Calibration of JASON-1 Altimeter over Lake Erie

This article describes absolute calibration results for both JASON-1 and TOPEX Side B (TSB) altimeters obtained at the Lake Erie calibration site, Marblehead, Ohio, USA. Using 15 overflights, the estimated JASON altimeter bias at Marblehead is 58 ± 38 mm, with an uncertainty of 19 mm based on detailed error analysis. Assuming that the TSB bias is negligible, relative bias estimates using both data from the TSB-JASON formation flight period and data from 48 water level gauges around the entire Great Lakes confirmed the Marblehead results. Global analyses using both the formation flight data and dual-satellite (TSB and JASON) crossovers yield a similar relative bias estimate of 146 ± 59 mm, which agrees well with open ocean absolute calibration results obtained at Harvest, Corsica, and Bass Strait (e.g., Watson et al. 2003). We find that there is a strong dependence of bias estimates on the choice of sea state bias (SSB) models. Results indicate that the invariant JASON instrument bias estimated oceanwide is 71 mm, with additional biases of 76 mm or 28 mm contributed by the choice of Collecte Localisation Satellites (CLS) SSB or Center for Space Research (CSR) SSB model, respectively. Similar analysis in the Great Lakes yields the invariant JASON instrument bias at 19 mm, with the SSB contributed biases at 58 mm or 13 mm, respectively. The reason for the discrepancy is currently unknown and warrants further investigation. Finally, comparison of the TOPEX/POSEIDON mission (1992-2002) data with the Great Lakes water level gauge measurements yields a negligible TOPEX altimeter drift of 0.1 mm/yr.     

Jason-1 Geophysical Performance Evaluation

The Jason-1 satellite was launched on 7 December 2001 with the primary objective of continuing the high accuracy time series of altimeter measurements that began with the TOPEX/Poseidon mission in 1992. To achieve this goal, it is necessary to validate the performance of the Jason-1 measurement system, and to verify that its error budget is at least at the same level as that of the TOPEX/Poseidon mission. The article reviews the main components of the Jason-1 altimetric error budget from instrument characterization to the geophysical use of the data. Using the Interim Geophysical Data Records (16DR) that were distributed to the Jason-1 Science Working Team during the verification phase of the mission, it is shown that the Jason-1 mission is performing well enough to continue studies of the large-scale features of the ocean, and especially to continue time series of mean sea-level variations with an accuracy comparable to TOPEX/Poseidon.     

Guest editorial

The Jason-1 satellite was launched on 7 December 2001 with the primary objective of continuing the high accuracy time series of altimeter measurements that began with the TOPEX/Poseidon mission in 1992. To achieve this goal, it is necessary to validate the performance of the Jason-1 measurement system, and to verify that its error budget is at least at the same level as that of the TOPEX/Poseidon mission. The article reviews the main components of the Jason-1 altimetric error budget from instrument characterization to the geophysical use of the data. Using the Interim Geophysical Data Records (16DR) that were distributed to the Jason-1 Science Working Team during the verification phase of the mission, it is shown that the Jason-1 mission is performing well enough to continue studies of the large-scale features of the ocean, and especially to continue time series of mean sea-level variations with an accuracy comparable to TOPEX/Poseidon.     

基于Jason-2的Saral/AltiKa高度计全球统计评估与交叉定标

利用Jason-2同期观测的GDR数据对Saral/AltiKa观测的有效波高、后向散射系数、电离层延迟、对流层延迟等参数进行对比分析,发现各参数存在不同程度的差异,并在文中对差异原因进行了讨论分析。计算了Saral/AltiKa卫星升轨与降轨间的交叉点海面高差异,结果表明,其交叉点差值为(1.22±65.00)mm,与同期Jason-2的交叉点海面高差异(0.25±58.60)mm相当,同时计算Saral/AltiKa和Jason-2之间的交叉点海面高差异进行星间交叉定标,发现存在(-58.64±66.53)mm的交叉点不符值,研究结果与国外定标场的绝对定标结果一致。     

Altimeter Signal-to-Noise for Deep Ocean Processes in Operational Systems

The ocean signal for this study is the sea surface height due to the slowly varying (greater than 5-day) ocean processes, which are predominantly the deep ocean mesoscale. These processes are the focus of present assimilation systems for monitoring and predicting ocean circulation due to ocean fronts and eddies and the associated environmental changes that impact real time activities in areas with depths greater than about 200 m. By this definition, signal-to-noise may be estimated directly from altimeter data sets through a crossover point analysis. The RMS variability in crossover differences is due to instrument noise, errors in environmental corrections to the satellite observation, and short time period oceanic variations. The signal-to-noise ratio indicates that shallow areas are typically not well observed due to the high frequency fluctuations. Many deep ocean areas also contain significant high frequency variability such as the subpolar latitudes, which have large atmospheric pressure systems moving through, and these in turn generate large errors in the inverse barometer correction. Understanding the spatial variations of signal to noise is a necessary prerequisite for correct assimilation of the data into operational systems.     

Altimeter Signal-to-Noise for Deep Ocean Processes in Operational Systems

The ocean signal for this study is the sea surface height due to the slowly varying (greater than 5-day) ocean processes, which are predominantly the deep ocean mesoscale. These processes are the focus of present assimilation systems for monitoring and predicting ocean circulation due to ocean fronts and eddies and the associated environmental changes that impact real time activities in areas with depths greater than about 200 m. By this definition, signal-to-noise may be estimated directly from altimeter data sets through a crossover point analysis. The RMS variability in crossover differences is due to instrument noise, errors in environmental corrections to the satellite observation, and short time period oceanic variations. The signal-to-noise ratio indicates that shallow areas are typically not well observed due to the high frequency fluctuations. Many deep ocean areas also contain significant high frequency variability such as the subpolar latitudes, which have large atmospheric pressure systems moving through, and these in turn generate large errors in the inverse barometer correction. Understanding the spatial variations of signal to noise is a necessary prerequisite for correct assimilation of the data into operational systems.     

Calibration of JASON-1 Altimeter over Lake Erie Special Issue: Jason-1 Calibration/Validation

This article describes absolute calibration results for both JASON-1 and TOPEX Side B (TSB) altimeters obtained at the Lake Erie calibration site, Marblehead, Ohio, USA. Using 15 overflights, the estimated JASON altimeter bias at Marblehead is 58 ± 38 mm, with an uncertainty of 19 mm based on detailed error analysis. Assuming that the TSB bias is negligible, relative bias estimates using both data from the TSB-JASON formation flight period and data from 48 water level gauges around the entire Great Lakes confirmed the Marblehead results. Global analyses using both the formation flight data and dual-satellite (TSB and JASON) crossovers yield a similar relative bias estimate of 146 ± 59 mm, which agrees well with open ocean absolute calibration results obtained at Harvest, Corsica, and Bass Strait (e.g., Watson et al. 2003). We find that there is a strong dependence of bias estimates on the choice of sea state bias (SSB) models. Results indicate that the invariant JASON instrument bias estimated oceanwide is 71 mm, with additional biases of 76 mm or 28 mm contributed by the choice of Collecte Localisation Satellites (CLS) SSB or Center for Space Research (CSR) SSB model, respectively. Similar analysis in the Great Lakes yields the invariant JASON instrument bias at 19 mm, with the SSB contributed biases at 58 mm or 13 mm, respectively. The reason for the discrepancy is currently unknown and warrants further investigation. Finally, comparison of the TOPEX/POSEIDON mission (1992–2002) data with the Great Lakes water level gauge measurements yields a negligible TOPEX altimeter drift of 0.1 mm/yr.     

中国近海海平面变化区域相关分析

由测高卫星升、降弧段海面高交叉点约束方法,用TOPEX／POSEIDON测高数据计算了黄海、东海、南海海域的海平面变化;分析了三个海区海平面变化的相关性;在频域内讨论了它们之间的相干性;分析了海水面积随纬度带的变化对不同纬度分布的海区海平面变化量的影响。     

Improvement of Sea Surface Height Measurements of HY-2A Satellite Altimeter Using Jason-2

Abstract

HY-2A, which was launched on 16 August 2011, is the Chinese first microwave ocean dynamics environment satellite. Analyses of HY-2A daily sea-level anomaly data and HY-2A–Jason-2 (H-J) dual crossover sea-level anomaly differences show that HY-2A has measurement differences that mainly refer to an orbit error. H-J crossover differences and HY-2A–HY-2A (H-H) crossover differences give an estimate of the HY-2A orbit error. Smoothing cubic-spline functions are then used to obtain a continuous estimation of the HY-2A orbit error over time. On the basis of the simultaneous global minimization of H-J dual crossover differences and H-H crossover differences, the HY-2A observation error is efficiently reduced and height measurement data that are more precise are obtained. Specifically, the range bias/trend of the HY-2A altimeter is removed effectively and the root mean square of H-J crossover sea-level anomaly differences decrease from above 60?cm to 5.64?cm, and the standard deviation of H-J crossover differences decreases from 6.68 to 5.64?cm. Furthermore, the rms and standard deviations of H-H crossover differences both decrease from 7.46 to 6.55?cm. The results show that HY-2A after correction has a measurement accuracy and precision that are comparable to those of Jason-2.     

联合卫星测高和卫星重力数据研究热容海平面变化

首先用卫星测高资料计算了1993～2009年6月的全球平均海平面变化。用GRACE(gravity recovery andclimate experiment)时变重力场系数反演了2003～2009年6月全球平均海水质量变化。联合GRACE和卫星测高资料计算了2003～2009年6月的热容海平面变化,该变化呈上升趋势。用日本气象局Ishii等提供的海温数据计算了1993～2006年的海水引起的平均热膨胀海平面变化,1993～2003年间,全球海洋热膨胀引起的热容海平面呈上升趋势,约占同期平均海平面变化的一半。利用ARGO温盐数据计算了2004～2009年6月平均热容海平面变化,也呈上升态势,只是变化速率有所减慢。     

The GAVDOS Mean Sea Level and Altimeter Calibration Facility: Results for Jason-1

The location of the GAVDOS facility is under a crossing point of the original ground-tracks of TOPEX/Poseidon and the present ones for Jason-1, and adjacent to an ENVISAT pass, about 50 km south of Crete, Greece. Ground observations and altimetry comparisons over cycles 70 to 90, indicate that a preliminary estimate of the absolute measurement bias for the Jason-1 altimeter is 144.7 ± 15 mm. Comparison of Jason microwave radiometer data from cycles 37 and 62, with locally collected water vapor radiometer and solar spectrometer observations indicate a 1-2 mm agreement.     

Trends in Extreme Mean Sea Level Quantiles from Satellite Altimetry

Satellite altimetry allows the study of sea-level long-term variability on a global and spatially uniform basis. Here quantile regression is applied to derive robust median regression trends of mean sea level as well as trends in extreme quantiles from radar altimetry time series. In contrast with ordinary least squares regression, which only provides an estimate on the rate of change of the mean of data distribution, quantile regression allows the estimation of trends at different quantiles of the data distribution, yielding a more complete picture of long-term variability. Trends derived from basin-wide averaged regional mean sea level time series are robust and similar for all quantiles, indicating that all parts of the data distribution are changing at the same rate. In contrast, trends are not robust and diverge across quantiles in the case of local time series. Trends are under- (over-)estimated in the western (eastern) equatorial Pacific. Furthermore, trends in the lowermost quantile (0.05) are larger than the median trend in the western Pacific, while trends in the uppermost quantile (0.95) are lower than the median trend in the eastern Pacific. These differences in trends in extreme mean sea level quantiles are explained by the exceptional effect of the strong 1997–1998 El Niño–Southern Oscillation (ENSO) event.     

The GAVDOS Mean Sea Level and Altimeter Calibration Facility: Results for Jason-1

The location of the GAVDOS facility is under a crossing point of the original ground-tracks of TOPEX/Poseidon and the present ones for Jason-1, and adjacent to an ENVISAT pass, about 50 km south of Crete, Greece. Ground observations and altimetry comparisons over cycles 70 to 90, indicate that a preliminary estimate of the absolute measurement bias for the Jason-1 altimeter is 144.7 ± 15 mm. Comparison of Jason microwave radiometer data from cycles 37 and 62, with locally collected water vapor radiometer and solar spectrometer observations indicate a 1–2 mm agreement.     

Absolute Sea Level Surface Modeling for the Mediterranean from Satellite Altimeter and Tide Gauge Measurements

Changes in the height of the ocean can be described through the relative and absolute sea level changes depending on the geodetic reference the sea level records are related to. Satellite altimetry provides absolute sea level (ASL) measurements related to the global geodetic reference, whereas tide gauges provide relative sea level (RSL) measurements related to the adjacent land. This study aims at computing the ASL surfaces for different time epochs from combined satellite altimeter and tide gauge records. A method of sea level data fusion is proposed to enable modeling of the impact of present and future sea level changes on the coast. Sea surface modeling was investigated for ten different gridding methods commonly used for the interpolation of altimeter data over the open ocean and extrapolation over the coastal zones. The performance of gridding methods was assessed based on the comparison of the gridded altimeter data and corrected tide gauge measurements. Finally, the sea level surfaces related to the GRS80 global reference ellipsoid were computed for the Mediterranean Sea over the altimeter period. In addition, the current sea level trends were estimated from both sea level measurements.     

Altimetric Algorithm and Errors of Ocean Altimetry Using GNSS Reflection Signals

As a new remote sensing technology, the global navigation satellite system (GNSS) reflection signals can be used to collect the information of ocean surface wind, surface roughness and sea surface height. Ocean altimetry based on GNSS reflection technique is of low cost and it is easy to obtain large amounts of data thanks to the global navigation satellite constellation. We can estimate the sea surface height as well as the position of the specular reflection point. This paper focuses on the study of the algorithm to determine the specular reflection point and altimetry equations to estimate the sea surface height over the reflection region. We derive the error equation of sea surface height based on the error propagation theory. Effects of the Doppler shift and the size of the glistening zone on the altimetry are discussed and analyzed at the same time. Finally, we calculate the sea surface height based on the simulated GNSS data within the whole day and verify the sea surface height errors according to the satellite elevation angles. The results show that the sea surface height can reach the precision of 6 cm for elevation angles of 55° to 90°, and the theoretical error and the calculated error are in good agreement.     

Cross-Calibration and Long-Term Monitoring of the Microwave Radiometers of ERS,TOPEX, GFO,Jason, and Envisat

The radiometers on board the satellites ERS-1, TOPEX/Poseidon, ERS-2, GFO, Jason-1, and Envisat measure brightness temperatures at two or three different frequencies to determine the total columnal water vapor content and wet tropospheric path delay, a major correction to the altimeter range measurements. In order to asses the long-term stability of the path delay, the radiometers are calibrated against vicarious cold and hot references, against each other, and against several atmospheric models. Four of these radiometers exhibit significant drifts in at least one of the channels, resulting in yet unmodeled errors in path delay of up to 1 mm/year, thus limiting the accuracy at which global sea level rise can be inferred from the altimeter range measurements.     

Cross-Calibration and Long-Term Monitoring of the Microwave Radiometers of ERS, TOPEX, GFO, Jason, and Envisat

The radiometers on board the satellites ERS-1, TOPEX/Poseidon, ERS-2, GFO, Jason-1, and Envisat measure brightness temperatures at two or three different frequencies to determine the total columnal water vapor content and wet tropospheric path delay, a major correction to the altimeter range measurements. In order to asses the long-term stability of the path delay, the radiometers are calibrated against vicarious cold and hot references, against each other, and against several atmospheric models. Four of these radiometers exhibit significant drifts in at least one of the channels, resulting in yet unmodeled errors in path delay of up to 1 mm/year, thus limiting the accuracy at which global sea level rise can be inferred from the altimeter range measurements.     

A New Methodology for Incorporating Tide Gauge Data in Sea Surface Topography Models

As part of the Vertical Offshore Reference Frames (VORF) project sponsored by the U. K. Hydrographic Office, a new model for Sea Surface Topography (SST) around the British Isles has been developed. For offshore areas (greater than 30 km from the coast), this model is largely derived from satellite altimetry. However, its accuracy and level of detail have been enhanced in coastal areas by the inclusion of not only the 60 PSMSL tide gauges with long-term records around the coasts of the United Kingdom and Ireland but also some 385 gauges established at different epochs and for different observation spans by the U. K. Admiralty. All tide gauge data were brought into a common reference frame by a combination of datum models and direct GPS observations, but a more significant challenge was to bring all short-term sea level observations to an unbiased value at a common epoch. This was achieved through developing a spatial-temporal correlation model for the variations in mean sea level around the British Isles, which in turn meant that gauges with long-term observation spans could be used as control points to improve the accuracy of Admiralty gauges. It is demonstrated that the latter can contribute point observations of mean sea level (MSL) with a precision of 0.078 m. A combination of least squares collocation and interpolation was developed to merge the coastal point and offshore gridded data sets, with particular algorithms having to be developed for different configurations of coastal topology. The resulting model of sea surface topography is shown to present a smooth transition from inshore coastal areas to offshore zones. Further benefits of the techniques developed include an enhanced methodology for detecting datum discontinuities at permanent tide gauges.     

Impact of Multisatellite Altimeter Data Assimilation on Wave Analysis and Forecast

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.