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.     

海平面长期变化对东中国海潮波的影响

对1992年10月～2007年9月AVISO高度计融合资料进行分析,得到东中国海海平面变化速率。根据计算出的海平面变化速率,线性外推50和100a后东中国海海平面。采用ECOMSED模式,模拟出当前以及50a,100a后东中国海潮波,分析海平面长期变化对东中国海潮波的影响。结果表明,各分潮振幅、迟角与现有各分潮振幅、迟角之差有一定的分布模式,振幅在大部分地区增大,迟角在大部分地区减小,在深水大洋区振幅和迟角基本不变,无潮点位置相对于现有各分潮无潮点位置均发生偏移。     

Sea Level Prediction in the Yellow Sea From Satellite Altimetry With a Combined Least Squares-Neural Network Approach

Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2?cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast.     

Impact of Satellite Altimetry on Simulations of Sea Level Variability by an Indian Ocean Model

This article describes the impact of satellite altimeter data on the simulations of sea level variability (SLV) by a nonlinear reduced gravity model of the entire Indian Ocean. The model has been forced by 6-hourly analyzed wind stress data containing SSM/I observations and has been able to produce realistic circulation features. However, SLV values observed by Topex/Poseidon altimeter do not fit these simulations because of imperfect initial data. Hence an attempt has been made to initialize the model using altimeter data. The initialized model-generated SLVvalues have been compared with SLV derived by altimeter for monsoon as well as nonmonsoon months of 1996. Experimental runs have been performed for 10 days, 20 days, and one month. It has been found that the initialized model results on the final day of these experiments are in very good agreement with altimeter data of the same day. It is thus possible, in principle, to hindcast and forecast sea level variations in the time scale of 10 days to one month with the availability of good quality wind data for forcing the model and altimeter observations of sea level for initializing it.     

Impact of Satellite Altimetry on Simulations of Sea Level Variability by an Indian Ocean Model

This article describes the impact of satellite altimeter data on the simulations of sea level variability (SLV) by a nonlinear reduced gravity model of the entire Indian Ocean. The model has been forced by 6-hourly analyzed wind stress data containing SSM/I observations and has been able to produce realistic circulation features. However, SLV values observed by Topex/Poseidon altimeter do not fit these simulations because of imperfect initial data. Hence an attempt has been made to initialize the model using altimeter data. The initialized model-generated SLVvalues have been compared with SLV derived by altimeter for monsoon as well as nonmonsoon months of 1996. Experimental runs have been performed for 10 days, 20 days, and one month. It has been found that the initialized model results on the final day of these experiments are in very good agreement with altimeter data of the same day. It is thus possible, in principle, to hindcast and forecast sea level variations in the time scale of 10 days to one month with the availability of good quality wind data for forcing the model and altimeter observations of sea level for initializing it.     

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.     

Submesoscale Eddies in the White Sea Based on Satellite Radar Measurements

Izvestiya, Atmospheric and Oceanic Physics - This paper presents the results of the analysis of the archive of radar images of Envisat Advanced Synthetic Aperture Radar (ASAR) and Radarsat-1,2 for...     

Effect of the East Siberian Current on Water Exchange in the Bering Strait Based on Satellite Altimetry Measurements

Oceanology - The seasonal and interannual variability of water exchange in the Bering Strait and its relationship with Arctic circulation is investigated on the basis of satellite-altimetry...     

Mesoscale Eddies in the Bering Sea from Satellite Altimetry Data

Izvestiya, Atmospheric and Oceanic Physics - The dynamics of mesoscale eddies in the Bering Sea is studied by the method for automated eddy identification on the basis of altimetry-derived...     

卫星测高正常点海面高度计算方法研究

正常点海面高计算是卫星测高数据处理的基础.从测高卫星飞行轨道的规律出发,提出了采用“距离加权平均”计算正常点海面高的新方法,阐述了“距离加权平均”这一方法计算正常点海面高的原理.并分别利用传统方法和新方法所计算出的中国海域内正常点海面高数据,进行交叉点海面高不符值及其平差计算,对所得结果进行精度评定.实际计算结果比对证明了利用“距离加权平均”法计算正常点海面高的可行性和优越性.     

Shelf Waves in the Great Australian Bight Based on Satellite Altimetry Data

Izvestiya, Atmospheric and Oceanic Physics - In this study we analyze shelf waves in the Great Australian Bight using satellite altimetry data. The phase velocity of the first mode of topographic...     

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.     

2003-2008年全球海平面变化评估

导致全球海平面短时间尺度变化主要有海水密度和海水质量这两方面的变化因素。通过重力校正和气候试验（GRACE）对地球重力场进行观测,并联合卫星测高SA、ARGO系统的观测结果可推知：自2003年以来,海平面的上升主要是因为海水质量的增加。     

卫星测高数据格网化方法研究

用连续曲率张力样条方法和Shepard方法分别对多颗卫星和单颗卫星的海面高数据进行格网化,得到平均海面高。将平均海面高与DNSC08、KMSS04、CLS01平均海面高模型进行了比较,分析了两种格网化方法的优劣。结果表明,连续曲率张力样条方法比Shepard方法更适合于卫星测高数据的格网化。     

Current Intensity Trends in the Labrador and Irminger Seas Based on Satellite Altimetry Data

Izvestiya, Atmospheric and Oceanic Physics - Sea level measurements from an absolute dynamic typography dataset for the period of 1993–2015 were used to study the variability in geostrophic...     

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。     

Assimilation of the Data of Satellite Altimetry in an Eddy-Resolving Model of Circulation of the Black Sea

The data of satellite altimetry are used to simulate the Black-Sea circulation. The altimetry data of the TOPEX/Poseidon and ERS satellites are prepared within the framework of the NASA Ocean Altimeter Pathfinder project. The additional data processing is performed to compute the dynamic level reflecting the circulation of the Black Sea. The altimetry sea-level is assimilated in an eddy-resolving model of circulation of the Black Sea based on primitive equations. The accuracy of the obtained fields of temperature and salinity is estimated by comparing with the data of large-scale hydrographic surveys according to the ComSBlack program. The prognostic capabilities of the proposed model are estimated by comparing the obtained results with the fields computed with the help of assimilation of the altimetry data.     

A Bathymetric Model for the South China Sea from Satellite Altimetry and Depth Data

A bathymetric model for the South China Sea is computed from altimeter-derived gravity anomalies, shipborne depths, ETOPO5, and the GMT shorelines using a procedure that includes downward continuation, linear regression, and data merging. The model best fits the GMT shorelines and is a compromise between smoothness, degree of agreement with ship data, and the seafloor features we wish to retain. The model is proven useful in studying the tectonics and modeling the ocean tide of the South China Sea.     

Estimating the Kuroshio Axis South of Japan Using Combination of Satellite Altimetry and Drifting Buoys

By tracking the locally strongest part of the sea-surface velocity field, which was obtained by integrating data of satellite altimeters and surface drifting buoys, we extracted the Kuroshio axis south of Japan every 10 days from October 1992 to December 2000. The obtained axes clearly express the effect of the bottom topography; three modes were observed when the Kuroshio ran over the Izu Ridge. The axis was very stable to the south of ‘Tosa-bae,’ off the Kii Channel. Mean current speed at the Kuroshio axis gradually increased from 0.65 m/s south of Kyushu to 1.45 m/s off Enshu-nada. This revised version was published online in July 2006 with corrections to the Cover Date.     

Direct Measurements of Deep Currents in the Northern Japan Sea

Long-term current measurements by means of subsurface moorings were made for the first time at seven sites in the Japan Basin, the northern part of the Japan Sea. The objective was to directly explore the velocity field in the highly homogeneous deep water mass (the Japan Sea Proper Water) that occupies depths below 500 m. On each mooring three current meters were equipped at an approximately equal distance below about 1000 m depth. Duration of the measurements was 1 to 3 years depending on specific site. This paper describes the basic data set from the moored measurements. It is found that the deep water of the Japan Basin is very energetic with eddies and vertically coherent currents of the order of 0.1 m/s. Surprisingly, the currents and eddies exhibit strong seasonal dependence even in the deepest layers of the Basin. The observed new current features are discussed in comparison with conventional deep circulation pictures derived from hydrographic data. This revised version was published online in August 2006 with corrections to the Cover Date.