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A method to extract characteristics of the Gulf Stream (GS) surface flow field using high-frequency radar (HFR)–derived currents is described. Radial velocity measurements, from radar installations near Cape Hatteras, North Carolina, serve as input, chosen because of the greater spatial and temporal coverage provided compared to total velocity fields. The landward GS edge, jet axis, orientation, and cyclonic shear zone (CSZ) width are identified along bearings within the radar footprint. The method is applied to observations from two radar installations from November 2014 and provides GS estimates with daily temporal resolution. Results along eight bearings provide a consistent representation of GS variability dominated by the passage of meanders. Average distance to the GS edge along bearings varies from 50 to 100 km; distance estimate quality degrades with range from the radars. Monthly mean GS jet axis locations from satellite sea surface height (SSH) and the algorithm are consistent. Cross correlations between estimates of GS characteristics in the same region vary from 0.37 to 0.73 for the GS edge. Estimates of radar distance to the GS edge are negatively correlated with current velocity measurements nearest the surface from a moored 150-kHz acoustic Doppler current profiler and vary between −0.58 and −0.71. GS CSZ width metrics range from mean values of 29–31 km. Daily GS orientation estimates are affected by the crossing angle of the radial bearing relative to the GS. Lags from the cross correlations of monthly mean properties suggest meander propagation speed estimates increase from 43.2 km day−1 south of the cape, to 136.8 km day−1 just east of it. [ABSTRACT FROM AUTHOR]

Forward-looking multichannel synthetic aperture radar (FLMC-SAR) is an important tool for modern remote sensing applications, which has the capability to reconstruct the high-resolution image of the front area. However, due to the azimuth-variant characteristics of the motion errors over a long aperture, FLMC-SAR data processing is usually a challenging task, especially when involving the motion compensation (MOCO) coupled with Doppler ambiguity resolving. To accomplish an accurate MOCO for FLMC-SAR, a novel parametric azimuth-variant MOCO approach is proposed in this article. Aiming at the coupling problem of MOCO and Doppler ambiguity resolving over the full aperture, we can decouple them through the subaperture division. As a full synthetic aperture is decomposed into several subapertures, the high-order motion errors of the full aperture can be decomposed into the first-order motion errors of the subaperture. On this basis, the mismatch of the space–time spectrum caused by the motion errors can be solved by spectral estimation, yielding Doppler ambiguity resolving for each subaperture. Meanwhile, the azimuth-variant characteristic of motion errors in FLMC-SAR system is characterized by a parametric angle-dependent quadratic phase error (QPE) model. The motion parameters are estimated by a joint multichannel angle estimation-based signal quadratic decomposition method. Immediately, the MOCO for ambiguous targets with different motion errors can be processed separately to improve the imaging performance. Experimental results based on both simulated and real data demonstrate that the proposed method is suitable for FLMC-SAR system. [ABSTRACT FROM AUTHOR]

Compact high-frequency surface wave radar has been widely applied to the measurement of sea surface current, but its accuracy and direction resolution of wave parameter estimation are always limited due to the wide beam of the antenna. In this article, a novel wave-height mapping method based on the second-order harmonic peak (SHP) of radar Doppler spectra is proposed to address this concern. The characteristic of the SHP at the Doppler frequency of $\sqrt {2}$ times the Bragg frequency is studied through the theoretical derivation and numerical simulation. A relationship between the ratio ($R$) of the SHP power to the Bragg peak power and significant wave height ($H_{s}$) is derived. Furthermore, the $R$ – $H_{s}$ model is improved by incorporating influences, such as background noise and antenna beamwidth. With this improved model, a wave-height mapping algorithm based on the direction finding technique is presented. This approach enables the significant wave-height map extraction using a broad-beam radar. Finally, wave-height maps obtained at different sea states are depicted and analyzed, and the wave heights appearing on the maps are compared with buoy data over a one-month experiment to verify the validity and robustness of the algorithm. During this period, the significant wave height varies from about 0.5 to 4.5 m, and the radar measured wave heights at different range/distance bins show an overall root-mean-square error (RMSE) of 0.33–0.77 m and a correlation coefficient (CC) of 0.78–0.94, with respect to the buoy measurements. [ABSTRACT FROM AUTHOR]

This study comprises the analysis and the interpretation of the coherent and the noncoherent parts of a coherent-on-receive microwave radar at grazing incidence conditions. The Doppler measurement is an extension of standard civil marine radar technology. While intensity images require interpretation based on understanding the underlying imaging mechanism, the Doppler signal measures the motion of an area of sea surface and is therefore closely related to the wave physics. Both the measured Doppler signal and the backscatter intensity signal are suitable for surface inversion and give almost identical surface elevations. A statistical comparison with a nearby buoy showed good correlation for the significant wave height and the peak period. By comparing the Doppler signal and the amplitude in the backscatter, the study amends the understanding of imaging mechanisms in marine radars at grazing incidence. [ABSTRACT FROM AUTHOR]

Radar tracking of aircraft targets at low elevation angles can be complicated by clutter from wind turbines, which we define to be clutter. In this paper, we study detection in a staring pulse-Doppler radar. By exploiting the second-order correlation structure of this wind-turbine clutter we derive a target detector that uses a sequence of adaptive coherence scores. The detector uses a multipulse coherence statistic consisting of an incoherent geometric average of coherently computed adaptive coherence scores. The detector compares favorably to a multipulse coherence detector that uses no modeling or estimation of the clutter. [ABSTRACT FROM PUBLISHER]

Sparse signal representation is used to coherently separate the main rotor blade components of a helicopter from the composite data of complex time series radar returns. Received signals of this type typically consist of returns from the rotating main and tail rotor blades, the helicopter body, and other residual components which may overlap in time and frequency, thus making it difficult for conventional time–frequency separation techniques to be applied for the signal separation. In the proposed algorithm, a sparse signal representation is applied with the use of tunable Q wavelet transform to construct the dictionary, and basis pursuit denoising is used for the signal reconstruction of the component of interest. The algorithm shows very effective separation of the main rotor blade component from the composite radar returns, which is demonstrated using both simulated and real radar data at X-band. [ABSTRACT FROM AUTHOR]

This article describes the development and trials at the Met Office of the assimilation of radar Doppler radial winds in a pre-operational framework. It uses a high-resolution 1.5 km convective-scale version of the Unified Model for nowcasting, on a small domain covering southern England and Wales. The assimilation was performed using a version of the Met Office 3D-variational data assimilation system at 1.5 km resolution. The Doppler radial wind observations were provided by the original four Dopplerized C-band single-polarization radars in the UK radar network, all situated in the south of England. This article provides a description of the Doppler radial wind observation operator, pre-processing, observation errors and data assimilation configuration. The system is tested on and verified for four case studies using continuous hourly cycling with 7 h forecasts. A significant positive impact for rain and wind is found in the first half of the forecasts (nowcasting time-scale). [ABSTRACT FROM AUTHOR]

Because of its extensive quality control procedures and uniform space-time grid, the NCEP Stage IV merged Weather Surveillance Radar-1988 Doppler (WSR-88D) radar and surface rain gauge dataset is often considered to be the best long-term gridded dataset of precipitation observations covering the contiguous United States. Stage IV accumulations are employed in a variety of applications, and while the WSR-88D systems are well suited for observing heavy rain events that are likely to affect flooding, limitations in surface radar and gauge measurements can result in missed precipitation, especially near topography and in the western United States. This paper compares hourly Stage IV observations of precipitation occurrence to collocated observations from the 94-GHz CloudSat Cloud Profiling Radar, which provides excellent sensitivity to light and frozen precipitation. Statistics from 4 yr of comparisons show that the CloudSat observes precipitation considerably more frequently than the Stage IV dataset, especially in northern states where frozen precipitation is prevalent in the cold season. The skill of Stage IV for precipitation detection is found to decline rapidly when the near-surface air temperature falls below 0°C. As a result, agreement between Stage IV and CloudSat tends to be best in the southeast, where radar coverage is good and moderate-to-heavy liquid precipitation dominates. Stage IV and CloudSat precipitation detection characteristics are documented for each of the individual river forecast centers that contribute to the Stage IV dataset to provide guidance regarding potential sampling biases that may impact hydrologic applications. [ABSTRACT FROM AUTHOR]

Waves, winds and currents can be extracted from the Doppler power Spectra of HF Radar. Worldwide research has been done for this purpose during the last 4 decades. A new multi-frequency HF (MHF) radar is applied to enrich this study in a ten-day experiment completed in the East China Sea. The new MHF radar is designed to simultaneously work at four different frequencies at most between 7.5 MHz and 25 MHz. In this paper, we particularly focus on wave measurements, which were obtained both from MHF radar and wave buoy. A comparison of the two measurements is made, and the final result points out a potential and practical way to improve the performance of HF radar wave measuring. It is suggested that, when the fusion algorithm of multi-frequency data is robust enough, MHF radar can be widely used for ocean remote sensing. [ABSTRACT FROM AUTHOR]

High-frequency surface wave radar (HFSWR) has been widely adopted as a useful remote-sensing tool for sea-state monitoring. There are limitations to the performance because of various unwanted clutters and interferences that contaminate radar signals. Among all types of unwanted signals, radio frequency interference (RFI) is dominant since the frequency bands 3-30 MHz, the operation range of HFSWR, are shared by many radio services. If RFI occupies the areas in the Doppler spectrum that are essential for the estimation of oceanographic parameters, for example, wind speed, current speed, wave height etc., it will significantly reduce the quality of the data. The characteristics of RFI in time, space and Doppler domains are analysed for sea-state monitoring, and a robust and general signal processing method consisting of image recognition, segmentation processing and subspace projection for cancellation of RFI is proposed. The effectiveness of this approach is validated using data obtained with the Pisces HF radar, which is a high-performance radar developed for long-range wave measurement, operating in the lower half of the HF band (5-10 MHz). [ABSTRACT FROM AUTHOR]

The paper proposes a way to increase the energy within a coherent processing interval (CPI) using more pulses instead of longer pulses. Long coded pulses result in masking targets at close range and poor Doppler tolerance. Increasing the number of pulses implies high pulse repetition frequency (PRF), which suffers from range ambiguity and target folding. These drawbacks of a high PRF can be mitigated by inter-pulse coding. The approach suggested here should be attractive for close and mid range applications of radar, ground penetrating radar, ultrasound imaging, and more. [ABSTRACT FROM AUTHOR]

Attenuation of radar signals by melting hydrometeors is studied using modeling approaches and comparisons of simulated and observed results. In spite that the melting layer in precipitating systems is usually relatively thin (~ 500 m), this attenuation can be substantial at X-band frequencies for low elevation angles and at millimeter-wavelength frequencies that are used by the U.S. Department of Energy's Atmospheric Radiation Measurement Program and CloudSat radars operating at vertical/ nadir incidence. Melting layer attenuation is stronger than the attenuation in the resultant rain at comparable path lengths and needs to be accounted for in remote sensing methods that use radar reflectivity measurements for retrieving cloud and precipitation parameters if the radar beam penetrates this layer. The choice of the mixing rule for calculating dielectric constants of melting hydrometeors determines, to a significant degree, the magnitude of the modeled attenuation values. A relatively simple Wiener mixing rule provides results that are consistent with melting layer reflectivity enhancements and attenuation estimates from the X-band radar observations. The total melting layer attenuation A is related to the resultant rain rate R in an approximately linear manner at X- and Ka-band frequencies, whereas at W-band, the melting layer attenuation increase with rain rate is slower due to strong non-Rayleigh scattering effects. Typical A-R relations are suggested, and the variability of these relations is discussed. This paper is mostly concerned with precipitating systems associated with snowflakes that are unrimed or only slightly rimed above the freezing level, as indicated by relatively low values of vertical Doppler velocities. [ABSTRACT FROM AUTHOR]

High-frequency (HF) radars require large-array antennas to achieve narrow beamwidths and are required to discriminate targets with low Doppler shifts compared with microwave radar. Superresolution processing can discriminate signals at separations much less than the beamwidth or conventional Doppler bin width (or conversely, achieve a given minimum resolvable separation with a smaller array or less time-on-target). Simulation results and analysis of real radar data presented here show at least a 2-fold improvement compared with conventional processing, assuming simple theoretical gain manifolds. A novel polarisation-sensitive superresolution algorithm applicable to skywave HF radar is also discussed. [ABSTRACT FROM AUTHOR]

In this letter, a novel method is proposed for estimating the median droplet diameter by using the Ka- and W-band dual-wavelength differences of the mean Doppler velocity and the Doppler spectrum width. The estimated median diameter together with the dual-wavelength ratio of the radar reflectivity can be effectively used to measure and compensate the attenuation in precipitation or clouds. The estimate of the median diameter is not affected by the attenuation and does not require an accurate radar calibration. Furthermore, the vertical air flows and the turbulent broadening of the Doppler spectra have no influence on the estimate. [ABSTRACT FROM AUTHOR]

The Barrick–Weber equations describe the interaction of radar signals with the dynamic ocean surface, and so provide a mathematical basis for oceanic remote sensing. This report considers the inversion of these equations with several of the row-action methods commonly used to solve large linear systems with unstructured sparsity. It is found that the performance of the methods in inverting both synthetic and measured Doppler spectral data is comparable, with the method of Chahine–Twomey–Wyatt offering a slight advantage in the reliability of the recovery of the full directional wave spectrum and of parameters derived from its integration. Some remarks and open questions on the ill-posedness of the inversion problem conclude the paper. [ABSTRACT FROM AUTHOR]

A remote sensing method is proposed to derive vertical profiles of the visible extinction coefficients in ice clouds from measurements of the radar reflectivity and Doppler velocity taken by a vertically pointing 35-GHz cloud radar. The extinction coefficient and its vertical integral, optical thickness τ, are among the fundamental cloud optical parameters that, to a large extent, determine the radiative impact of clouds. The results obtained with this method could be used as input for different climate and radiation models and for comparisons with parameterizations that relate cloud microphysical parameters and optical properties. An important advantage of the proposed method is its potential applicability to multicloud situations and mixed-phase conditions. In the latter case, it might be able to provide the information on the ice component of mixed-phase clouds if the radar moments are dominated by this component. The uncertainties of radar-based retrievals of cloud visible optical thickness are estimated by comparing retrieval results with optical thicknesses obtained independently from radiometric measurements during the yearlong Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment. The radiometric measurements provide a robust way to estimate τ but are applicable only to optically thin ice clouds without intervening liquid layers. The comparisons of cloud optical thicknesses retrieved from radar and from radiometer measurements indicate an uncertainty of about 77% and a bias of about -14% in the radar estimates of τ relative to radiometric retrievals. One possible explanation of the negative bias is an inherently low sensitivity of radar measurements to smaller cloud particles that still contribute noticeably to the cloud extinction. This estimate of the uncertainty is in line with simple theoretical considerations, and the associated retrieval accuracy should be considered good for a nonoptical instrument, such as radar. This paper also presents relations between radar-derived characteristic cloud particle sizes and effective sizes used in models. An average relation among τ, cloud ice water path, and the layer mean value of cloud particle characteristic size is also given. This relation is found to be in good agreement with in situ measurements. Despite a high uncertainty of radar estimates of extinction, this method is useful for many clouds where optical measurements are not available because of cloud multilayering or opaqueness. [ABSTRACT FROM AUTHOR]