Technical background, chapter 3, part B

A description is given of the physics of electromagnetic scattering from the sea and a guideline is presented to relate an observable (such as the radar cross section) to the hydrodynamics or physical properties of the sea. As specific examples of the interdisciplinary science of electromagnetics and geophysical oceanography, the physics is discussed in connection with data provided by three instruments: namely, the scatterometer, the altimeter, and the imaging radar. The data provided by each instrument are discussed in context with specular point and Bragg scattering theories. Finally, the degrading effect of extraneous sources of noise is discussed as a limiting mechanism of the accuracy of the ocean surface measurement

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

A model for the wind direction signature in the stokes smissin sector from the ocean surfaces at microwave frequencies

This paper presents a model of the Stokes emission vector from the ocean surface. The ocean surface is described as an ensemble of facets with Cox and Munk's (1954) Gram-Charlier slope distribution. The study discusses the impact of different up-wind and cross-wind rms slopes, skewness, peakedness, foam cover models and atmospheric effects on the azimuthal variation of the Stokes vector, as well as the limitations of the model. Simulation results compare favorably, both in mean value and azimuthal dependence, with SSM/I data at 53/spl deg/ incidence angle and with JPL's WINDRAD measurements at incidence angles from 30/spl deg/ to 65/spl deg/, and at wind speeds from 2.5 to 11 m/s.Peer ReviewedPostprint (published version

An operational satellite scatterometer for wind vector measurements over the ocean

Performance requirements and design characteristics of a microwave scatterometer wind sensor for measuring surface winds over the oceans on a global basis are described. Scatterometer specifications are developed from user requirements of wind vector measurement range and accuracy, swath width, resolution cell size and measurement grid spacing. A detailed analysis is performed for a baseline fan-beam scatterometer design, and its performance capabilities for meeting the SeaSat-A user requirements. Various modes of operation are discussed which will allow the resolution of questions concerning the effects of sea state on the scatterometer wind sensing ability and to verify design boundaries of the instrument

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

S-193 scatterometer backscattering cross section precision/accuracy for Skylab 2 and 3 missions

Procedures for measuring the precision and accuracy with which the S-193 scatterometer measured the background cross section of ground scenes are described. Homogeneous ground sites were selected, and data from Skylab missions were analyzed. The precision was expressed as the standard deviation of the scatterometer-acquired backscattering cross section. In special cases, inference of the precision of measurement was made by considering the total range from the maximum to minimum of the backscatter measurements within a data segment, rather than the standard deviation. For Skylab 2 and 3 missions a precision better than 1.5 dB is indicated. This procedure indicates an accuracy of better than 3 dB for the Skylab 2 and 3 missions. The estimates of precision and accuracy given in this report are for backscattering cross sections from -28 to 18 dB. Outside this range the precision and accuracy decrease significantly

Toward RADSCAT measurements over the sea and their interpretation

Investigations into several areas which are essential to the execution and interpretation of suborbital observations by composite radiometer - scatterometer sensor (RADSCAT) are reported. Experiments and theory were developed to demonstrate the remote anemometric capability of the sensor over the sea through various weather conditions. It is shown that weather situations found in extra tropical cyclones are useful for demonstrating the all weather capability of the composite sensor. The large scale fluctuations of the wind over the sea dictate the observational coverage required to correlate measurements with the mean surface wind speed. Various theoretical investigations were performed to establish a premise for the joint interpretation of the experiment data. The effects of clouds and rains on downward radiometric observations over the sea were computed. A method of predicting atmospheric attenuation from joint observations is developed. In other theoretical efforts, the emission and scattering characteristics of the sea were derived. Composite surface theories with coherent and noncoherent assumptions were employed

Technical approaches, chapter 3, part E

Radar altimeters, scatterometers, and imaging radar are described in terms of their functions, future developments, constraints, and applications

Impact of rain, swell, and surface currents on the electromagnetic bias in GNSS-Reflectometry

The assessment of the electromagnetic (EM) bias is required to predict the performance of upcoming global navigation satellite systems-reflectometry (GNSS-R) altimetry systems, and its impact in data assimilation climate studies. In previous studies, the EM bias in bistatic GNSS-R altimetry (L-band) was numerically estimated for a wind-driven sea surface height spectrum, including the time-domain variability. In the present study, spectral models for the rain, swell, and surface currents are used to compute a perturbed wind-driven sea surface height spectrum, from which a perturbed three-dimensional (3-D) time-evolving wind-driven sea surface height is computed. The generated sea surface is then illuminated by a right hand circular polarization (RHCP) L-band EM wave, and the wave scattered from each facet is computed from each facet using the physical optics (PO) method under the Kirchhoff approximation (KA). Finally, the EM bias is computed numerically as the height of each patch times the forward-scattering coefficient, divided by the average of the forward-scattering coefficient. The impact of rain on the EM bias is a moderate decrease (in magnitude) due to the damping of the large gravity waves, which is more significant as the wind speed increases. The impact of swell is a small increase (in magnitude) mostly due to the change of the local incidence angles. The impact of currents can be either a moderate increase or decrease (in magnitude), depending on the sense of the current with respect to the wind, due to a change in the surface roughness.Peer ReviewedPostprint (author's final draft

Development Of An Improved Microwave Ocean Surface Emissivity Radiative Transfer Model

An electromagnetic model is developed for predicting the microwave blackbody emission from the ocean surface over a wide range of frequencies, incidence angles, and wind vector (speed and direction) for both horizontal and vertical polarizations. This ocean surface emissivity model is intended to be incorporated into an oceanic radiative transfer model to be used for microwave radiometric applications including geophysical retrievals over oceans. The model development is based on a collection of published ocean emissivity measurements obtained from satellites, aircraft, field experiments, and laboratory measurements. This dissertation presents the details of methods used in the ocean surface emissivity model development and comparisons with current emissivity models and aircraft radiometric measurements in hurricanes. Especially, this empirically derived ocean emissivity model relates changes in vertical and horizontal polarized ocean microwave brightness temperature measurements over a wide range of observation frequencies and incidence angles to physical roughness changes in the ocean surface, which are the result of the air/sea interaction with surface winds. Of primary importance are the Stepped Frequency Microwave Radiometer (SFMR) brightness temperature measurements from hurricane flights and independent measurements of surface wind speed that are used to define empirical relationships between C-band (4 - 7 GHz) microwave brightness temperature and surface wind speed. By employing statistical regression techniques, we develop a physical-based ocean emissivity model with empirical coefficients that depends on geophysical parameters, such as wind speed, wind direction, sea surface temperature, and observational parameters, such as electromagnetic frequency, electromagnetic polarization, and incidence angle