Combined Co- and Cross-Polarized SAR Measurements Under Extreme Wind Conditions

Mouche, Alexis; Chapron, Bertrand; Zhang, Biao; Husson, Romain

doi:10.1109/tgrs.2017.2732508

Cited by 151 publications

(156 citation statements)

References 28 publications

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“…One is in copolarization (VV or HH), and the other is in cross polarization (VH or HV). In this study we only use L1 data acquired in dual polarization (VV+VH) to take benefit of the two polarization channels for the SAR wind retrieval (Mouche et al, ). To note, the EW Sentinel‐1 acquisition mode has also the dual‐polarization capability with a larger swath (400 km wide) more adapted to hurricane monitoring.…”

Section: Data Setmentioning

confidence: 99%

“…The NRCS accuracy and the signal‐to‐noise ratio are thus the main limitations for applications based on cross‐polarized signals. The potential of Sentinel‐1 dual‐polarized acquisitions for ocean applications (Mouche & Chapron, ) and a first algorithm for ocean surface wind measurements over extremes (Mouche et al, ) have already been presented. Sentinel‐1 mission requirements for radiometric accuracy is 1 dB.…”

Section: Data Setmentioning

confidence: 99%

“…In particular, Radarsat‐2 capabilities to measure the backscattered signals in copolarization and cross‐polarization (antenna emits in Vertical polarization and receives in Horizontal polarization; or vice versa) opened for new analysis strategies (Kudryavtsev et al, , ), to help reveal and interpret surface roughness changes related to upper ocean dynamics. For extreme weather events, such as TCs, the expected high sensitivity of cross‐polarized signals to ocean wave breaking further translated into a new potential: the use of these new cross‐polarized signals to map, at very high resolution, variations in ocean surface winds in and around the TC eyes (Mouche et al, ; Zhang & Perrie, ). Early demonstrations rapidly triggered vast interests, leading to refinements of future concept missions (Fois et al, ) to best exploit this high sensitivity to high wind conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Then, we consider particular acquisitions during Irma, one of the strongest North Atlantic TCs recorded during the 2017 season. To recall, most previous studies hardly sampled wind speed conditions higher than 40 m/s (Hwang et al, ) or 50 m/s (Mouche et al, ). Section presents the data sets we used and the collocation method we applied.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

et al. 2019

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C‐band high‐resolution radar (synthetic aperture radar [SAR]) is the only spaceborne instrument able to probe at very high resolution and over all ocean basins the sea surface under extreme weather conditions. When coanalyzed with Stepped Frequency Microwave Radiometer wind estimates, the radar backscatter signals acquired in major hurricanes from Sentinel‐1 and Radarsat‐2 SAR reveal high sensitivity in the cross‐polarized channel for wind speeds up to 75 m/s. The combination of the two copolarized and cross‐polarized channels can then be used to derive high‐resolution surface wind estimates. The retrieval methods and impacts of intense rainfall are discussed in the context of a Hurricane Irma (2017) case study. On 7 September 2017, Sentinel‐1 measurements intercepted Hurricane Irma when it was at category 5 intensity. When compared to Stepped Frequency Microwave Radiometer, SAR‐derived wind speeds yield bias and root‐mean‐square of about 1.5 and 5.0 m/s, respectively. The retrieved wind structure parameters for the outer core are found to be in agreement with the Best‐Track and combined satellite‐ and aircraft‐based analyses. SAR measurements uniquely describe the inner core and provide independent measurements of the maximum wind speed and the radius of maximum wind. Near the radius of maximum wind a 65‐m/s increase in wind speed in less than 10 km is detected, corresponding to an instantaneous absolute vorticity of order 210 times the Coriolis parameter. Using a parametric Holland model and the environmental surface pressure (1,011 hPa), SAR‐derived wind speeds correspond to a central surface pressure of 918 hPa (921 hPa from the Best‐Track) in Irma's eye.

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Section: Data Setmentioning

confidence: 99%

Section: Data Setmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

et al. 2019

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“…Thus, NRCS can represent information on wind sea (short wave roughness) and co-polarized (VV) NRCS has been introduced into SAR empirical SWH algorithms [19,20,23]. Besides, C-band cross-polarization (VH or HV) has demonstrated good performance to extract high winds even in hurricanes when saturation was observed in co-polarization i.e., [46,47]. Thus, the SAR SWH empirical model could be expected to provide better performance on estimation of wind wave energy in high sea state by taking VH NRCS into consideration (see Section 5.1 for detailed discussion).…”

Section: Normalized Radar Cross Section (Nrcs)mentioning

confidence: 99%

Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

Wang¹,

Wang

Yang

et al. 2018

Remote Sensing

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Gaofen-3 (GF-3), the first Chinese civil C-band synthetic aperture radar (SAR), was successfully launched by the China Academy of Space Technology on 10 August 2016. Among its 12 imaging modes, wave mode is designed to monitor the ocean surface waves over the open ocean. An empirical retrieval algorithm of significant wave height (SWH), termed Quad-Polarized C-band WAVE algorithm for GF-3 wave mode (QPCWAVE_GF3), is developed for quad-polarized SAR measurements from GF-3 in wave mode. QPCWAVE_GF3 model is built using six SAR image and spectrum related parameters. Based on a total of 2576 WaveWatch III (WW3) and GF-3 wave mode match-ups, 12 empirical coefficients of the model are determined for 6 incidence angle modes. The validation of the QPCWAVE_GF3 model is performed through comparisons against independent WW3 modelling hindcasts, and observations from altimeters and buoys from January to October in 2017. The assessment shows a good agreement with root mean square error from 0.5 m to 0.6 m, and scatter index around 20%. In particular, applications of the QPCWAVE_GF3 model in SWH estimation for two storm cases from GF-3 data in wave mode and Quad-Polarization Strip I mode are presented respectively. Results indicate that the proposed algorithm is suitable for SWH estimation from GF-3 wave mode and is promising for other similar data.

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Strong winds in a coupled wave–atmosphere model during a North Atlantic storm event: evaluation against observations

Pineau‐Guillou

Ardhuin

Bouin

et al. 2018

Quart J Royal Meteoro Soc

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Strong winds may be biased in atmospheric models. Here the European Centre for Medium-range Weather Forecasts (ECMWF) coupled wave-atmosphere model is used (i) to evaluate strong winds against observations, and (ii) to test how alternative wind stress parametrizations could lead to a more accurate model. For the period of storms Kaat and Lilli (23-27 January 2014), we compared simulated winds with in situ -moored buoys and platforms -and satellite observations available from the North Atlantic. Five wind stress parametrizations were evaluated. The first result is that moderate simulated winds (5-20 m s −1 ) match with all observations. However, for strong winds (above 20 m s −1 ), mean differences appear, as much as −7 m s −1 at 30 m s −1 . Significant differences also exist between observations, with buoys and Advanced Scatterometer ASCAT-KNMI generally showing lower wind speeds than the platforms and other remote-sensing data used in this study (AMSR2, ASCAT-RSS, WindSat, SMOS and JASON-2). Buoy and ASCAT-KNMI winds are likely to underestimate the real wind speed. It is difficult to conclude which dataset should be used as a reference. The second result is that common wave-age dependent parametrizations produce unrealistic drags and are not appropriate for coupling, whereas a newly empirically adjusted Charnock parametrization leads to higher winds compared to the default ECMWF parametrization. This proposed new parametrization may lead to more accurate results in an operational context.

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Combined Co- and Cross-Polarized SAR Measurements Under Extreme Wind Conditions

Cited by 151 publications

References 28 publications

Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

Copolarized and Cross‐Polarized SAR Measurements for High‐Resolution Description of Major Hurricane Wind Structures: Application to Irma Category 5 Hurricane

Empirical Algorithm for Significant Wave Height Retrieval from Wave Mode Data Provided by the Chinese Satellite Gaofen-3

Strong winds in a coupled wave–atmosphere model during a North Atlantic storm event: evaluation against observations

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