Numerical study on signatures of atmospheric convective cells in radar images of the ocean

Current and wind variations at the ocean surface can give rise to a modulation of the sea surface roughness and thus become visible in radar images. The discrimination between radar signatures of oceanic and atmospheric phenomena can be quite difficult, since signatures of different origin can have very similar shapes and magnitudes and are often superimposed upon each other. In this work we employ a numerical radar imaging model for an investigation of typical properties of radar signatures of atmospheric convective cells and of theoretical differences between such atmospherically induced radar signatures and those of oceanic phenomena. We show that main characteristics of observed multifrequency/multipolarization radar signatures of atmospheric convective cells over the Gulf Stream are reproduced quite well by the proposed model. This encourages us to vary wind and radar parameters systematically in order to get a general overview of the dependency of atmospherically induced radar signatures on these parameters. Finally, we compare typical characteristics of radar signatures of atmospheric and oceanic phenomena, and we present simulated radar images of a scenario of superimposed atmospheric convective cells and oceanic internal waves. We show that the proposed model supports the experimental finding that radar signatures of oceanic phenomena are stronger at horizontal (HH) than at vertical (VV) polarization, while atmospherically induced radar signatures are better visible at VV polarization

Evaluation of a semi-analytical approach to the retrieval of water quality parameters from optical data in European coastal Case-II waters

This work addresses the retrieval of the three water quality parameters chlorophyll-a, yellow substance and suspended particulate matter from spectra of remote sensing reflectance in European coastal waters. We study the suitability of a semi-analytical algorithm for the retrieval of these parameters in coastal waters to investigate the validity of radiative transfer theory and bio-optical models that have been developed primarily for open ocean waters. To obtain water quality parameters from reflectance measurements we employ a non-linear inversion method (Gauss-Newton). Algorithm parameters are established to ensure convergence of the method and reduce trapping by local minima. The developed algorithm is then evaluated with the help of a case-specific sensitivity analysis that reveals strengths and weaknesses with respect to measurement errors and inaccuracies of the bio-optical models on which the algorithm is based. In order to establish the validity of the results, a second sensitivity analysis is carried out based on the analysis of normalised partial derivatives of the algorithm's central equation. The algorithm is then applied to an extensive in situ data set consisting of 447 high-resolution spectra of remote sensing reflectance and water quality parameters from a range of European coastal waters, acquired in the framework of three different projects. Given the different measurement techniques within the various projects, it is not surprising that the algorithm performs poorly for the complete data set. Studying the regional subsets individually yields improved results in some cases, suggesting potential for developing regionally specific algorithms on the basis of dedicated tuning. The complete failure of the algorithm in other regions displays the shortcomings of the methodology. It is shown that, in some cases, the forward model fails to describe the optical characteristics encountered producing a pronounced mismatch between calculated and measured reflectance spectra in both spectral shape and magnitude. In other regions the spectral shape is largely reproduced by the model but a mismatch in magnitude results in failure of the inversion procedure. However, the most fundamental problem encountered is the non-uniqueness of the reflectance inversion process for some spectra. Improved bio-optical models and dedicated measurement campaigns in coastal waters are a crucial requirement to resolve this problem for future regional applications of semi-analytical algorithms. We point out the optical characteristics of favourable and unfavourable conditions for the retrieval of water quality parameters and provide some guidelines to future measurements of optical properties of coastal waters

On the remote sensing of oceanic and atmospheric convection in the Greenland Sea by synthetic aperture radar

In this paper we discuss characteristic properties of radar signatures of oceanic and atmospheric convection features in the Greenland Sea. If the water surface is clean (no surface films or ice coverage), oceanic and atmospheric features can become visible in radar images via a modulation of the surface roughness, and their radar signatures can be very similar. For an unambiguous interpretation and for the retrieval of quantitative information on current and wind variations from radar imagery with such signatures, theoretical models of current and wind phenomena and their radar imaging mechanisms must be utilized. We demonstrate this approach with the analysis of some synthetic aperture radar (SAR) images acquired by the satellites ERS-2 and RADARSAT-1. In once case, an ERS-2 SAR image an a RADARSAT-1 ScanSAR image exhibit pronounced cell-like signatures with length scales on the order of 10-20 km and modulation depths of about 5-6 dB and 9-10 dB, respectively. Simulations with a numerical SAR imagaing model and various input current and wind fields reveal that the signatures in both images can be expained consistently by wind variations on the order of±2.5 ms, but not by surface current variations on realistic orders of magnitude. Accordingly, the observed features must be atmospheric convection cells. This is confirmed by visible typical cloud patterns in a NOAA AVHRR image of the test scenario. In another case, the presence of an oceanic convective chimney is obvious from in situ data, but no signatures of it are visible in an ERS-2 SAR image. We show by numerical simulations with an oceanic convection model and our SAR imaging model that this is consistent with theoretical predictions, since the current gradients associated with the observed chimney are not sufficiently strong to give rise to significant signatures in an ERS-2 SAR image under the given conditions. Further model results indicate that it should be generally difficult to observe oceanic convection features in the Greenland Sea with ERS-2 or RADARSAT-1 SAR, since their signatures resulting from pure wave-current interaction will be too weak to become visible in the noisy SAR images in most cases. This situation will improve with the availability of future high-resolution SARs such as RADARSAT-2 SAR in fine resolution mode (2004) and TerraSAR-X (2005) which will offer significantly reduced speckle noise fluctuations at comparable spatial resolutions and thus a much better visibility of small image variations on spatial scales on the order of a few hundred meters

A new interpretation of multifrequency/multipolarization radar signatures of the Gulf Stream front

Radar signatures which are observed on SIR-C/X-SAR multifrequency/multipolarization synthetic aperture radar images of the Gulf Stream off the U.S. east coast are compared with results of simulations with a numerical radar imaging model. Based on in situ data, current and wind variations are included into the model as well as a variation of the thermal stability of the marine atmospheric boundary layer across the Gulf Stream front. According to our model predictions, all of these parameter variations can cause radar signatures of similar shape and modulation depth. But, due to specific dependencies of radar signatures on variations of surface currents and winds, we show that it is possible to distinguish between radar signatures of oceanic and atmospheric origin in multifrequency/multipolarization images and to estimate the corresponding current and wind variations independently. For one set of radar images we derive a most likely scenario of oceanic and atmospheric parameters during the time of the image acquisition for which good overall agreement between observed and simulated radar signatures is obtained at most radar channels

A sea-state dependent parameterization of whitecapping and air-sea gas transfer velocities (abstract of paper presented at the EGU General Assembly 2005, Vienna, 24-29 April 2005)

A parameterization of whitecapping that depends on sea state in addition to the friction velocity of the wind is justified in terms of the energetics of wind waves. This new parameterization has implications for processes wholly or partly dependent on whitecapping including sea-salt production and air-sea gas transfer. A parameterization of gas transfer velocities is derived from a previous model modified by the sea-state dependent parameterization of whitecapping. This new model is evaluated. The new model provides a rationale for the divergence of earlier gas transfer coefficient models, giving due consideration to the sea-state conditions prevalent in the underlying data sets. Contemporary gas transfer is evaluated over the globe at seasonal and regional resolutions (up to monthly and 1 degree) for both the new and traditional parameterisations using both reanalysis products (ECMWF ERA40) and earth observation (scatterometer and altimeter) products. The new model implies mean global transfer velocities, mean global exchange coefficients and a net global carbon dioxide sink broadly in line with previous estimates but with significant differences in detail. The sensitivity of the net carbon dioxide sink to the balance of non-whitecapping and whitecapping components of gas transfer is high. Regional differences in gas transfer between traditional formulations and the new model are substantial. Whitecapping in the North Atlantic is notable for strong inter-annual variability driven primarily by the high sensitivity of wave heights to the North Atlantic Oscillation

Synergy between synthetic aperture radar and other sensors for the remote sensing of the ocean

Over the last decades, satellite remote sensing has proved to be a valuable and effective tool for monitoring physical and biological ocean processes. However there are cases where data from one remote sensor alone cannot be interpreted unambiguously. In these situations the combination of data from different sensors can help to understand the observed processes due to the combined benefits of the various strengths and advantages of individual instruments. This paper illustrates the potential of synergy between synthetic aperture radar data and data from thermal and optical satellite sensors. Different aspects of oceanic and atmospheric fronts, eddies, upwelling, internal waves and surface films are imaged by the sensors and combined data give a broader picture of the physical processes involved. While the strengths of synergy are demonstrated in several examples, more frequent coincidence of data from existing and future sensors will be necessary before the benefits of synergy occur on an operational basis

Der deutsche Stahltrust

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