UNRAVEL: A Robust Modular Velocity Dealiasing Technique for Doppler Radar

Unfold Radar Velocity (UNRAVEL) is an open-source modular Doppler velocity dealiasing algorithm for weather radars. UNRAVEL is an algorithm that does not need external reference velocity data, making it easily applicable. The proposed algorithm includes 11 core modules and 2 dealiasing strategies. UNRAVEL is an iterative algorithm. The goal is to build the dealiasing results starting with the strictest possible continuity tests in azimuth and range and, after each step, relaxing the parameters to include more results from a progressively growing number of reference points. UNRAVEL also has modules that perform 3D continuity checks. Thanks to this modular design, the number of dealiasing strategies can be expanded in order to optimize the dealiasing results. While the first driver dealiases Doppler velocity from each tilt independently from one another, the second driver also performs a three-dimensional continuity check of the velocity using successive elevations. The proposed dealiasing algorithm is tested using severe weather data from an S-band Doppler radar that have been aliased to mimic aliased radial velocity patterns that would be observed by a C-band Doppler radar. Artificially aliasing S-band data permits creation of a reference to which the performance of various dealiasing techniques can be compared. Comparisons show that UNRAVEL consistently outperforms other established dealiasing algorithms for the test period selected in this work.

Automated estimation of englacial radar velocity from zero offset data; implications for glacier bed topography retrieval

<p>Ground Penetrating Radar (GPR) is widely used on polythermal and temperate glaciers to sound bed topography and investigate the hydrothermal conditions through detection of englacial radar scattering. Water held within micro- and macro-scale pores and ice grain boundaries in ice at the pressure melting point influences the velocity of radar propagation on the scale of the wavelength, and can result in the occurrence of pronounced diffraction patterns in the data. Methods to investigate the water content distribution quantitatively within temperate ice often require the use of multi-offset common mid-point or common source-point survey techniques, which are logistically challenging and expensive. As a result, bed topography estimation is often undertaken using a constant velocity, and, because lateral variations in the the velocity field are unaccounted for, errors in topography are likely.</p><p>Here, we present an automated workflow to estimate an englacial radar velocity field from zero offset data and apply the algorithm to GPR data collected on Von Postbreen, a polythermal glacier in Svalbard, using a 25 MHz zero-offset GPR system. We first extract the diffracted wavefield using local coherent stacking to remove scatter and enhance diffractions. We then use the focusing metric of negative entropy to deduce a local migration velocity field from constant-velocity migration panels and produce a glacier-wide model of local (interval) radar velocity. We show that this velocity field is successful in differentiating between areas of cold and temperate ice and can detect lateral variations in radar velocity close to the glacier bed. The effects of this velocity field in both migration and depth-conversion of the bed reflection are shown to result in consistently lower ice depths across the glacier, indicating that diffraction focusing and velocity estimation are crucial in retrieving correct bed topography in the presence of temperate ice.</p>

Eddy Detection in HF Radar-Derived Surface Currents in the Gulf of Naples

Submesoscale eddies play an important role in the energy transfer from the mesoscale down to the dissipative range, as well as in tracer transport. They carry inorganic matter, nutrients and biomass; in addition, they may act as pollutant conveyors. However, synoptic observations of these features need high resolution sampling, in both time and space, making their identification challenging. Therefore, HF coastal radar were and are successfully used to accurately identify, track and describe them. In this paper we tested two already existing algorithms for the automated detection of submesoscale eddies. We applied these algorithms to HF radar velocity fields measured by a network of three radar systems operating in the Gulf of Naples. Both methods showed shortcomings, due to the high non-geostrophy of the observed currents. For this reason we developed a third, novel algorithm that proved to be able to detect highly asymmetrical eddies, often not properly identified by the previous ones. We used the results of the application of this algorithm to estimate the eddy boundary profiles and the eddy spatial distribution.

An IVAP-Based Dealiasing Method for Radar Velocity Data Quality Control

Dealiasing is a common procedure in radar radial velocity quality control. Generally, there are two dealiasing steps: a continuity check and a reference check. In this paper, a modified version that uses azimuthal variance of radial velocity is introduced based on the integrating velocity–azimuth process (IVAP) method, referred to as the V-IVAP method. The new method can retrieve the averaged winds within a local area instead of averaged wind within a full range circle by the velocity–azimuth display (VAD) or the modified VAD method. The V-IVAP method is insensitive to the alias of the velocity, and provides a better way to produce reference velocities for a reference check. Instead of a continuity check, we use the IVAP method for a fine reference check because of its high-frequency filtering function. Then a dealiasing procedure with two steps of reference check is developed. The performance of the automatic dealiasing procedure is demonstrated by retrieving the wind field of a tornado. Using the dealiased radar velocities, the retrieved winds reveal a clear mesoscale vortex. A test based on radar network observations also has shown that the two-step dealiasing procedure based on V-IVAP and IVAP methods is reliable.

Validation of Clyde River SuperDARN radar velocity measurements with the RISR-C incoherent scatter radar

The study considers simultaneous plasma velocity measurements in the eastward direction carried out by the Clyde River (CLY) Super Dual Auroral Radar Network (SuperDARN) high-frequency (HF) radar and Resolute Bay (RB) incoherent scatter radar – Canada (RISR-C). The HF velocities are found to be in reasonable agreement with RISR velocities up to magnitudes of 700–800 m s−1 while, for faster flows, the HF velocity magnitudes are noticeably smaller. The eastward plasma flow component inferred from SuperDARN convection maps (constructed for the area of joint measurements with consideration of velocity data from all the radars of the network) shows the effect of smaller HF velocities more notably. We show that the differences in eastward velocities between the two instruments can be significant and prolonged for observations of strongly sheared plasma flows.