A new parameterization of an empirical model for wind/ocean scatterometry

The power law form of the SEASAT A Scatterometer System (SASS) empirical backscatter-to-wind model function does not uniformly meet the instrument performance over the range 4 to 24 /ms. Analysis indicates that the horizontal polarization (H-Pol) and vertical polarization (V-Pol) components of the benchmark SASS1 model function yield self-consistent results only for a small mid-range of speeds at larger incidence angles, and for a somewhat larger range of speeds at smaller incidence angles. Comparison of SASS1 to in situ data over the Gulf of Alaska region further underscores the shortcomings of the power law form. Finally, a physically based empirical SASS model is proposed which corrects some of the deficiencies of power law models like SASS1. The new model allows the mutual determination of sea surface wind stress and wind speed in a consistent manner from SASS backscatter measurements

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

Wind speed retrieval from the Gaofen-3 synthetic aperture radar for VV- and HH-polarization using a re-tuned algorithm

In this study, a re-tuned algorithm based on the geophysical model function (GMF) C-SARMOD2 is proposed to retrieve wind speed from Synthetic Aperture Radar (SAR) imagery collected by the Chinese C-band Gaofen-3 (GF-3) SAR. More than 10,000 Vertical-Vertical (VV) and Horizontal-Horizontal (HH) polarization GF-3 images acquired in quad-polarization stripmap (QPS) and wave (WV) modes have been collected during the last three years, in which wind patterns are observed over open seas with incidence angles ranging from 18° to 52°. These images, collocated with wind vectors from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis at 0.125° resolution, are used to re-tune the C-SARMOD2 algorithm to specialize it for the GF-3 SAR (CSARMOD-GF). In particular, the CSARMOD-GF performs differently from the C-SARMOD2 at low-to-moderate incidence angles smaller than about 34°. Comparisons with wind speed data from the Advanced Scatterometer (ASCAT), Chinese Haiyang-2B (HY-2B) and buoys from the National Data Buoy Center (NDBC) show that the root-mean-square error (RMSE) of the retrieved wind speed is approximately 1.8 m/s. Additionally, the CSARMOD-GF algorithm outperforms three state-of-the-art methods – C-SARMOD, C-SARMOD2, and CMOD7 – that, when applied to GF-3 SAR imagery, generating a RMSE of approximately 2.0–2.4 m/s

Improving Sea-Surface Remote Sensing of Ocean Wind Vectors by Scatterometers

Though scatterometers have been used to sense global ocean surface wind vectors for over 40 years, there remain some significant shortcomings. The largest problems appear in retrieving the wind vector when the ocean is being driven by high wind speeds or when rain is present in the beam-illuminated volume. Geophysical model functions (GMFs) developed using data from high-wind events can improve retrievals at high wind speeds, but only if sufficient ground truth measurements exist in the scatterometer swath. Airborne scatterometers, such as the Imaging Wind and Rain Airborne Profiler (IWRAP) developed by the Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts Amherst (UMass), are well-suited for collecting such high-wind data, largely due to their abilities to reposition to areas of interest, sample the ocean surface on a small scale, and use complementary in-situ sensors. The IWRAP system is also able to investigate the effect of precipitation impact (the “splash effect”) on the sea surface normalized radar cross-section (NRCS), since it can discriminate between volume and surface effects of precipitation. This dissertation will improve upon the existing IWRAP GMF and quantify the effect of precipitation on wind vector retrievals. Additionally, IWRAP is used to observe the effects of Earth-incidence angle and polarization on the sea-surface radar backscatter, helping scatterometer GMFs to be applicable to other satellite sensors. IWRAP and collocated Stepped Frequency Microwave Radiometer (SFMR) data were gathered from 4 years of flight experiments. Using this data, the high-wind IWRAP GMF is extended to incidence angles near 22° at C- and Ku-band VV- and HH-polarization from 15 m s−1 to 45 m s−1. There is also a revision made to the higher harmonics of the GMF near 50° incidence, but the mean NRCS appears to be modeled appropriately. There is no splash effect observed in the mean NRCS or first harmonic at wind speeds from 15 m s−1 to 45 m s−1. The second harmonic shows some muted behavior in precipitation. Lastly, a wind speed dependence is observed in the VV/HH NRCS polarization ratio in both incidence angle and azimuth

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

Theoretical modeling of dual-frequency scatterometer response: improving ocean wind and rainfall effects

Ocean surface wind is a key parameter of the Earth’s climate system. Occurring at the interface between the ocean and the atmosphere, ocean winds modulate fluxes of heat, moisture and gas exchanges. They reflect the lower branch of the atmospheric circulation and represent a major driver of the ocean circulation. Studying the long-term trends and variability of the ocean surface winds is of key importance in our effort to understand the Earth’s climate system and the causes of its changes. More than three decades of surface wind data are available from spaceborne scatterometer/radiometer missions and there is an ongoing effort to inter-calibrate all these measurements with the aim of building a complete and continuous picture of the ocean wind variability. Currently, spaceborne scatterometer wind retrievals are obtained by inversion algorithms of empirical Geophysical Model Functions (GMFs), which represent the relationship between ocean surface backscattering coefficient and the wind parameters. However, by being measurement-dependent, the GMFs are sensor-specific and, in addition, they may be not properly defined in all weather conditions. This may reduce the accuracy of the wind retrievals in presence of rain and it may also lead to inconsistencies amongst winds retrieved by different sensors. Theoretical models of ocean backscatter have the big potential of providing a more general and understandable relation between the measured microwave backscatter and the surface wind field than empirical models. Therefore, the goal of our research is to understand and address the limitations of the theoretical modeling, in order to propose a new strategy towards the definition of a unified theoretical model able to account for the effects of both wind and rain. In this work, it is described our approach to improve the theoretical modeling of the ocean response, starting from the Ku-band (13.4 GHz) frequency and then broadening the analysis at C-band (5.3 GHz) frequency. This research has revealed the need for new understanding of the frequency-dependent modeling of the surface backscatter in response to the wind-forced surface wave spectrum. Moreover, our ocean wave spectrum modification introduced to include the influences of the surface rain, allows the interpretation/investigation of the scatterometer observations in terms not only of the surface winds but also of the surface rain, defining an additional step needed to improve the wind retrievals algorithms as well as the possibility to jointly estimate wind and rain from scatterometer observations

Characterization of surface radar cross sections at W-band at moderate incidence angles

This paper presents the results of a recent flight campaign conducted over the Great Lakes region and reports the first observations of the W-band normalized backscattered cross section ( σ0 ) for V and H polarization and the linear depolarization ratios (LDRs) from different types of surfaces at moderate incidence angles (<70°). For sea surfaces, while the observed σ0 behaves as previously reported at small incidence angles, it features a marked decrease with increasing incidence angles between 20° and 50°. There is a strong dependence of normalized backscattered cross sections both on the wind speed and on the wind direction, with larger values found in the presence of higher wind speeds and when the radar antenna is looking upwind. This is in line with theoretical models (though models tend to overpredict the range of variability at a given incidence angle) and with observations at lower frequencies. The LDRs are steadily increasing from values certainly lower than −30 dB, at vertical incidence, to the values of about −10 dB, at the incidence angles of about 60°–70°, with a good matching between observations and theoretical predictions. On the other hand, land surface backscattering properties are not characterized by a strong angular dependence: σ0 and LDR values typically range between −20 and 0 dB and between −15 and −5 dB, respectively. This paper is relevant for spaceborne concepts of W-band radars, which envisage moderate incidence angles to achieve a broad swath needed for global coverage

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

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