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1.
Estimation of Contamination of ERS-2 and POSEIDON Satellite Radar Altimetry Close to the Coasts of Australia 总被引：4，自引：0，他引：4
It is broadly acknowledged that the precision of satellite-altimeter-measured instantaneous sea surface heights (SSH) is lower in coastal regions than in open oceans, due partly to contamination of the radar return from the coastal sea-surface state and from land topography. This study investigates the behavior of ERS-2 and POSEIDON altimeter waveform data in coastal regions and estimates a boundary around Australia's coasts in which the altimeter range may be poorly estimated by on-satellite tracking software. Over one million 20 Hz ERS-2 (March to April 1999) and POSEIDON (January 1998 to January 1999) radar altimeter waveform data were used over an area extending 350 km offshore Australia. The DS759.2 (5'resolution) ocean depth model and the GSHHS (0.2 km resolution) shoreline model were used together to define the coastal regions. Using the 50% threshold retracking points as the estimates of expected tracking gate, we determined that the sea surface height is contaminated out to maximum distance of between about 8 km and 22 km from the Australian shoreline for ERS-2, depending partly on coastal topography. Using the standard deviation of the mean waveforms as an indication of the general variability of the altimeter returns in the Australian coastal region shows obvious coastal contamination out to about 4 km for both altimeters, and less obvious contamination out to about 8 km for POSEIDON and 10 km for ERS-2. Therefore, ERS-2 and POSEIDON satellite altimeter data should be treated with some caution for distances less than about 22 km from the Australian coast and probably ignored altogether for distances less than 4 km. 相似文献
2.
Patrick F. Cummins Gary S.E. Lagerloef 《Deep Sea Research Part I: Oceanographic Research Papers》2004,51(12):365
Interannual variability of the sea surface height (SSH) over the northeast Pacific Ocean is hindcast with a reduced-gravity, quasi-geostrophic model that includes linear damping. The model is forced with monthly Ekman pumping fields derived from the NCEP reanalysis wind stresses. The numerical solution is compared with SSH observations derived from satellite altimeter data and gridded at a lateral resolution of 1 degree. Provided that the reduced gravity parameter is chosen appropriately, the results demonstrate that the model has significant hindcast skill over interior regions of the basin, away from continental boundaries. A damping time scale of 2 to 3 years is close to optimal, although the hindcast skill is not strongly dependent on this parameter.A simplification of the quasi-geostrophic model is considered in which Rossby waves are eliminated, yielding a Markov model driven by local Ekman pumping. The results approximately reproduce the hindcast skill of the more complete quasi-geostrophic model and indicate that the interannual SSH variability is dominated by the local response to wind forcing. There is a close correspondence the two leading empirical orthogonal modes of the local model and those of the observed SSH anomalies. The latter account for over half of the variance of the interannual signal over the region. 相似文献
3.
4.
Analysis and modeling of the seasonal South China Sea temperature cycle using remote sensing 总被引：1，自引：0，他引：1
Daniel J. Twigt Erik D. De Goede Ernst J. O. Schrama Herman Gerritsen 《Ocean Dynamics》2007,57(4-5):467-484
The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale.
It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated
tidal mixing and exchange. This is motivated by the possibility to significantly increase the model’s computational efficiency
when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate
transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal
time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature
cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed
using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly
mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological
forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature
(SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed
against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good
agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply
a SST nudging method at the free water surface. This considerably improves the model’s vertical temperature representation
in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal
temperature cycle for the deep SCS basin can be represented to a good degree. For shallow regions, the absence of tidal mixing
and exchange has a clear impact on the model’s temperature representation. This effect on the large-scale temperature cycle
can be compensated to a good degree by SST nudging for diagnostic applications. 相似文献
5.
Field biological and geomorphological observations in certain East Asia coasts permit definition of Mean Sea Level (MSL) with an accuracy of ～10 cm, that is, a vertical geodetic datum, as well as recognition of the MSL of fossil shorelines, up to a few thousand years old, mainly associated with tectonic/seismic effects. Subsidence produced by compaction of nearly-surficial strata seems also to be a usual effect. These data indicate that datum variability is a widespread effect in East Asia, time-dependent even at time scales affecting engineering works, but only in a few cases fully predictable. 相似文献
6.
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
7.
Hani Abdallah Jean-Stéphane Bailly Nicolas Baghdadi Nicolas Lemarquand 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):833-844
Given that water resources are scarce and are strained by competing demands, it has become crucial to develop and improve techniques to observe the temporal and spatial variations in the inland water volume. Due to the lack of data and the heterogeneity of water level stations, remote sensing, and especially altimetry from space, appear as complementary techniques for water level monitoring. In addition to spatial resolution and sampling rates in space or time, one of the most relevant criteria for satellite altimetry on inland water is the accuracy of the elevation data. Here, the accuracy of ICESat LIDAR altimetry product is assessed over the Great Lakes in North America. The accuracy assessment method used in this paper emphasizes on autocorrelation in high temporal frequency ICESat measurements. It also considers uncertainties resulting from both in situ lake level reference data. A probabilistic upscaling process was developed. This process is based on several successive ICESat shots averaged in a spatial transect accounting for autocorrelation between successive shots. The method also applies pre-processing of the ICESat data with saturation correction of ICESat waveforms, spatial filtering to avoid measurement disturbance from the land–water transition effects on waveform saturation and data selection to avoid trends in water elevations across space. Initially this paper analyzes 237 collected ICESat transects, consistent with the available hydrometric ground stations for four of the Great Lakes. By adapting a geostatistical framework, a high frequency autocorrelation between successive shot elevation values was observed and then modeled for 45% of the 237 transects. The modeled autocorrelation was therefore used to estimate water elevations at the transect scale and the resulting uncertainty for the 117 transects without trend. This uncertainty was 8 times greater than the usual computed uncertainty, when no temporal correlation is taken into account. This temporal correlation, corresponding to approximately 11 consecutive ICESat shots, could be linked to low transmitted ICESat GLAS energy and to poor weather conditions. Assuming Gaussian uncertainties for both reference data and ICESat data upscaled at the transect scale, we derived GLAS deviations statistics by averaging the results at station and lake scales. An overall bias of −4.6 cm (underestimation) and an overall standard deviation of 11.6 cm were computed for all lakes. Results demonstrated the relevance of taking autocorrelation into account in satellite data uncertainty assesment. 相似文献
8.
We propose a new analytical algorithm for the estimation of wind speeds from altimeter data using the mean square slope of
the ocean surface, which is obtained by integration of a widely accepted wind-wave spectrum including the gravity-capillary
wave range. It indicates that the normalized radar cross section depends not only on the wind speed but also on the wave age.
The wave state effect on the altimeter radar return becomes remarkable with increasing wind speed and cannot be neglected
at high wind speeds. A relationship between wave age and nondimensional wave height based on buoy observational data is applied
to compute the wave age using the significant wave height of ocean waves, which could be simultaneously obtained from altimeter
data. Comparison with actual data shows that this new algorithm produces more reliable wind speeds than do empirical algorithms.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
9.
Hui Feng Doug Vandemark Yves Quilfen Bertrand Chapron Brian Beckley 《Ocean Engineering》2006,33(11-12):1431-1461
The study presents assessment of an operational wave model (Wavewatch III), focusing upon the model sensitivity to wind-forcing products. Four wind fields are used to drive the model, including the NCEP/NCAR reanalysis and three other products that assimilate various satellite wind measurements having high spatial resolution, including the QuikSCAT scatterometer. Three wave field statistics: significant wave height, mean zero-crossing wave period, and mean square slope are compared with collocated TOPEX altimeter derivatives to gauge the relative skill of differing wind-forced model runs, as well as to demonstrate an extended use of the altimeter beyond simply supplying wave height for wave model validation and assimilation. Results suggest that model output is critically sensitive to choice of the wind field product. Higher spatial resolution in the wind fields does lead to improved agreement for the higher-order wave statistics. 相似文献
10.
利用8a的TOPEX/Poseidon高度计资料,采用小波分析方法,研究南海东北部海域海面高度的多尺度变异.研究得出,南海东北部海域的海面高度变化主要受3个不同时间尺度因素的影响,其中最强的是季节变化(Va)的影响,其周期范围为0.60～1.20a,它主要与海面高度的年循环相联系;其次是周期在0.17～0.45a(即2～5个月)的变化(V25)的影响,它主要与中尺度时间周期引起的海面高度变化相联系.较小的一个因素是周期在1 50～5 00a的年际变化(Vi)的影响,它主要与El Niño事件引起的海面高度变化相联系.分析表明对8a平均而言,海面高度变化所引起的能量偏差V25的高值区主要分布在吕宋海峡以西海域,在1995,1996和1999年出现最大值;偏差Va的高值区分布在吕宋岛西北海域,在1995年出现最大值;年际偏差Vi的高值区位于台湾的西南海域,在1997～1998年El Niño事件期间达到最大. 相似文献