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

Satellite observations of mesoscale features in lower Cook Inlet and Shelikof Strait, Gulf of Alaska

The Seasat satellite launched in Summer 1978 carried a synthetic aperture radar (SAR). Although Seasat failed after 105 days in orbit, it provided observations that demonstrate the potential to examine and monitor upper oceanic processes. Seasat made five passes over lower Cook Inlet and Shelikof Strait, Alaska, during Summer 1978. SAR images from the passes show oceanographic features, including a meander in a front, a pair of mesoscale eddies, and internal waves. These features are compared with contemporary and representative images from a satellite-borne Advanced Very High Resolution Radiometer (AVHRR) and Coastal Zone Color Scanner (CZCS), with water property data, and with current observations from moored instruments. The results indicate that SAR data can be used to monitor mesoscale oceanographic features

Synergic use of SAR imagery and high resolution atmospheric model to estimate marine wind fields : an application in presence of an atmospheric gravity wave episode.

A study aimed at retrieving sea surface wind fields of semi-enclosed basins from combined use of SAR imagery and a high resolution mesoscale numerical atmospheric model, is presented. Two consecutive ERS-2 SAR frames and a set of NOAA/AVHRR and MODIS images acquired over the North Tyrrhenian Sea on March 30, 2000 were used for the analysis. SAR wind speeds and directions at 10 m above the sea surface were retrieved using the semi-empirical backscatter models CMOD4 and CMOD-IFREMER. Surface wind vectors predicted by the meteorological ETA model were exploited as guess input to SAR wind inversion procedure. ETA is a three-dimensional, primitive equation, grid-point model currently operational at the National Centers for Environmental Prediction of the U.S. National Weather Service. The model was adapted to run with a resolution up to about 4.0 Km. It was found that the inversion methodology was not able to resolve wind speed modulations due to the action of an atmospheric gravity wave, called “lee wave”, which occurred in the analyzed area. A simple atmospheric wave propagation model was thus used to account for the SAR observed surface wind speed modulation. Synergy with ETA model outputs was further exploited in simulations where atmospheric parameters up-wind the atmospheric wave were provided as input to the lee wave propagation model

Atmospheric gravity waves in the Red Sea : a new hotspot

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Nonlinear Processes in Geophysics 18 (2011): 71-79, doi:10.5194/npg-18-71-2011.The region of the Middle East around the Red Sea (between 32° E and 44° E longitude and 12° N and 28° N latitude) is a currently undocumented hotspot for atmospheric gravity waves (AGWs). Satellite imagery shows evidence that this region is prone to relatively high occurrence of AGWs compared to other areas in the world, and reveals the spatial characteristics of these waves. The favorable conditions for wave propagation in this region are illustrated with three typical cases of AGWs propagating in the lower troposphere over the sea. Using weakly nonlinear long wave theory and the observed characteristic wavelengths we obtain phase speeds which are consistent with those observed and typical for AGWs, with the Korteweg-de Vries theory performing slightly better than Benjamin-Davis-Acrivos-Ono theory as far as phase speeds are concerned. ERS-SAR and Envisat-ASAR satellite data analysis between 1993 and 2008 reveals signatures consistent with horizontally propagating large-scale internal waves. These signatures cover the entire Red Sea and are more frequently observed between April and September, although they also occur during the rest of the year. The region's (seasonal) propagation conditions for AGWs, based upon average vertical atmospheric stratification profiles suggest that many of the signatures identified in the satellite images are atmospheric internal waves.This research was conducted with support from KAUST (King Abdullah University for Science and Technology) in collaboration with the Woods Hole Oceanographic Institution, Biology Department. Some support was also provided by a Treaty of Windsor Grant awarded by the British Council (Portugal)

Tropospheric phase delay in interferometric synthetic aperture radar estimated from meteorological model and multispectral imagery

ENVISAT Medium Resolution Imaging Spectrometer Instrument (MERIS) multispectral data and the mesoscale meteorological model MM5 are used to estimate the tropospheric phase delay in synthetic aperture radar (SAR) interferograms. MERIS images acquired simultaneously with ENVISAT Advanced Synthetic Aperture Radar data provide an estimate of the total water vapor content W limited to cloud-free areas based on spectral bands ratio (accuracy 0.17 g cm^(−2) and ground resolution 300 m). Maps of atmospheric delay, 2 km in ground resolution, are simulated from MM5. A priori pertinent cumulus parameterization and planetary boundary layer options of MM5 yield near-equal phase correction efficiency. Atmospheric delay derived from MM5 is merged with available MERIS W product. Estimates of W measured from MERIS and modeled from MM5 are shown to be consistent and unbiased and differ by ~0.2 g cm^(−2) (RMS). We test the approach on data over the Lebanese ranges where active tectonics might contribute to a measurable SAR signal that is obscured by atmospheric effects. Local low-amplitude (1 rad) atmospheric oscillations with a 2.25 km wavelength on the interferograms are recovered from MERIS with an accuracy of 0.44 rad or 0.03 g cm^(−2). MERIS water product overestimates W in the clouds shadow due to mismodeling of multiple scattering and underestimates W on pixels with undetected semitransparent clouds. The proposed atmospheric filter models dynamic atmospheric signal which cannot be recovered by previous filtering techniques which are based on a static atmospheric correction. Analysis of filter efficiency with spatial wavelength shows that ~43% of the atmospheric signal is removed at all wavelengths

A Marine Radar Wind Sensor

A new method for retrieving the wind vector from radar-image sequences is presented. This method, called WiRAR, uses a marine X-band radar to analyze the backscatter of the ocean surface in space and time with respect to surface winds. Wind direction is found using wind-induced streaks, which are very well aligned with the mean surface wind direction and have a typical spacing above 50 m. Wind speeds are derived using a neural network by parameterizing the relationship between the wind vector and the normalized radar cross section (NRCS). To improve performance, it is also considered how the NRCS depends on sea state and atmospheric parameters such as air–sea temperature and humidity. Since the signal-to-noise ratio in the radar sequences is directly related to the significant wave height, this ratio is used to obtain sea state parameters. All radar datasets were acquired in the German Bight of the North Sea from the research platform FINO-I, which provides environmental data such as wind measurements at different heights, sea state, air–sea temperatures, humidity, and other meteorological and oceanographic parameters. The radar-image sequences were recorded by a marine X-band radar installed aboard FINO-I, which operates at grazing incidence and horizontal polarization in transmit and receive. For validation WiRAR is applied to the radar data and compared to the in situ wind measurements from FINO-I. The comparison of wind directions resulted in a correlation coefficient of 0.99 with a standard deviation of 12.8°, and that of wind speeds resulted in a correlation coefficient of 0.99 with a standard deviation of 0.41 m s^−1. In contrast to traditional offshore wind sensors, the retrieval of the wind vector from the NRCS of the ocean surface makes the system independent of the sensors’ motion and installation height as well as the effects due to platform-induced turbulence

Observing Marine Pollution with Synthetic Aperture Radar

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Modeling of SAR signatures of shallow water ocean topography

A hydrodynamic/electromagnetic model was developed to explain and quantify the relationship between the SEASAT synthetic aperture radar (SAR) observed signatures and the bottom topography of the ocean in the English Channel region of the North Sea. The model uses environmental data and radar system parameters as inputs and predicts SAR-observed backscatter changes over topographic changes in the ocean floor. The model results compare favorably with the actual SEASAT SAR observed backscatter values. The developed model is valid for only relatively shallow water areas (i.e., less than 50 meters in depth) and suggests that for bottom features to be visible on SAR imagery, a moderate to high velocity current and a moderate wind must be present

Co-seismic deformation during the M_w 7.3 Aqaba earthquake (1995) from ERS-SAR interferometry

The M_w 7.3 1995 Aqaba earthquake is the largest instrumental earthquake along the Dead Sea Fault. We complement previous seismological studies by analyzing co‐seismic ground displacement from differential interferometry computed from ERS images spanning 3 different areas. They are compared with a synthetic model derived from seismological study. Only far‐field deformation related to the main sub‐event could be revealed because the near‐field area lies within the gulf. The interferometric data imply a 56 km long and 10 km wide fault segment, connecting the Elat Deep to the Aragonese Deep, which strikes N195°E and dips 65° to the west, with 2.1 m left‐lateral slip and a 15.5° rake indicating a slight normal component. The geodetic moment compares well with the seismic momen