Sea Level Acceleration in the China Seas

While global mean sea level rise (SLR) and acceleration (SLA) are indicators of climate change and are informative regarding the current state of the climate, assessments of regional and local SLR are essential for policy makers responding to, and preparing for, changes in sea level. In this work, three acceleration detection techniques are used to demonstrate the robust SLA in the China Seas. Interannual to multidecadal sea level variations (periods \u3e2 years), which are mainly related to natural internal climate variability and significantly affect estimation of sea level acceleration, are removed with empirical mode decomposition (EMD) analysis prior to the acceleration determination. Consistent SLAs of 0.085 ± 0.020 mm·yr−2 (1950–2013) and 0.074 ± 0.032 mm·yr−2 (1959–2013) in regional tide gauge records are shown to result from the three applied approaches in the Bohai Sea (BS) and East China Sea (ECS), respectively. The SLAs can be detected in records as short as 20 years if long-term sea level variability is adequately removed. The spatial distribution of SLA derived from a sea level reconstruction shows significant SLA in the BS, Yellow Sea (YS) and Yangtze River Estuary

Impacts of Oil Spills on Altimeter Waveforms and Radar Backscatter Cross Section

Ocean surface films can damp short capillary-gravity waves, reduce the surface mean square slope, and induce sigma0 blooms in satellite altimeter data. No study has ascertained the effect of such film on altimeter measurements due to lack of film data. The availability of Environmental Response Management Application (ERMA) oil cover, daily oil spill extent, and thickness data acquired during the Deepwater Horizon (DWH) oil spill accident provides a unique opportunity to evaluate the impact of surface film on altimeter data. In this study, the Jason-1/2 passes nearest to the DWH platform are analyzed to understand the waveform distortion caused by the spill as well as the variation of σ0 as a function of oil thickness, wind speed, and radar band. Jason-1/2 Ku-band σ0 increased by 10 dB at low wind speed (s-1) in the oil-covered area. The mean σ0 in Ku and C bands increased by 1.0-3.5 dB for thick oil and 0.9-2.9 dB for thin oil while the waveforms are strongly distorted. As the wind increases up to 6 m s-1, the mean σ0 bloom and waveform distortion in both Ku and C bands weakened for both thick and thin oil. When wind exceeds 6 m s-1, only does the σ0 in Ku band slightly increase by 0.2-0.5 dB for thick oil. The study shows that high-resolution altimeter data can certainly help better evaluate the thickness of oil spill, particularly at low wind speeds. © 2017. American Geophysical Union

Using satellite altimetry and tide gauges for storm surge warning

The combination of the coarse temporal sampling by satellite altimeters in the deep ocean with the high temporal sampling at sparsely located tide gauges along the coast has been used to improve the forecast of high water for the North Sea along the Danish Coast and for the northeast coast of Australia. For both locations we have tried to investigate the possibilities and limitations of the use of satellite altimetry to capture high frequency signals (surges) using data from the past 20 years. The two regions are chosen to represent extra-tropical and tropical storm surge conditions. We have selected several representative high water events on the two continents based on tide gauge recordings and investigated the capability of satellite altimetry to capture these events in the sea surface height data. Due to the lack of recent surges in the North Sea we focused on general high water level and found that in the presence of two or more satellites we could capture more than 90% of the high water sea level events. In the Great Barrier Reef section of the northeast Australian coast, we have investigated several large tropical cyclones; one of these being Cyclone Larry, which hit the Queensland coast in March 2006 and caused both loss of lives as well as huge devastation. Here we demonstrate the importance of integrating tide gauges with satellite altimetry for forecasting high water at the city of Townsville in northeast Australia

Spatio-Temporal Variability of Annual Sea Level Cycle in the Baltic Sea

In coastal and semi-enclosed seas, the mean local sea level can significantly influence the magnitude of flooding in inundation areas. Using the cyclostationary empirical orthogonal function (CSEOF) method, we examine the spatial patterns and temporal variations of annual sea level cycle in the Baltic Sea based on satellite altimetry data, tide gauge data, and regional model reanalysis during 1993 and 2014. All datasets demonstrate coherent spatial and temporal annual sea level variability, although the model reanalysis shows a smaller interannual variation of annual sea level amplitude than other datasets. A large annual sea level cycle is observed in the Baltic Sea, except in the Danish straits from December to February. Compared with altimetry data, tide gauge data exhibit a stronger annual sea level cycle in the Baltic Sea (e.g., along the coasts and in the Gulf of Finland and the Gulf of Bothnia), particularly in the winter. Moreover, the maps of the maximum and minimum annual sea level amplitude imply that all datasets underestimate the maximum annual sea level amplitude. Analysis of the atmospheric forcing factors (e.g., sea level pressure, North Atlantic Oscillation (NAO), winds and air temperature), which may contribute to the interannual variation of the annual sea level cycle shows that both the zonal wind and winter NAO (e.g., from December to March) are highly correlated with the annual cycle variations in the tide gauge data in 1900–2012. In the altimetry era (1993–2014), all the atmospheric forcing factors are linked to the annual sea level cycle variations, particularly in 1996, 2010 and 2012, when a significant increase and drop of annual sea level amplitude are observed from all datasets, respectively

A new wind-wave spectrum model for deep water

181-194With the statistical relationships and equations, a new wind wave spectrum model for deep water is proposed in this study. In the new model, the total spectral energy level, the location of the maximum spectral energy (represented by location of spectral peak), and the width character of energy distribution (represented by the spectral steepness) at high frequencies located to the right of spectral peak of wind waves are all determined by the two basic parameters, i.e., the wind speed and the inverse wave age. The statistical relationships also show that with the same wind speed and wave age, the steepness of the wind wave spectrum at high frequencies located to the right of the spectral peak for field case is different from that for laboratory case. This is the main difference between field wind wave spectrum and laboratory spectrum. With the inverse spectral width, the new model is more appropriate to describe the real wind wave status. Compared with measurements in the Black Sea, the model calculated zeroth spectral moment m0 and the spectral width are in both good agreements with measured data. Furthermore, the new model can match elevation spectrum data obtained by four-frequency microwave radar and other field measurements fairly well. The new model can describe better and explain the influence of the wind speed and wave age on the energy distribution of developing wind waves generated in open ocean, also it plays a significant role in the study of oceanic microwave remote sensing, especially for understanding the uncertainty of retrieved ocean environment variables