Ocean wave imaging mechanism by imaging radar

Analytical representations of the high frequency spectra of ocean wave and its variation due to the variation of ocean surface current are derived from the wave-number spectrum balance equation. The ocean surface imaging formulation of real aperture radar (RAR) is given using electromagnetic wave backscattering theory of ocean surface and the modulations of ocean surface winds, currents and their variations to RAR are described. A general representation of the phase modulation induced by the ocean surface motion is derived according to standard synthetic aperture radar (SAR) imaging theory. The detectability of ocean current and sea bottom topography by imaging radar is discussed. The results constitute the theoretical basis for detecting ocean wave fields, ocean surface winds, ocean surface current fields, sea bottom topography, internal wave and so on.     

机载探地雷达数值模拟及逆时偏移成像

机载探地雷达可以用于人类无法到达的危险地区、植被严重覆盖的地下目标体探测,然而由于机载探地雷达的特殊性,影响机载探地雷达探测效果的因素包括天线的极化方向、天线的飞行高度以及地表粗糙度等.为了研究这些影响因素与探测效果之间的关系,用三维时间域有限差分模拟电磁波的传播过程,以沙漠地区地下空洞掩体的机载探地雷达探测为实例,分别模拟了不同天线极化方向、天线高度及地表粗糙度情况下的机载探地雷达剖面,分析了各因素对机载探地雷达探测地下空洞目标体的影响.天线极化方向与目标体走向垂直更有利于地下目标体探测;天线距离地表越近,可以获得更高分辨率的雷达剖面;沙漠地表起伏越大,雷达剖面中的散射杂波能量越强,浅部地下目标体信号容易被掩盖.为了消除起伏地形造成的散射杂波,提出用逆时偏移成像技术对共炮集机载探地雷达数据进行偏移成像,成像结果优于基尔霍夫偏移成像结果.     

基于正则化方法的高频地波雷达海浪方向谱反演

提出了一种从高频地波雷达海面回波谱中提取海浪方向谱的新方法:基于高频电波海洋探测基本原理将线性化后的非线性积分方程离散为矩阵方程组,通过引入正则化数学模型将不适定方程转化为正规方程,然后采用奇异值分解法求解.对于正则化方法中正则化参数,采用L曲线法来确定.为了验证本文算法的有效性,分别在单部雷达和双部雷达探测下进行了不同噪声水平下的数值模拟,结果表明了该正则化反演方法的有效性.文中还给出了实测数据分析初步结果.该算法的工程性应用还需进一步研究.对于实际的地波雷达海浪反演具有良好的应用前景.     

The selection of artificial corner reflectors based on RCS analysis

Artificial corner reflectors (ACRs) are widely applicable in monitoring terrain change via interferometric synthetic aperture radar (InSAR) remote sensing techniques. Many different types are available. The choice of the most appropriate ones has recently attracted scholarly attentions. Based on physical optics methods, via calculating the radar cross section (RCS) values (the higher the value, the better the detectability), the current study tested three ACRs, i.e., triangular pyramidal, rectangular pyramidal and square trihedral ACRs. Our calculation suggests that the square trihedral ACR produces the largest RCS but least tolerance towards incident radar ray’s deviation from optimal angle. The triangular pyramidal trihedral ACR is the most geometrically stable ACR, and has the highest tolerance towards incident radar ray’s deviation. Its RCS values, however, are the least of the three. Due to the high cost of deploying ACRs in the fields, the physical optics method seems to provide a viable way to choose appropriate ACRs.     

High-resolution atmospheric forcing for regional oceanic model: the Iroise Sea

This study was aimed at modeling, as realistically as possible, the dynamics and thermodynamics of the Iroise Sea by using the Model for Applications at Regional Scale (MARS), a regional ocean 3D model. The horizontal resolution of the configuration in use is 2 km with 30 vertical levels. The 3D model of the Iroise Sea is embedded in a larger model providing open boundary conditions. As regards the atmospheric forcing, the originality of this study is to force the regional ocean model with the high-resolution (6 km) regional meteorological model, Weather Research and Forecasting (WRF). In addition, as the air surface temperature is highly sensitive to the sea surface temperature (SST), this regional meteorological model is improved by taking into account a regional climatologic SST to compute meteorological parameters. By allowing a better coherence between the SST and the temperature of the atmospheric boundary layer while giving a more realistic representation of heat fluxes exchanged at the air/sea interface, this forcing constitutes a noticeable improvement of the Iroise Sea modeling. The different sensitivity tests discussed here pinpoint the importance of entering, in WRF, SST data of sufficiently high quality before the computation of meteorological forcing when the aim is a study of dynamics and thermodynamics far away from the coast. On the other hand, when the target is the reproduction of coastal small-scale features in Iroise Sea modeling, the resolution of the meteorological forcing and the quality of SST are both paramount. The simulation of reference was carried out throughout the Summer and Autumn of year 2005 to allow comparisons with a campaign of surface current measurements by high-frequency radars conducted at the same period.     

The influence of rainfall on PR radar measurement of ocean surface wind speed and its calibration

Rain can significantly degrade the wind vector retrieval from Precipitation Radar(PR) by three mechanisms, namely, two-way rain attenuation, rain volume-backscattering, and ocean surface roughening from the rain splash effect. Here we first derive the radar equation for PR in rainy conditions. Then we use the rain attenuation model for Ku band, volume backscatter model for spherical raindrops and PR–TMI(TRMM Microwave Imager, TMI) matchup datasets from June to August in 2010 to solve the radar equation, and quantitatively analyze the influence of rainfall on PR radar measurement of ocean surface wind speed. Our results show that the significant effect of rain on radar signal is dominated by two-way rain attenuation and rain splash effect, and the effect of rain volume-backscattering is relatively the weakest, which can even be neglected in rain-weak conditions. Moreover, both the two-way rain attenuation and rain splash effect increase with the increasing of integration rain rate and incident angle. Last, we combine volume-backscattering effect and splash effect into a simple phenomenological model for rain calibration and select three typhoon cases from June to August in 2012 to verify the accuracy of this model. Before calibration, the mean difference and mean square error(MSE) between PR-observed ? 0 and wind-induced ? 0 are about 2.95 dB and 3.10 dB respectively. However, after calibration, the mean difference and MSE are reduced to 0.64 dB and 1.61 dB respectively. The model yields an accurate calibration for PR near-nadir normalized radar cross section(NRCS) in rainy conditions.     

Detection of macroalgae blooms by complex SAR imagery

Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean.     

Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations. Part I: Surface fluxes

A mesoscale non-hydrostatic atmospheric model has been coupled with a mesoscale oceanic model. The case study is a four-day simulation of a strong storm event observed during the SEMAPHORE experiment over a 500 × 500 km² domain. This domain encompasses a thermohaline front associated with the Azores current. In order to analyze the effect of mesoscale coupling, three simulations are compared: the first one with the atmospheric model forced by realistic sea surface temperature analyses; the second one with the ocean model forced by atmospheric fields, derived from weather forecast re-analyses; the third one with the models being coupled. For these three simulations the surface fluxes were computed with the same bulk parametrization. All three simulations succeed well in representing the main oceanic or atmospheric features observed during the storm. Comparison of surface fields with in situ observations reveals that the winds of the fine mesh atmospheric model are more realistic than those of the weather forecast re-analyses. The low-level winds simulated with the atmospheric model in the forced and coupled simulations are appreciably stronger than the re-analyzed winds. They also generate stronger fluxes. The coupled simulation has the strongest surface heat fluxes: the difference in the net heat budget with the oceanic forced simulation reaches on average 50 Wm⁻² over the simulation period. Sea surface-temperature cooling is too weak in both simulations, but is improved in the coupled run and matches better the cooling observed with drifters. The spatial distributions of sea surface-temperature cooling and surface fluxes are strongly inhomogeneous over the simulation domain. The amplitude of the flux variation is maximum in the coupled run. Moreover the weak correlation between the cooling and heat flux patterns indicates that the surface fluxes are not responsible for the whole cooling and suggests that the response of the ocean mixed layer to the atmosphere is highly non-local and enhanced in the coupled simulation.     

Estimating the 4DVAR analysis error of GODAE products

We explore the ocean circulation estimates obtained by assimilating observational products made available by the Global Ocean Data Assimilation Experiment (GODAE) and other sources in an incremental, four-dimensional variational data assimilation system for the Intra-Americas Sea. Estimates of the analysis error (formally, the inverse Hessian matrix) are computed during the assimilation procedure. Comparing the impact of differing sea surface height and sea surface temperature products on both the final analysis error and difference between the model state estimates, we find that assimilating GODAE and non-GODAE products yields differences between the model and observations that are comparable to the differences between the observation products themselves. While the resulting analysis error estimates depend on the configuration of the assimilation system, the basic spatial structures of the standard deviations of the ocean circulation estimates are fairly robust and reveal that the assimilation procedure is capable of reducing the circulation uncertainty when only surface data are assimilated.     

Coastal sea level variability in the US West Coast Ocean Forecast System (WCOFS)

Sea level variability along the US West Coast is analyzed using multi-year time series records from tide gauges and a high-resolution regional ocean model, the base of the West Coast Ocean Forecast System (WCOFS). One of the metrics utilized is the frequency of occurrences when model prediction is within 0.15 m from the observed sea level, F. A target level of F?=?90% is set by an operational agency. A combination of the tidal sea level from a shallow water inverse model, inverted barometer (IB) term computed using surface air pressure from a mesoscale atmospheric model, and low-pass filtered sea level from WCOFS representing the effect of coastal ocean dynamics (DYN) provides the most straightforward approach to reaching levels F>80%. The IB and DYN components each add between 5 and 15% to F. Given the importance of the DYN term bringing F closer to the operational requirement and its role as an indicator of the coastal ocean processes on scales from days to interannual, additional verification of the WCOFS subtidal sea level is provided in terms of the model-data correlation, standard deviation of the band-pass filtered (2–60 days) time series, the annual cycle amplitude, and alongshore sea level coherence in the range of 5–120-day periods. Model-data correlation in sea level increases from south to north along the US coast. The rms amplitude of model sea level variability in the 2–60-day band and its annual amplitude are weaker than observed north of 42 N, in the Pacific Northwest (PNW) coast region. The alongshore coherence amplitude and phase patterns are similar in the model and observations. Availability of the multi-year model solution allows computation and analysis of spatial maps of the coherence amplitude. For a reference location in the Southern California Bight, relatively short-period sea level motions (near 10 days) are incoherent with those north of the Santa Barbara Channel (in part, due to coastal trapped wave scattering and/or dissipation). At a range of periods around 60 days, the coastal sea level in Southern California is coherent with the sea surface height (SSH) variability over the shelf break in Oregon, Washington, and British Columbia, more than with the coastal SSH at the same latitudes.     

Spectral analysis of mean flow and turbulence forced by waves in a horizontally homogeneous zone of the Iroise sea

The 1D version of the Model for Applications at Regional Scale is used to parameterize the effects of sea surface waves in 2D in a horizontally homogeneous offshore zone of the Iroise sea. Here we present the first simulation of the Iroise sea including sea surface waves forcing, and more generally, the first study of a boundary layer including the Hasselmann force with a tidal wave. We use a single equation turbulence closure based on a non-local diagnosis for energetic and dissipation length scales. The turbulent energy flux at the surface due to whitecaps and the Hasselmann force induced by Stokes drift are assessed using the whole sea surface waves spectrum given by the Wave Watch Third generation model. The ability of the parameterization to reproduce surface currents over a period of 1 year (2007) is tested with high frequency radar using spectral and time-frequency analysis. One problem with 1D modelling, corresponding to overestimation of current oscillating at inertial frequency is illustrated by comparing 1D and 3D simulations. We found an overall improvement by including the Hasselmann force mainly within the bandwidth of less than one cycle per day to one cycle per day for surface currents. Turbulence is induced by whitecaps decaying rapidly below the ocean surface but the mixed layer below 40 m is deeper due to waves breaking on the sea surface.     

Simulation and detection of tsunami signatures in ocean surface currents measured by HF radar

High-frequency (HF) surface wave radars provide the unique capability to continuously monitor the coastal environment far beyond the range of conventional microwave radars. Bragg-resonant backscattering by ocean waves with half the electromagnetic radar wavelength allows ocean surface currents to be measured at distances up to 200 km. When a tsunami propagates from the deep ocean to shallow water, a specific ocean current signature is generated throughout the water column. Due to the long range of an HF radar, it is possible to detect this current signature at the shelf edge. When the shelf edge is about 100 km in front of the coastline, the radar can detect the tsunami about 45 min before it hits the coast, leaving enough time to issue an early warning. As up to now no HF radar measurements of an approaching tsunami exist, a simulation study has been done to fix parameters like the required spatial resolution or the maximum coherent integration time allowed. The simulation involves several steps, starting with the Hamburg Shelf Ocean Model (HAMSOM) which is used to estimate the tsunami-induced current velocity at 1 km spatial resolution and 1 s time step. This ocean current signal is then superimposed to modelled and measured HF radar backscatter signals using a new modulation technique. After applying conventional HF radar signal processing techniques, the surface current maps contain the rapidly changing tsunami-induced current features, which can be compared to the HAMSOM data. The specific radial tsunami current signatures can clearly be observed in these maps, if appropriate spatial and temporal resolution is used. Based on the entropy of the ocean current maps, a tsunami detection algorithm is described which can be used to issue an automated tsunami warning message.     

“龙王”台风期间高频地波雷达数据分析

OSMAR2003岸基高频地波雷达系统由武汉大学电波传播实验室研制并于2005年应用于福建沿海,能够全天候、大面积探测台湾海峡内海洋表面动力学要素. 本文首先将0519号台风期间高频地波雷达的测量数据与局部点的浮标数据对比，然后又对大面积海域内雷达测量风场与uikSCAT卫星遥感数据进行了对比分析. 结果表明高频地波雷达较好地反映了台风期间台湾海峡内风场的空间分布及其发展变化情况，具有一定的灾害性海洋天气监测能力.     

Air–sea interactions during strong winter extratropical storms

A high-resolution, regional coupled atmosphere–ocean model is used to investigate strong air–sea interactions during a rapidly developing extratropical cyclone (ETC) off the east coast of the USA. In this two-way coupled system, surface momentum and heat fluxes derived from the Weather Research and Forecasting model and sea surface temperature (SST) from the Regional Ocean Modeling System are exchanged via the Model Coupling Toolkit. Comparisons are made between the modeled and observed wind velocity, sea level pressure, 10 m air temperature, and sea surface temperature time series, as well as a comparison between the model and one glider transect. Vertical profiles of modeled air temperature and winds in the marine atmospheric boundary layer and temperature variations in the upper ocean during a 3-day storm period are examined at various cross-shelf transects along the eastern seaboard. It is found that the air–sea interactions near the Gulf Stream are important for generating and sustaining the ETC. In particular, locally enhanced winds over a warm sea (relative to the land temperature) induce large surface heat fluxes which cool the upper ocean by up to 2 °C, mainly during the cold air outbreak period after the storm passage. Detailed heat budget analyses show the ocean-to-atmosphere heat flux dominates the upper ocean heat content variations. Results clearly show that dynamic air–sea interactions affecting momentum and buoyancy flux exchanges in ETCs need to be resolved accurately in a coupled atmosphere–ocean modeling framework.     

Correcting surface winds by assimilating high-frequency radar surface currents in the German Bight

Surface winds are crucial for accurately modeling the surface circulation in the coastal ocean. In the present work, high-frequency radar surface currents are assimilated using an ensemble scheme which aims to obtain improved surface winds taking into account European Centre for Medium-Range Weather Forecasts winds as a first guess and surface current measurements. The objective of this study is to show that wind forcing can be improved using an approach similar to parameter estimation in ensemble data assimilation. Like variational assimilation schemes, the method provides an improved wind field based on surface current measurements. However, the technique does not require an adjoint, and it is thus easier to implement. In addition, it does not rely on a linearization of the model dynamics. The method is validated directly by comparing the analyzed wind speed to independent in situ measurements and indirectly by assessing the impact of the corrected winds on model sea surface temperature (SST) relative to satellite SST.     

Regional patterns of observed sea level change: insights from a 1/4° global ocean/sea-ice hindcast

A global eddy-admitting ocean/sea-ice simulation driven over 1958–2004 by daily atmospheric forcing is used to evaluate spatial patterns of sea level change between 1993 and 2001. In the present study, no data assimilation is performed. The model is based on the Nucleus for European Models of the Ocean code at the 1/4° resolution, and the simulation was performed without data assimilation by the DRAKKAR project. We show that this simulation correctly reproduces the observed regional sea level trend patterns computed using satellite altimetry data over 1993–2001. Generally, we find that regional sea level change is best simulated in the tropical band and northern oceans, whereas the Southern Ocean is poorly simulated. We examine the respective contributions of steric and bottom pressure changes to the total regional sea level changes. For the steric component, we analyze separately the contributions of temperature and salinity changes as well as upper and lower ocean contributions. Generally, the model results show that most regional sea level changes arise from temperature changes in the upper 750 m of the ocean. However, contributions of salinity changes and deep steric changes can be locally important. We also propose a map of ocean bottom pressure changes. Finally, we assess the robustness of such a model by comparing this simulation with a second simulation performed by MERCATOR-Ocean based on the same core model, but differing by its short length of integration (1992–2001) and its surface forcing data set. The long simulation presents better performance over 1993–2001 than the short simulation, especially in the Southern Ocean where a long adjustment time seems to be needed. In memory of my little brother Jean-Eudes, whose thirst for science filled out the rich discussions we had about my investigations and his job as user-service provider for MERCATOR-Ocean.     

Relationship between thermally forced surface wind and sea surface temperature gradient

An important part of the influence of the oceans on the atmosphere is through direct radiation, sensible heat flux and release of latent heat of evaporation, whereby all of these processes are directly related to the surface temperature of the oceans. A main effect of the atmosphere on the oceans is through momentum exchange at the air-ocean interface, and this process is directly related to the surface wind stress. The sea surface temperature (SST) and the surface wind stress are the two important components in the air-ocean system. If SST is given, a thermally forced boundary layer atmospheric circulation can be simulated. On the other hand, if the surface wind stress is given, the wind-driven ocean waves and ocean currents can be computed.The relationship between SST and surface wind is a coupling of the atmosphere and the oceans. It changes a one-way effect (ocean mechanically driven by atmosphere, or atmosphere thermally forced by oceans) into two-way air-sea interactions. Through this coupling the SST distribution, being an output from an ocean model, leads to the thermally forced surface winds, which feeds back into the ocean model as an additional forcing.Based on Kuo's planetary boundary layer model a linear algebraic equation is established to link the SST gradient with the thermally forced surface wind. The surface wind blows across the isotherms from cold to warm region with some deflection angle to the right (left) in the Northern (Southern) Hemisphere. Results from this study show that the atmospheric stratification reduces both the speed and the deflection angle of the thermally forced wind, however, the Coriolis' effect increases the wind speed in stable atmosphere (Ri>10^–4) and increases the deflection angle.     

MOM4_L40模式对全球海洋CFC-11分布的模拟及其通风能力评估

CFC-11是评估全球海洋环流模式的一个重要工具,海水中溶解的CFC-11被用来分析全球海洋模式的通风模拟.本文在中国气象局国家气候中心发展的40层全球海洋环流模式(MOM4_L40)增加了示踪物CFC-11模块,然后利用该模式研究了CFC-11在全球海洋中的分布,并评估了模式的通风能力.对CFC-11的海表浓度、柱总含量以及大洋剖面的垂直浓度分布和渗透深度进行了分析,结果表明,与观测相比,模式较好地再现了CFC-11在海洋表面的水平分布特征,CFC-11主要储存区位于西北大西洋、副热带北太平洋及南大洋,其浓度分布与温度分布梯度相反.沿三个大洋的5个剖面的CFC-11垂直分布模拟也与观测基本吻合.模式模拟的CFC-11分布情况与全球平均经向流函数吻合,在南大洋模拟效果更加接近观测值,深海模拟效果较好,渗透深度接近观测.同时,模拟与观测相比也存在偏差.比如在北大西洋主要的存储区域,模式低估了CFC-11的吸收,这与高纬的CFC-11向低纬过度输送有关,可能是受温盐环流和强迫资料的影响.总体来说,MOM_L40模式模拟大洋吸收的CFC-11总量是理想的,通过模拟被动示踪物CFC-11很好地再现了海洋的通风能力.     

Benchmarking the mesoscale variability in global ocean eddy-permitting numerical systems

The role of data assimilation procedures on representing ocean mesoscale variability is assessed by applying eddy statistics to a state-of-the-art global ocean reanalysis (C-GLORS), a free global ocean simulation (performed with the NEMO system) and an observation-based dataset (ARMOR3D) used as an independent benchmark. Numerical results are computed on a 1/4 ^° horizontal grid (ORCA025) and share the same resolution with ARMOR3D dataset. This “eddy-permitting” resolution is sufficient to allow ocean eddies to form. Further to assessing the eddy statistics from three different datasets, a global three-dimensional eddy detection system is implemented in order to bypass the need of regional-dependent definition of thresholds, typical of commonly adopted eddy detection algorithms. It thus provides full three-dimensional eddy statistics segmenting vertical profiles from local rotational velocities. This criterion is crucial for discerning real eddies from transient surface noise that inevitably affects any two-dimensional algorithm. Data assimilation enhances and corrects mesoscale variability on a wide range of features that cannot be well reproduced otherwise. The free simulation fairly reproduces eddies emerging from western boundary currents and deep baroclinic instabilities, while underestimates shallower vortexes that populate the full basin. The ocean reanalysis recovers most of the missing turbulence, shown by satellite products , that is not generated by the model itself and consistently projects surface variability deep into the water column. The comparison with the statistically reconstructed vertical profiles from ARMOR3D show that ocean data assimilation is able to embed variability into the model dynamics, constraining eddies with in situ and altimetry observation and generating them consistently with local environment.     

Arctic sea ice thickness variations from CryoSat-2 satellite altimetry data

Arctic sea ice plays an important role in Earth's climate and environmental system. Sea ice thickness is one of the most important sea ice parameters. Accurately obtaining the sea ice thickness and its changes has great significance to Arctic and global change research. Satellite altimeters can be used to derive long-term and large-scale changes in sea ice thickness. The leads detection is vital in sea ice thickness estimation by using satellite altimetry. Different leads detection methods are compared with remote sensing images, and results show that the detection method that uses waveform parameters can obtain improved results. The model for the conversion of freeboard to thickness is optimized by considering the incomplete penetration of snow for radar altimeters. We derive the estimates of the Arctic sea ice thickness for November 2010 to December 2019 by using the CryoSat-2 altimetry data. The sea ice thickness from the IceBridge and draft data from the upward-looking sonar are used to validate our thickness results. Validations show that the accuracy of our thickness estimates is within 0.2 m. Variations in the Arctic sea ice thickness are analyzed using the PIOMAS model and air and sea surface temperatures. A sharp increase in sea ice thickness is found in 2014.