Sea Surface Wind Retrievals from SIR-C/X-SAR Data:  A Revisit

Ren, Yongzheng; Li, Xiaoming; Zhou, Guoqing

doi:10.3390/rs70403548

Cited by 13 publications

(16 citation statements)

References 24 publications

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“…Typically, wind information over the sea surface is provided by ancillary in situ and/or remotely-sensed data, e.g., buoy measurements and/or scatterometer and radiometer satellite data. The former measure sea surface wind speed at the usual height of 5 m, while the latter allow retrieving near surface wind speed at a reference height of 10 m above sea level [43][44][45]. Unfortunately, very often, the information coming from other remotely-sensed sources is not colocated in time and/or space with the available SAR dataset.…”

Section: Experiments and Discussionmentioning

confidence: 99%

COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

2018

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Oil spills are adverse events that may be very harmful to ecosystems and the food chain. In particular, large sea oil spills are very dramatic occurrences that may affect sea and coastal areas. Hence, the sustainability of oil rig infrastructures and oil transportation via oil tankers is linked to law enforcement based on proper monitoring techniques, which are also fundamental to mitigate the impact of such pollution. In this study, a showcase referring to the Deepwater Horizon (DWH) oil incident, one of the world’s largest incidental oil pollution event that occurred in the Gulf of Mexico in 2010 affecting a sea area larger than 10,000 km 2 , is analyzed using remotely-sensed information collected by Synthetic Aperture Radar (SAR). Although, operationally, SAR sea oil slick observation is typically accomplished using C-band VV-polarized SAR imagery, during the DWH oil incident, because of their very dense revisit time, even single-polarization X-band COSMO-SkyMed (CSK) SAR measurements were collected. In this study, we exploit, for the first time, incoherent dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.

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Section: Experiments and Discussionmentioning

confidence: 99%

COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

2018

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“…Although several algorithms have been recently exploited for wind retrieval from co-polarization TS-X/TD-X image, such as GMF SIRX-MOD [3], GMF XMOD2 [4] and polarization ratio XPRs [2,5], these algorithms are only valid for wind speeds up to 25 m/s. When XWAVE is applied for wave retrieval from HH-polarization TS-X/TD-X image, XPR has to be used for converting NRCS in HH-polarization to NRCS in VV-polarization to retrieve wind speed.…”

Section: Discussionmentioning

confidence: 99%

“…Then, similar to the development of C-band GMF CMOD5 [33] that was derived from ERS-1 SAR images and ECMWF reanalysis wind data, XMOD2 has been exploited in [4] by using collocated VV-polarization TS-X/TD-X images and National Data Buoy Center (NDBC) buoy measurements and it was found that a 1.44 m/s RMSE of wind speed was achieved against NOAA in situ buoys. Besides, another X-band GMF, called SIRX-MOD, was proposed in [3] by retuning the coefficients in the C-band GMF CMOD-IFR2 [34] with the VVpolarization Spaceborne Imaging Radar (SIR) X-band SAR NRCS data and ECMWF reanalysis wind data. XMOD2 and SIRX-MOD take the general form of:…”

Section: Existing X-band Sar Wind and Wave Algorithmsmentioning

confidence: 99%

“…TS-X and its twin TD-X have 514 km orbit height above earth and a 100-min orbit period with fine spatial resolution of image up to 1 m. TS-X and TD-X SAR are officially operated by Germen Aerospace Center (DLR). In the past few years, several algorithms for winds [1][2][3][4][5] and waves [6][7][8][9] retrieval from TS-X/TD-X image have been developed. Geophysical model function tropical cyclone conditions yet.…”

Section: Introductionmentioning

confidence: 99%

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An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery

Shao

Wang

et al. 2017

Remote Sensing

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Abstract:In this study, we proposed an empirical algorithm for significant wave height (SWH) retrieval from TerraSAR-X/TanDEM (TS-X/TD-X) X-band synthetic aperture radar (SAR) co-polarization (vertical-vertical (VV) and horizontal-horizontal (HH)) images. As the existing empirical algorithm at X-band, i.e., XWAVE, is applied for wave retrieval from HH-polarization TS-X/TD-X image, polarization ratio (PR) has to be used for inverting wind speed, which is treated as an input in XWAVE. Wind speed encounters saturation in tropical cyclone. In our work, wind speed is replaced by normalized radar cross section (NRCS) to avoiding using SAR-derived wind speed, which does not work in high winds, and the empirical algorithm can be conveniently implemented without converting NRCS in HH-polarization to NRCS in VV-polarization by using X-band PR. A total of 120 TS-X/TD-X images, 60 in VV-polarization and 60 in HH-polarization, with homogenous wave patterns, and the coincide significant wave height data from European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis field at a 0.125 • grid were collected as a dataset for tuning the algorithm. The range of SWH is from 0 to 7 m. We then applied the algorithm to 24 VV and 21 HH additional SAR images to extract SWH at locations of 30 National Oceanic and Atmospheric Administration (NOAA) National Data Buoy Center (NDBC) buoys. It is found that the algorithm performs well with a SWH stander deviation (STD) of about 0.5 m for both VV and HH polarization TS-X/TD-X images. For large wave validation (SWH 6-7 m), we applied the empirical algorithm to a tropical cyclone Sandy TD-X image acquired in 2012, and obtained good result with a SWH STD of 0.3 m. We concluded that the proposed empirical algorithm works for wave retrieval from TS-X/TD-X image in co-polarization without external sea surface wind information.

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“…The correcting term is a function of wavenumber and wind speed with twelve adjusted parameters, which are derived from L-, C-and Ku-band radar backscatter. It is noted that the X-band GMF has been developed by Li et al [29] and Ren et al [30]. But the upwind-crosswind asymmetry in their GMFs needs to be verified by large amounts of data.…”

Section: Discussionmentioning

confidence: 99%

Directional Spreading Function of the Gravity-Capillary Wave Spectrum Derived from Radar Observations

Zhou

Chong

et al. 2017

Remote Sensing

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Directional spreading function of the gravity-capillary wave spectrum can provide the high-wavenumber wave energy distribution among different directions on the sea surface. The existing directional spreading functions have been mainly developed for the low-wavenumber gravity wave with buoy data. In this paper, we use radar observations to derive the directional spreading function of the gravity-capillary wave spectrum, which is expressed as the second-order Fourier series expansion. So far the standard form of the second-order harmonic coefficient has not been proposed to correctly unify the gravity and gravity-capillary wave. Our strategy is to introduce a correcting term to replace the inaccurate gravity-capillary spectral component in Elfouhaily's directional spreading function. The second-order harmonic coefficient at L, C and Ku band calculated by the radar observation is used to fit the correcting term to obtain one at the full gravity-capillary wave region. According to our proposed the directional spreading function, there is a spectral region between the gravity and gravity-capillary range where it signifies the negative upwind-crosswind asymmetry at low and moderate speed range. And this is not reflected by the previous models, but has been confirmed by radar observations. The Root Mean Square Difference (RMSD) of the proposed second-order harmonic coefficient versus the radar-observed one at L, C band Ku band is 0.0438, 0.0263 and 0.0382, respectively. The overall bias and RMSD are −0.0029 and 0.0433 for the whole second-order harmonic coefficient range, respectively. The result verifies the accuracy of the proposed directional spreading function at L, C band Ku band.

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Sea Surface Wind Retrievals from SIR-C/X-SAR Data: A Revisit

Cited by 13 publications

References 24 publications

COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

An Empirical Algorithm for Wave Retrieval from Co-Polarization X-Band SAR Imagery

Directional Spreading Function of the Gravity-Capillary Wave Spectrum Derived from Radar Observations

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