO. Using these coefficients, MLD has been estimated from Geosat altimeter data. MLD in this region has been computed with an RMS error of 16 m, from altimeter data, as verified by TOGA in situ profiles. 相似文献
11.
We present an improved crossover adjustment procedure to determine mean sea surface height using TOPEX, 35-day repeat phase ERS-1, Geosat, and 168-day repeat phase ERS-1 satellite altimeter data. The mean sea surface frame defined by the TOPEX data is imposed as certain constraints in our crossover adjustment procedure rather than held fixed as in some other procedures. The new procedure is discussed in detail. Equations are developed to incorporate the a priori information of Topex data as well as other satellite altimeter data. The numerical computation result shows that the rms crossover discrepancies are reduced by an order of 1 cm when the Topex data is not fixed. Furthermore, the computed mean sea surface is less noisy and more realistic than that computed by the traditional procedure. 相似文献
12.
《Marine Geodesy》2013,36(3-4):399-421
The Jason-1 radar altimeter satellite, launched on December 7, 2001 is the follow on to the highly successful TOPEX/Poseidon (T/P) mission and will continue the time series of centimeter level ocean topography measurements. Orbit error is a major component in the overall error budget of all altimeter satellite missions. Jason-1 is no exception and has set a 1-cm radial orbit accuracy goal, which represents a factor of two improvement over what is currently being achieved for T/P. The challenge to precision orbit determination (POD) is both achieving the 1-cm radial orbit accuracy and evaluating the performance of the 1-cm orbit. There is reason to hope such an improvement is possible. The early years of T/P showed that GPS tracking data collected by an on-board receiver holds great promise for precise orbit determination. In the years following the T/P launch there have been several enhancements to GPS, improving its POD capability. In addition, Jason-1 carries aboard an enhanced GPS receiver and significantly improved SLR and DORIS tracking systems along with the altimeter itself. In this article we demonstrate the 1-cm radial orbit accuracy goal has been achieved using GPS data alone in a reduced dynamic solution. It is also shown that adding SLR data to the GPS-based solutions improves the orbits even further. In order to assess the performance of these orbits it is necessary to process all of the available tracking data (GPS, SLR, DORIS, and altimeter crossover differences) as either dependent or independent of the orbit solutions. It was also necessary to compute orbit solutions using various combinations of the four available tracking data in order to independently assess the orbit performance. Towards this end, we have greatly improved orbits determined solely from SLR+DORIS data by applying the reduced dynamic solution strategy. In addition, we have computed reduced dynamic orbits based on SLR, DORIS, and crossover data that are a significant improvement over the SLR- and DORIS-based dynamic solutions. These solutions provide the best performing orbits for independent validation of the GPS-based reduced dynamic orbits. The application of the 1-cm orbit will significantly improve the resolution of the altimeter measurement, making possible further strides in radar altimeter remote sensing. 相似文献
13.
The 1-Centimeter Orbit: Jason-1 Precision Orbit Determination Using GPS, SLR, DORIS, and Altimeter Data 总被引：1，自引：0，他引：1
S. B. Luthcke N. P. Zelensky D. D. Rowlands F. G. Lemoine T. A. Williams 《Marine Geodesy》2003,26(3):399-421
The Jason-1 radar altimeter satellite, launched on December 7, 2001 is the follow on to the highly successful TOPEX/Poseidon (T/P) mission and will continue the time series of centimeter level ocean topography measurements. Orbit error is a major component in the overall error budget of all altimeter satellite missions. Jason-1 is no exception and has set a 1-cm radial orbit accuracy goal, which represents a factor of two improvement over what is currently being achieved for T/P. The challenge to precision orbit determination (POD) is both achieving the 1-cm radial orbit accuracy and evaluating the performance of the 1-cm orbit. There is reason to hope such an improvement is possible. The early years of T/P showed that GPS tracking data collected by an on-board receiver holds great promise for precise orbit determination. In the years following the T/P launch there have been several enhancements to GPS, improving its POD capability. In addition, Jason-1 carries aboard an enhanced GPS receiver and significantly improved SLR and DORIS tracking systems along with the altimeter itself. In this article we demonstrate the 1-cm radial orbit accuracy goal has been achieved using GPS data alone in a reduced dynamic solution. It is also shown that adding SLR data to the GPS-based solutions improves the orbits even further. In order to assess the performance of these orbits it is necessary to process all of the available tracking data (GPS, SLR, DORIS, and altimeter crossover differences) as either dependent or independent of the orbit solutions. It was also necessary to compute orbit solutions using various combinations of the four available tracking data in order to independently assess the orbit performance. Towards this end, we have greatly improved orbits determined solely from SLR+DORIS data by applying the reduced dynamic solution strategy. In addition, we have computed reduced dynamic orbits based on SLR, DORIS, and crossover data that are a significant improvement over the SLR- and DORIS-based dynamic solutions. These solutions provide the best performing orbits for independent validation of the GPS-based reduced dynamic orbits. The application of the 1-cm orbit will significantly improve the resolution of the altimeter measurement, making possible further strides in radar altimeter remote sensing. 相似文献
14.
We present an improved crossover adjustment procedure to determine mean sea surface height using TOPEX, 35-day repeat phase ERS-1, Geosat, and 168-day repeat phase ERS-1 satellite altimeter data. The mean sea surface frame defined by the TOPEX data is imposed as certain constraints in our crossover adjustment procedure rather than held fixed as in some other procedures. The new procedure is discussed in detail. Equations are developed to incorporate the a priori information of Topex data as well as other satellite altimeter data. The numerical computation result shows that the rms crossover discrepancies are reduced by an order of 1 cm when the Topex data is not fixed. Furthermore, the computed mean sea surface is less noisy and more realistic than that computed by the traditional procedure. 相似文献
15.
卫星测高中的垂线偏差法 总被引：6，自引：0，他引：6
卫星测高中的垂线偏差法是当前利用卫星测高技术研究海洋重力场的最优方法,包括利用卫星测高数据计算垂线偏差和利用该垂线偏差确定海洋重力场两部分。研究了Sandwell、Olgiafi、Hwang测高垂线偏差的计算方法和Molodenskii、Hwang利用测高垂线偏差确定海洋重力场的基本原理,分析比较了上述方法的异同,为科学地利用卫星测高资料反演海洋重力场提供理论依据。 相似文献
16.
验潮站资料为评定卫星测高海面高度观测值的精度提供了有效途径。基于数据编辑准则筛选出HY-2A数据，通过引入NCEP实时大气压模型，解决了HY-2A卫星任务后期测高数据产品中部分干对流层延迟项和大气逆压校正项不可用的问题。在此基础上，将HY-2A海面高观测值与验潮站数据进行时空匹配，在选取的9个站点上进行了相关系数和标准差计算。结果表明，两者相关系数平均约为0.676 9，最优可达0.898 7，平均标准差为0.089 5 m。整体验证结果表明，HY-2A卫星测高数据质量符合设计指标，达到预期水平，为海洋重力场反演等应用研究提供了新的可靠数据源。 相似文献
17.
One possible technique to validate the observations of altimeter missions is the comparison with sea-surface heights measured by tide gauges. In our investigation, we compared observations of the two tide gauge stations, Sassnitz and Warnemünde, which are located at the southern coast of the Baltic Sea, with sea-surface heights obtained from the altimeter missions Geosat, ERS-1, ERS-2, and TOPEX/Poseidon. For this purpose, the compared sea-surface heights were related to a common reference system and extrapolated to a common location. GPS observations, leveling data, regional geoid information, sea-surface topography, and postglacial rebound were included in the analysis. Considering the uncertainties of all model components, a more reliable estimation of the error budget (source, type, and magnitude of the errors) was performed. The obtained absolute altimeter biases are (-243 - 32) mm for Geosat, (467 - 19) mm for ERS-1, (76 - 19) mm for ERS-2, and (13 - 18) mm for TOPEX. 相似文献
18.
Stelios P. Mertikas Antonis Daskalakis Ilias N. Tziavos George Vergos Xenofon Fratzis Achilleas Tripolitsiotis 《Marine Geodesy》2015,38(3):249-259
This work presents the first calibration results for the SARAL/AltiKa altimetric mission using the Gavdos permanent calibration facilities. The results cover one year of altimetric observations from April 2013 to March 2014 and include 11 calibration values for the altimeter bias. The reference ascending orbit No. 571 of SARAL/AltiKa has been used for this altimeter assessment. This satellite pass is coming from south and nears Gavdos, where it finally passes through its west coastal tip, only 6 km off the main calibration location. The selected calibration regions in the south sea of Gavdos range from about 8 km to 20 km south off the point of closest approach. Several reference surfaces have been chosen for this altimeter evaluation based on gravimetric, but detailed regional geoid, as well as combination of it with other altimetric models.Based on these observations and the gravimetric geoid model, the altimeter bias for the SARAL/AltiKa is determined as mean value of ?46mm ±10mm, and a median of ?42 mm ±10 mm, using GDR-T data at 40 Hz rate. A preliminary cross-over analysis of the sea surface heights at a location south of Gavdos showed that SARAL/AltiKa measure less than Jason-2 by 4.6 cm. These bias values are consistent with those provided by Corsica, Harvest, and Karavatti Cal/Val sites. The wet troposphere and the ionosphere delay values of satellite altimetric measurements are also compared against in-situ observations (?5 mm difference in wet troposphere and almost the same for the ionosphere) determined by a local array of permanent GNSS receivers, and meteorological sensors. 相似文献
19.
With the advent of satellite altimetry it has become possible to determine the gravity field of the oceans on a global scale. This set of data can be used to predict the bathymetry of deep-seafloor features such as seamounts and ridges. During the last two decades, several algorithms which can be used to develop bathymetric predictions from satellite altimeter data have been published. The characteristics and quality of these algorithms are reviewed in this study. Based on this analysis, we suggest some guidelines for processing data towards the production of maps showing predicted bathymetry for economical purposes. 相似文献
20.
A method is described for mapping time-uncorrelated large-scale errors in satellite altimeter sea surface heights. Standard deviations of differences between pairs of successive measurements at track crossovers are computed, and the functional dependence of these deviations on absolute time difference is used to estimate the errors of individual measurements. This is first applied to all of ERS-1,2 altimeter data in the Pacific Ocean, yielding average errors of 3.2 cm in the deep ocean (>1 km) and 4.7 cm in the shallow seas (<1 km). The procedure is repeated for variable latitude bands, each with a full range of possible time differences, yielding a meridional profile of computed errors, ranging from 2.6 cm near the Antarctic continent (67–60S) and South Subtropical regions (25–5S) to 3.5 cm in the Antarctic Circumpolar Current (60–45S) and the Northern Hemisphere Subtropical and Subpolar Gyres. Finally, coarse-resolution maps of these errors are produced by subdividing the Pacific Ocean into latitude-longitude bins, each large enough to contain a sufficient number of samples for the functional fits. The larger errors are in Northwest and Subtropical Pacific, especially in South China Sea (4.3 to 4.5 cm) and off northern Australia (5.4 cm), while the smaller errors (2.5 to 3 cm) are in Northeast Pacific, central Tropical Pacific and near Antarctica in Southeast Pacific Ocean. These are lower bounds on altimeter errors, as they do not include contributions from time-correlated errors. We find that the computed error fields are not correlated with sea level standard deviations, thus disproving the notion that altimeter error variance can be scaled with the variance of sea surface height data. 相似文献