Analysis of Dual-Frequency Ocean Backscatter Measurements at Ku- and Ka-Bands Using Near-Nadir Incidence GPM Radar Data

Nouguier, Frédéric; Mouche, Alexis; Rascle, Nicolas; Chapron, Bertrand; Vandemark, D.

doi:10.1109/lgrs.2016.2583198

Cited by 40 publications

(39 citation statements)

References 22 publications

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“…The experimental data and regression dependencies of

σ_{t o t}^{2}

on U 10 for oil‐covered and clean surface are presented in Figure a. The derived dependence for a clean surface,

σ_{t o t Ku_clean}^{2} = 0.0111 + 0.002 U_{10} \pm 0.006

is in a good agreement with Chu et al () and Nouguier et al (). The dependence for slick in Ku‐band is obtained for the first time here as

σ_{t o t Ku_slick}^{2} = 0.0071 + 0.0018 U_{10} \pm 0.004 .

…”

Section: Mean Square Slope In the Slicksupporting

confidence: 83%

“…is in a good agreement with Chu et al (2012b) and Nouguier et al (2016). The dependence for slick in Kuband is obtained for the first time here as r 2 totKu slick 50:007110:0018U 10 60:004:…”

Section: Mean Square Slope In the Slicksupporting

confidence: 81%

“…The method for

σ^{0} true(0 true)

and

σ_{x}^{2}

retrieval is based on equation . Usually, as in Freilich and Vanhoff (), Chu and Chen (), Nouguier et al (), the parameters are obtained by solving the least squares problem. Below we discuss the application of the least squares regression method, and an alternative method is suggested.…”

Section: Methods To Extract Nrcs At Nadir and σX2 From Pr Datamentioning

confidence: 99%

“…In previous papers on PR and Dual‐frequency Precipitation Radar (DPR) data the dependency of NRCS on the incidence angle is presented at different wind speeds (Chu et al, ; Freilich & Vanhoff, ) and at various significant wave heights (SWH; Nouguier et al, ). These studies show that the dependence

σ^{0} true(θ true)

is stronger at lower sea states than at higher sea states.…”

Section: Distribution Of Nrcs Within Pr Swath: Contrast On a Surface mentioning

confidence: 99%

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Oil Slick Observation at Low Incidence Angles in Ku‐Band

2018

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On the 20 April 2010 the oil platform Deep Water Horizon in the Gulf of Mexico suffered an explosion during the final phases of drilling an exploratory well. As a result, an oil film covered the sea surface area of several thousand square kilometers. In the present paper the data of the Ku‐band Precipitation Radar, which operates at low incidence angles, were used to explore the oil spill event. The two‐scale model of the scattering surface was used to describe radar backscatter from the sea surface. The algorithm for retrieval of normalized radar cross section at nadir and the total slope variance of large‐scale waves compared to the wavelength of electromagnetic wave (22 mm) was developed for the Precipitation Radar swath. It is shown that measurements at low incidence angles can be used for oil spill detection. This is the first time that the dependence of mean square slope of large‐scale waves on wind speed has been obtained for oil slicks from Ku‐band data, and compared to mean square slope obtained by Cox and Munk from optical data.

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“…The experimental data and regression dependencies of

σ_{t o t}^{2}

on U 10 for oil‐covered and clean surface are presented in Figure a. The derived dependence for a clean surface,

σ_{t o t Ku_clean}^{2} = 0.0111 + 0.002 U_{10} \pm 0.006

is in a good agreement with Chu et al () and Nouguier et al (). The dependence for slick in Ku‐band is obtained for the first time here as

σ_{t o t Ku_slick}^{2} = 0.0071 + 0.0018 U_{10} \pm 0.004 .

…”

Section: Mean Square Slope In the Slicksupporting

confidence: 83%

Section: Mean Square Slope In the Slicksupporting

confidence: 81%

“…The method for

σ^{0} true(0 true)

and

σ_{x}^{2}

Section: Methods To Extract Nrcs At Nadir and σX2 From Pr Datamentioning

confidence: 99%

σ^{0} true(θ true)

is stronger at lower sea states than at higher sea states.…”

Section: Distribution Of Nrcs Within Pr Swath: Contrast On a Surface mentioning

confidence: 99%

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Oil Slick Observation at Low Incidence Angles in Ku‐Band

2018

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“…The other key parameter derived from the retracking process is the maximum amplitude of the radar echo, denoted by the normalized backscatter coefficient, σ 0 . This is primarily related to the statistics of surface slopes (Nouguier et al, 2016), usually summarized by the mean square slope (mss), which is primarily dependent upon the near surface wind speed at 10 m elevation, U 10 (Cox and Munk, 1954;Bréon and Henriot, 2006). Yet, second-order effects, diffraction, curvature, and/or non-Gaussian effects can still be traced, especially when directly comparing coincident altimeter measurements performed with differing operating frequencies, i.e., C-band and Ku-band for TOPEX and the JASON instruments (Chapron et al, 1995;Elfouhaily et al, 1998;Tran et al, 2006).…”

Section: Surface Roughness and Wind Speed From Altimetersmentioning

confidence: 99%

Observing Sea States

et al. 2019

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Sea state information is needed for many applications, ranging from safety at sea and on the coast, for which real time data are essential, to planning and design needs for infrastructure that require long time series. The definition of the wave climate and its possible evolution requires high resolution data, and knowledge on possible drift in the observing system. Sea state is also an important climate variable that enters in air-sea fluxes parameterizations. Finally, sea state patterns can reveal the intensity of storms and associated climate patterns at large scales, and the intensity of currents at small scales. A synthesis of user requirements leads to requests for spatial resolution at kilometer scales, and estimations of trends of a few centimeters per decade. Such requirements cannot be met by observations alone in the foreseeable future, and numerical wave models can be combined with in situ and remote sensing data to achieve the required resolution. As today's models are far from perfect, observations are critical in providing forcing data, namely winds, currents and ice, and validation data, in particular for frequency and direction information, and extreme wave heights. In situ and satellite observations are particularly critical for the correction and calibration of significant wave heights to ensure the stability of model time series. A number of developments are underway for extending the capabilities of satellites and in situ observing systems. These include the generalization of directional measurements, an easier exchange of moored buoy data, the measurement of waves on drifting buoys, the evolution of satellite altimeter technology, and the measurement of directional wave spectra from satellite radar instruments. For each of these observing systems, the stability of the data is a very important issue. The combination of the different data sources, including numerical models, can help better fulfill the needs of users.

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A global wave parameter database for geophysical 1 applications. Part 3: improved forcing and spectral 2 resolution

Alday¹,

Accensi²,

Ardhuin³

2020

Preprint

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Numerical wave models are used for a wide range of applications, from the global ocean to coastal scales. Here we report on significant improvements compared to the previous hindcast detailed in Part 2 of the present study by Rascle and Ardhuin (2013). This result was obtained by updating forcing fields, adjusting the spectral discretization and retuning wind wave growth and swell dissipation parameters. Most of the model calibration and performance analysis is done using significant wave heights (Hs) from the recent re-calibrated and denoised satellite altimeter data set provided by the European Space Agency Climate Change Initiative (ESA-CCI), with additional verification using spectral buoy data. We find that, for the year 2011, using wind fields from the recent ERA5 reanalysis provides lower scatter against satellite Hs data compared to historical ECMWF operational analyses, but still yields a low bias on wave heights that can be mitigated by re-scaling wind speeds larger than 20 m/s. Alternative blended wind products can provide more accurate forcing in some regions, but were not retained because of larger errors elsewhere. We use the shape of the probability density function of Hs around 2 m to fine tune the swell dissipation parameterization. The updated model hindcast appears to be generally more accurate than the previous version, and can be more accurate than the ERA5 Hs estimates, in particular in strong current regions and for Hs > 7 m. Highlights► An update on the Rascle and Ardhuin (2013) wave hindcast is presented. ► ERA5 wind forcing gives best results but requires a bias correction for high winds. ► Satellite altimeter data was used to adjust swell dissipation parameters.

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Analysis of Dual-Frequency Ocean Backscatter Measurements at Ku- and Ka-Bands Using Near-Nadir Incidence GPM Radar Data

Abstract: Please note that this is an author-produced PDF of an article accepted for publication following peer review. The definitive publisher-authenticated version is available on the publisher Web site.

Cited by 40 publications

References 22 publications

Oil Slick Observation at Low Incidence Angles in Ku‐Band

Oil Slick Observation at Low Incidence Angles in Ku‐Band

Observing Sea States

A global wave parameter database for geophysical 1 applications. Part 3: improved forcing and spectral 2 resolution

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