Surface Current Maps Research Articles

Non-contact imaging of terahertz surface currents with aperture-type near-field microscopy.

Terahertz (THz) near-field imaging and spectroscopy provide valuable insights into the fundamental physical processes occurring in THz resonators and metasurfaces on the subwavelength scale. However, so far, the mapping of THz surface currents has remained outside the scope of THz near-field techniques. In this study, we demonstrate that aperture-type scanning near-field microscopy enables non-contact imaging of THz surface currents in subwavelength resonators. Through extensive near-field mapping of an asymmetric D-split-ring THz resonator and full electromagnetic simulations of the resonator and the probe, we demonstrate the correlation between the measured near-field images and the THz surface currents. The observed current dynamics in the interval of several picoseconds reveal the interplay between several excited modes, including dark modes, whereas broadband THz near-field spectroscopy analysis enables the characterization of electromagnetic resonances defined by the resonator geometry.

Controlled Preparation of High Quality Bubble-Free and Uniform Conducting Interfaces of Vertical van der Waals Heterostructures of Arrays.

Sharp and clean interfaces of van der Waals (vdW) heterostructures are highly demanded in two-dimensional (2D) materials-based devices. However, current assembly methods usually cause interfacial bubbles and wrinkles, hindering carrier interlayer transport. The preparation of a large-scale vdW heterostructure with a bubble-free interface is still a challenge. Although many efforts have been made to eliminate bubbles, the evolution processes of the interfacial bubbles are rarely studied. Here, the interface bubble formation and evolution of the transferred 2D materials and their vdW heterostructure are systemically studied by the atomic force microscopy (AFM) technique and high-resolution surface current mapping. A thermal annealing procedure is developed to reduce the number of bubbles and to improve the quality of interfaces. In addition, influences of the interface residues and nanosteps on bubble evolution are also discussed. Further, we develop the polystyrene (PS)-mediated polydimethylsiloxane (PDMS) transfer technique to realize the high-quality transfer of heterostructure arrays. Finally, high-resolution surface current mapping results confirm that we can now produce highly uniform electrical conduction interfaces of heterojunctions. This study provides guidance for assembling high quality interfaces and paves the way for production of bubble-free heterostructure-based electronic devices with high performance and good uniformity.

Intercomparison of surface velocimetry techniques for drone-based marine current characterization

Mapping tidal currents is important for a variety of coastal and marine applications. Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive. Previous application of particle image velocimetry to tidal current measurements demonstrated that accuracy depends on site and environmental conditions. This study compares surface velocimetry techniques across a range of these conditions. Various open-source tools and image pre-processing methods were applied to six sets of videos and validation data that cover a variety of site and weather conditions. When wind-driven ripples are present in imagery, it was found a short-wave celerity inversion performed best, with mean absolute percentage error (MAPE) of 5–6% compared to surface drifters. During lower wind speeds, current-advected surface features are visible and techniques which track these work best, of which the most appropriate technique depends on specifics of the collected imagery; MAPEs of 9–21% were obtained. This work has quantified accuracy and demonstrated that surface current maps can be obtained from drones under both high and low wind speeds and at a variety of sites. By following these suggested approaches, practitioners can use drones as a current mapping tool at coastal and offshore sites with confidence in the outputs.

New Signal Processing Techniques for Phased-Array Oceanographic Radars: Self-Calibration, Antenna Grouping, and Denoising

Abstract Original techniques are proposed for the improvement of surface current mapping with phased-array oceanographic high-frequency radars. The first idea, which works only in bistatic configuration, is to take advantage of a remote transmitter to perform an automatic correction of the receiving antennas based on the signal received in the direct path, an adjustment that is designated as “self-calibration.” The second idea, which applies to both mono- and bistatic systems, consists in applying a direction finding (DF) technique (instead of traditional beamforming), not only to the full antenna array but also to subarrays made of a smaller number of sequential antennas, a method that is referred to as “antenna grouping.” In doing this, the number of sources can also be varied, leading to an increased number of DF maps that can be averaged, an operation that is designated as “source stacking.” The combination of self-calibration, antenna grouping, and source stacking makes it possible to obtain high-resolution maps with increased coverage and is found robust to damaged antennas. The third improvement concerns the mitigation of noise in the antenna signal. These methods are illustrated with the multistatic high-frequency radar network in Toulon and their performances are assessed with drifters. The improved DF technique is found to significantly increase the accuracy of radar-based surface current when compared to the conventional beamforming technique.

Improved global sea surface height and current maps from remote sensing and in situ observations

Abstract. We present a new gridded sea surface height and current dataset produced by combining observations from nadir altimeters and drifting buoys. This product is based on a multiscale and multivariate mapping approach that offers the possibility to improve the physical content of gridded products by combining the data from various platforms and resolving a broader spectrum of ocean surface dynamic than in the current operational mapping system. The dataset covers the entire global ocean and spans from 1 July 2016 to 30 June 2020. The multiscale approach decomposes the observed signal into different physical contributions. In the present study, we simultaneously estimate the mesoscale ocean circulations as well as part of the equatorial wave dynamics (e.g. tropical instability and Poincaré waves). The multivariate approach is able to exploit the geostrophic signature resulting from the synergy of altimetry and drifter observations. Sea-level observations in Arctic leads are also used in the merging to improve the surface circulation in this poorly mapped region. A quality assessment of this new product is proposed with regard to an operational product distributed in the Copernicus Marine Service. We show that the multiscale and multivariate mapping approach offers promising perspectives for reconstructing the ocean surface circulation: observations of leads contribute to improvement of the coverage in delivering gap-free maps in the Arctic and observations of drifters help to refine the mapping in regions of intense dynamics where the temporal sampling must be accurate enough to properly map the rapid mesoscale dynamics. Overall, the geostrophic circulation is better mapped in the new product, with mapping errors significantly reduced in regions of high variability and in the equatorial band. The resolved scales of this new product are therefore between 5 % and 10 % finer than the Copernicus product (https://doi.org/10.48670/moi-00148, Pujol et al., 2022b).

Bragg-region recognition of high-frequency radar spectra based on deep learning and image fusion processing

ABSTRACT In previous research, the identification of the Bragg region, which is often achieved using image recognition, was easily affected by ionospheric interference and different manual parameter settings. Strong disturbances from the ionosphere and other environmental noise may interfere with high-frequency radar (HFR) systems when determining first-order Bragg regions and thus may directly influence the surface current mapping performance. To avoid human intervention in first-order Bragg-region recognition, deep learning methods were used to extract multiple levels of feature abstractions of the first-order Bragg region. In this study, to assist in developing sufficient training data, a procedure integrating a morphological approach and Otsu’s method was proposed to provide manual labelled data for a U-Net deep learning model. Additionally, several sets of activation functions and optimizers were used to achieve optimal deep learning model performance. The best combination of model parameters results in an accuracy of over 90%, an F1 score of over 80%, and an intersection over union (IoU) reaching 60%. The identification time of one image is approximately 70 ms. These results demonstrate that this deep learning model can predict the position of first-order Bragg regions under ionospheric interference and avoid being affected by strong noise that could cause prediction errors. Hence, deep learning and image fusion processing can effectively recognize the first-order Bragg regions under strong interference and noise and can thereby improve the surface current mapping accuracy.

Towards Retrieving Reliable Ocean Surface Currents in the Coastal Zone From the Sentinel‐1 Doppler Shift Observations

AbstractRecent developments on calibration and partitioning of the signal between the wave and current contributions significantly improve the accuracy of geophysical retrievals from Sentinel‐1 Synthetic Aperture Radar‐based Doppler shift measurements in the open ocean. In this study, we revise the Sentinel‐1B Interferometric Wide products acquired from December 2017 to January 2018 along the coastal zone of northern Norway. We find that the satellite attitude is responsible for 30% of the variation in the Doppler shift observations, while the antenna pattern can describe an additional 15%. The residual variation after recalibration is about 3.8 Hz, corresponding to 0.21–0.15 m/s radial velocity (RVL) depending on the incidence angle. Using recalibrated Sentinel‐1 observations, collocated with near‐surface wind from MetCoOp‐Ensemble Prediction System and sea state from MyWaveWAM, we develop an empirical function (CDOP3SiX) for estimating the sea‐state‐induced Doppler shift. CDOP3SiX improves the accuracy of sea state contribution estimates under mixed wind fetch conditions and demonstrates that the Norwegian Coastal Current can be detected in the Sentinel‐1 derived ocean surface current RVL maps. Moreover, two anticyclonic mesoscale eddies with radial velocities of about 0.5 m/s are detected. The surface current patterns are consistent with the collocated sea surface temperature observations. The Doppler shift observations from Sentinel‐1 can therefore be used to study ocean surface currents in the coastal zone with a 1.5 km spatial resolution.

Omnibearing Interpretation of External Ions Passivated Ion Migration in Mixed Halide Perovskites.

Fundamental understanding of ion migration inside perovskites is of vital importance for commercial advancements of photovoltaics. However, the mechanism for external ions incorporation and its effect on ion migration remains elusive. Herein, taking K+ and Cs+ co-incorporated mixed halide perovskites as a model, the impact of external ions on ion migration behavior has been interpreted via multiple dimensional characterization aspects. The space-effect on phase segregation inhibition has been revealed by the photoluminescence evolution and in situ dynamic cathodoluminescence behaviors. The plane-effect on current suppression along grain boundary has been evidenced via visualized surface current mapping, local current hysteresis, and time-resolved current decay. And the point-effect on activation energy incremental for individual ions has been also probed by cryogenic electronic quantification. All these results sufficiently demonstrate the passivated ion migration results in the eventually improved phase stability of perovskite, of which the origin lies in various ion migration energy barriers.

Nonlinear Analytical Modelling for Surface-Mounted Permanent Magnet Motors with Magnet Defect Fault

This paper analyzes magnet defect fault signature in the surface-mounted permanent magnet motor (SPMM) using nonlinear analytical model considering the influence of magnet shape and magnetization direction. Based on the surface current method and conformal mapping technique, the magnet defect equivalent current and equivalent nonlinearity current are proposed to represent the magnet defect. Accordingly, the performance of SPMM can be obtained. The proposed model has great potential to investigate SPMM with non-uniform magnet defect and gives theoretical basis for fault diagnosis. The extra sensing coil is added to measure the voltage waveforms, which can also be predicted using the nonlinear analytical model and shows the influence of magnet defect fault. Finally, the finite element analysis and experimental results verify the high accuracy of nonlinear analytical model.

An Objective Method with a Continuity Constraint for Improving Surface Velocity Estimates from the Geostationary Ocean Color Imager

Mapping surface currents with high spatiotemporal resolution over a wide coverage is crucial for understanding ocean dynamics and associated biogeochemical processes. The most widely used algorithm for estimating surface velocities from sequential satellite observations is the maximum cross-correlation (MCC) method. However, many unrealistic vectors still exist, despite the utilization of various filtering techniques. In this study, an objective method has been developed through the combination of MCC and multivariate optimum interpolation (MOI) analysis under a continuity constraint. The MCC method, with and without MOI, is applied to sequences of simulated sea surface temperature (SST) fields with a 1/48° spatial resolution over the East China Sea continental shelf. Integration of MOI into MCC reduces the average absolute differences between the model’s ‘actual’ velocity and the SST-derived velocity by 19% in relative magnitude and 22% in direction, respectively. Application of the proposed method to Geostationary Ocean Color Imager (GOCI) satellite observations produces good agreement between derived surface velocities and the Oregon State University (OSU) regional tidal model outputs. Our results demonstrate that the incorporation of MOI into MCC can provide a significant improvement in the reliability and accuracy of satellite-derived velocity fields.

High-Frequency Radar Measurements with CODAR in the Region of Nice: Improved Calibration and Performance

AbstractWe report on the installation and first results of one compact oceanographic radar in the region of Nice for a long-term observation of the coastal surface currents in the northwest Mediterranean Sea. We describe the specific processing and calibration techniques that were developed at the laboratory to produce high-quality radial surface current maps. In particular, we propose an original self-calibration technique of the antenna patterns, which is based on the sole analysis of the database and does not require any shipborne transponder or other external transmitters. The relevance of the self-calibration technique and the accuracy of inverted surface currents have been assessed with the launch of 40 drifters that remained under the radar coverage for about 10 days.

First multi-year assessment of Sentinel-1 radial velocity products using HF radar currents in a coastal environment

Direct sensing of total ocean surface currents with microwave Doppler signals is a growing topic of interest for oceanography, with relevance to several new ocean mission concepts proposed in recent years. Since 2014, the spaceborne C-band SAR instruments of the Copernicus Sentinel-1 (S1) mission routinely acquire microwave Doppler data, distributed to users through operational S1 Level-2 ocean radial velocity (L2 OCN RVL) products. S1 L2 RVL data could produce high-resolution maps of ocean surface currents that would benefit ocean observing and modelling, particularly in coastal regions. However, uncorrected platform effects and instrument anomalies continue to impact S1 RVL data and prevent direct exploitation.In this paper, a simple empirical method is proposed to calibrate and correct operational S1 L2 RVL products and retrieve two-dimensional maps of surface currents in the radar line-of-sight. The study focuses on the German Bight where wind, wave and current data from marine stations and an HF radar instrumented site provide comprehensive means to evaluate S1 retrieved currents. Analyses are deliberately limited to Sentinel-1A (S1A) ascending passes to focus on one single instrument and fixed SAR viewing geometry. The final dataset comprises 78 separate S1A acquisitions over 2.5 years, of which 56 are matched with collocated HF radar data. The empirical corrections bring significant improvements to S1A RVL data, producing higher quality estimates and much better agreement with HF radar radial currents.Comparative evaluation of S1A against HF radar currents for different WASV corrections reveal that best results are obtained in this region when computing the WASV with sea state rather than wind vector input. Accounting for sea state produces S1 radial currents with a precision (std of the difference) around 0.3m/s at ∼1km resolution. Precision improves to ∼0.24m/s when averaging over 21×27km2, with correlations with HF radar data reaching up to 0.93. Evidence of wind-current interactions when tides and wind align and short fetch conditions call for further research with more satellite data and other sites to better understand and correct the WASV in coastal regions.Finally, 1km resolution maps of climatological S1A radial currents obtained over 2.5 years reveal strong coastal jets and fine scale details of the coastal circulation that closely match the known bathymetry and deep-water coastal channels in this region. The wealth of oceanographic information in corrected S1 RVL data is encouraging for Doppler oceanography from space and its application to observing small scale ocean dynamics, atmosphere and ocean vertical exchanges and marine ecosystem response to environmental change.

Multi-Platform, High-Resolution Study of a Complex Coastal System: The TOSCA Experiment in the Gulf of Trieste

Although small in size, the Gulf of Trieste (GoT), a marginal coastal basin in the northern Adriatic Sea, is characterized by very complex dynamics and strong variability of its oceanographic conditions. In April–May 2012, a persistent, large-scale anticyclonic eddy was observed in the GoT. This event was captured by both High Frequency Radar (HFR) and Lagrangian drifter observations collected within the European MED TOSCA (Tracking Oil Spill and Coastal Awareness) project. The complexity of the system and the variety of forcing factors constitute major challenges from a numerical modeling perspective when it comes to simulating the observed features. In this study, we implemented a high-resolution hydrodynamic model in an attempt to reproduce and analyze the observed basin-wide eddy structure and determine its drivers. We adopted the Massachusetts Institute of Technology General Circulation Model (MITgcm), tailored for the GoT, nested into a large-scale simulation of the Adriatic Sea and driven by a tidal model, measured river freshwater discharge data and surface atmospheric forcing. Numerical results were qualitatively and quantitatively evaluated against HFR surface current maps, Lagrangian drifter trajectories and thermohaline data, showing good skills in reproducing the general circulation, but failing in accurately tracking the drifters. Model sensitivity to different forcing factors (wind, river and tides) was also assessed.

Reconstructing Ocean Surface Current Combining Altimetry and Future Spaceborne Doppler Data

AbstractTwo methods for the mapping of ocean surface currents from satellite measurements of sea level and future current vectors are presented and contrasted. Both methods rely on the linear and Gaussian analysis framework with different levels of covariance definitions. The first method separately maps sea level and currents with single‐scale covariance functions and leads to estimates of the geostrophic and ageostrophic circulations. The second maps both measurements simultaneously and projects the circulation onto four contributions: geostrophic, ageostrophic rotary, ageostrophic divergent, and inertial. When compared to the first method, the second mapping moderately improves the resolution of geostrophic currents but significantly improves estimates of the ageostrophic circulation, in particular near‐inertial oscillations. This method offers promising perspectives for reconstructions of the ocean surface circulation. Even the hourly dynamics can be reconstructed from measurements made locally every few days because nearby measurements are coherent enough to help fill the gaps. Based on numerical simulation of ocean surface currents, the proposed SKIM mission that combines a nadir altimeter and a Doppler scatterometer with a 300 km wide swath (with a mean revisit time of 3 days) would allow the reconstruction of 50% of the near‐inertial variance around an 18 h period of oscillation.

A gridded surface current product for the Gulf of Mexico from consolidated drifter measurements

Abstract. A large set of historical surface drifter data from the Gulf of Mexico – 3770 trajectories spanning 28 years and more than a dozen data sources – are collected, uniformly processed and quality controlled, and assimilated into a spatially and temporally gridded dataset called GulfFlow. This dataset is available in two versions, with 1/4∘ or 1/12∘ spatial resolution respectively, both of which have overlapping monthly temporal bins with semimonthly spacing and which extend from the years 1992 through 2020. Together these form a significant resource for studying the circulation and variability in this important region. The uniformly processed historical drifter data from all publicly available sources, interpolated to hourly resolution, are also distributed in a separate product called GulfDriftersOpen. Forming a mean surface current map by directly bin-averaging the hourly drifter data is found to lead to severe artifacts, a consequence of the extremely inhomogeneous temporal distribution of the drifters. Averaging instead the already monthly-averaged data in GulfFlow avoids these problems, resulting in the highest-resolution map of the mean Gulf of Mexico surface currents yet produced. The consolidated drifter dataset is freely available at https://doi.org/10.5281/zenodo.3985916 (Lilly and Pérez-Brunius, 2021a), while the gridded products are available for noncommercial use only (for reasons discussed herein) at https://doi.org/10.5281/zenodo.3978793 (Lilly and Pérez-Brunius, 2021b).

High-Frequency Radar Ocean Current Mapping at Rapid Scale With Autoregressive Modeling

In this article, we use an autoregressive (AR) approach combined with a maximum entropy method (MEM) to estimate radial surface currents from coastal high-frequency radar (HFR) complex voltage time-series. The performances of this combined AR-MEM model are investigated with synthetic HFR data and compared with the classical Doppler spectrum approach. It is shown that AR-MEM drastically improves the quality and the rate of success of the surface current estimation for short integration time. To confirm these numerical results, the same analysis is conducted with an experimental data set acquired with a 16.15-MHz HFR in Toulon. It is found that the AR-MEM technique is able to provide high-quality and high-coverage maps of surface currents even with very short integration time (about 1 min) where the classical spectral approach can only fulfill the quality tests on a sparse coverage. Further useful application of the technique is found in the tracking of surface current at high-temporal resolution. Rapid variations of the surface current at the time scale of the minute are unveiled and shown consistent with an f <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5/3</sup> decay of turbulent spectra.

Ocean Surface Current Inversion With Anchored Floating High-Frequency Radar: Yaw Compensation

Deploying a high-frequency (HF) radar on one anchored floating platform for the maneuverability appears to be a good alternative. In this case, because the yaw rotation during one coherent integration time may be rather large, an effective method to get precise direction-of-arrival (DOA) estimations is important for reliable ocean surface current mapping. In this article, we propose an adaptive data channel conversion method to compensate for this kind of rotation. In this method, radar data can be converted from rotating antenna channels into pseudo-fixed beam channels by following the minimum-mean-square-error rule between the wanted pseudo-fixed beam and a reference beam. Simulations with a uniform circular array and one kind of yaw rotation, the range of which is 90 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> , are conducted. After compensation, the DOA estimation of one simulated object becomes unbiased and performs nearly as good as that on a fixed platform. Besides, the high root-mean-square errors of radial ocean currents, caused by the yaw rotation, also decrease. Furthermore, we introduce a field experiment of one anchored floating HF radar, during which the DOA estimations of two onshore radars' direct waves improved drastically. The field ocean currents, deduced from this floating HF radar, also indicate the feasibility of the proposed method. This method offers a new idea to compensate for a floating platform's yaw rotation and can help introduce the traditional onshore HF radar to a much more flexible offshore scenario.

Effects of magnetogastrography sensor configurations in tracking slow wave propagation

Magnetogastrography (MGG) is a non-invasive method of assessing gastric slow waves (SWs) by recording the resultant magnetic fields. MGG can capture both SW frequency and propagation, and identify SW dysrhythmias that are associated with motility disorders. However, the impact of the restricted spatial coverage and sensor density on SW propagation tracking performance is unknown. This study simulated MGG using multiple anatomically specific torso geometries and two realistic SW propagation patterns to determine the effect of different sensor configurations on tracking SW propagation. The surface current density mapping and center-of-gravity tracking methods were used to compare four magnetometer array configurations: a reference system currently used in GI research and three hypothetical higher density and coverage arrays. SW propagation patterns identified with two hypothetical arrays (with coverage over at least the anterior of the torso) correlated significantly higher with simulated realistic 3 cycle-per-minute SW activity than the reference array (p = 0.016, p = 0.005). Furthermore, results indicated that most of the magnetic fields that contribute to the performance of SW propagation tracking were located on the anterior of the torso as further increasing the coverage did not significantly increase performance. A 30% decrease in sensor spacing within the same spatial coverage of the reference array also significantly increased correlation values by approximately 0.50 when the signal-to-noise ratio was 5 dB. This study provides evidence that higher density and coverage sensor layouts will improve the utility of MGG. Further work is required to investigate optimum sensor configurations across larger anatomical variations and other SW propagation patterns.

Assessment of HF Radar in Mapping Surface Currents under Different Sea States

AbstractTwo Ocean State Monitoring and Analyzing Radar (OSMAR071) (7.8 MHz) high-frequency (HF) radars and four moored ADCPs were operated concurrently in the southwestern Taiwan Strait during January–March 2013. Qualitative and quantitative comparisons of surface currents were conducted between the HF radars and the ADCPs. Except for a location probably affected by shallow water and sand waves on the Taiwan Banks, the HF-radar-derived radial currents (radials) showed good agreement with the ADCP measured results (correlation coefficient: 0.89–0.98; rms difference: 0.07–0.13 m s−1). To provide further insight into the geophysical processes involved, the performance of the HF-radar-derived radials was further evaluated under different sea states (sea states: 2–6). It was found that both the data returns of the radar-derived radials and the differences between the radar-derived radials and the ADCP-derived radials varied with sea state. The HF radar performed best at sea state 4 in terms of data returns. The spatial coverage increased rapidly as the waves increased from sea state 2 to 4. However, it decreased slowly from sea state 4 to 6. Second, the radial differences were relatively high under lower sea states (2 and 3) at the location where the best agreement was obtained between the radar and ADCP radials, whereas the differences increased as the sea states increased at the other three locations. The differences between the radials measured by the HF radars and the ADCPs could be attributed to wave-induced Stokes drift and spatial sampling differences.

Ka-Band Doppler Scatterometry over a Loop Current Eddy

Doppler scatterometry is a promising new technique for the simultaneous measurement of ocean surface currents and winds. These measurements have been recommended by the recent US NRC Decadal Review for NASA as being priority variables for the coming decade of Earth observations. In addition, currents and winds are useful for many applications, including assessing the operating conditions for oil platforms or tracking the dispersal of plastic or oil by surface currents and winds. While promising, Doppler scatterometry is relatively new and understanding the measurement characteristics is an important area of research. To this end, Chevron sponsored the deployment of DopplerScatt, a NASA/JPL Ka-band Doppler scatterometer, over instrumented sites located at the edge of a Gulf of Mexico Loop Current Eddy (LCE). In addition to in situ measurements, coincident synoptic maps of surface currents were collected by the Areté ROCIS instrument, an optical current measurement system. Here we report on the results of this experiment for both surface currents and winds. Surface current comparisons show that the Ka-band Current Geophysical Model Function (CGMF) needs to include wind drift currents, which could not be estimated with prior data sets. Once the CGMF is updated, ROCIS and DopplerScatt show good agreement for surface current speeds, but, at times, direction differences on the order of 10° can occur. Remote sensing optical and radar data agree better among themselves than with ADCP currents measured at 5 m depth, showing that remote sensing is sensitive to the the currents in top 1 m of the ocean. The LCE data provided a unique opportunity to study the effects of surface currents and stability conditions on scatterometer winds. We show that, like Ku-band, Ka-band estimates of winds are related to neutral winds (and wind stress) and are referenced relative to the moving frame provided by the current. This is useful for the study of air-sea interactions, but must be accounted for when using scatterometer winds for weather prediction.