Assessing the Bayesian inversion technique of C-band synthetic aperture radar data for the retrieval of wind fields in marine coastal areas

Adamo, Maria; Rana, Fabio Michele; Carolis, Giacomo De; Pasquariello, G.

doi:10.1117/1.jrs.8.083531

Cited by 15 publications

(11 citation statements)

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“…Thus the estimation of wind fields obtained by means of a Bayesian approach (Adamo et al, 2014) exploits both the radar cross section of the normalized SAR and external information, such as the fields of wind meteorological models (Numerical Weather Product). Results show that although SAR wind fields were able to solve fine-scale spatial patterns and improve wave downscaling in the study area, especially during bora wind events due to complex orography on the Istrian coast, the following weaknesses were found:…”

Section: Resultsmentioning

confidence: 99%

On the feasibility of the use of wind SAR to downscale waves on shallow water

et al. 2016

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Abstract. In recent years, wave reanalyses have become popular as a powerful source of information for wave climate research and engineering applications. These wave reanalyses provide continuous time series of offshore wave parameters; nevertheless, in coastal areas or shallow water, waves are poorly described because spatial resolution is not detailed. By means of wave downscaling, it is possible to increase spatial resolution in high temporal coverage simulations, using forcing from wind and offshore wave databases. Meanwhile, the reanalysis wave databases are enough to describe the wave climate at the limit of simulations; wind reanalyses at an adequate spatial resolution to describe the wind structure near the coast are not frequently available. Remote sensing synthetic aperture radar (SAR) has the ability to detect sea surface signatures and estimate wind fields at high resolution (up to 300 m) and high frequency.In this work a wave downscaling is done on the northern Adriatic Sea, using a hybrid methodology and global wave and wind reanalysis as forcing. The wave fields produced were compared to wave fields produced with SAR winds that represent the two dominant wind regimes in the area: the bora (ENE direction) and sirocco (SE direction). Results show a good correlation between the waves forced with reanalysis wind and SAR wind. In addition, a validation of reanalysis is shown. This research demonstrates how Earth observation products, such as SAR wind fields, can be successfully uptaken into oceanographic modeling, producing similar downscaled wave fields when compared to waves forced with reanalysis wind.

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Section: Resultsmentioning

confidence: 99%

On the feasibility of the use of wind SAR to downscale waves on shallow water

et al. 2016

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“…We adopt the low wind speed range ( V < 5 m/s), moderate wind speed range (5 ≤ V < 10 m/s), and high wind speed range ( V ≥ 10 m/s) [ Adamo et al ., ] and set 3 m/s, 8 m/s, and 25 m/s as three typical cases. The three lines labeled 3 m/s, 8 m/s, and 25 m/s in Figure show three conditions of NRCS as a function of ϕ .…”

Section: Gmf Propertymentioning

confidence: 99%

“…That is to say, DNVAR can efficiently improve wind direction retrieval accuracy for higher wind speed, which is similar to the result of Adamo et al . []. For V B ≥ 10 m/s, V DE < V RE , and ϕ DE < ϕ RE .…”

Section: Numerical Simulation Experimentsmentioning

confidence: 99%

“…[] and Adamo et al . [] investigated the accuracy of SAR‐derived wind fields with respect to different scales. Other marine phenomena such as internal waves, surface currents, and atmospheric fronts [ Stopa et al ., ] can also manifest streaks on SAR images, but these streaks may not be induced by winds.…”

Section: Introductionmentioning

confidence: 99%

“…Meanwhile, ϕ DE decreases slightly, which is smaller than ϕ BE and ϕ RE . That is to say, DNVAR can efficiently improve wind direction retrieval accuracy for higher wind speed, which is similar to the result ofAdamo et al [2014]. For V…”

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A damped Newton variational inversion method for SAR wind retrieval

Jiang

et al. 2017

JGR Atmospheres

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The variational inversion for synthetic aperture radar (SAR) wind retrieval can take all sources' errors into account, but its iterative computation is very time consuming. For the wind vectors, (u, v) components are commonly used for variational inversion, but they are not intuitive for practical applications. In this paper, we modify the decomposition of wind vectors in the cost function into wind speed and wind direction and adopt the damped Newton method (DNVAR) to solve the cost function. Experimental results on simulated data show that DNVAR can effectively reduce background wind vector errors. Additionally, the average number of iterations is reduced drastically compared to prior arts. Furthermore, a detailed comparison between direct SAR wind retrieval (DIRECT) and DNVAR is performed. Simulations reveal that the DNVAR errors are smaller than the background wind vector errors in all considered cases. Thus, DNVAR could be employed to retrieve SAR sea surface wind. For practical applications, when the background wind speed is within moderate and high wind speed range, DNVAR has higher accuracy and is thus preferred. Otherwise, both DNVAR and DIRECT are feasible, considering the unknown actual errors of both background wind vectors and geophysical model function. Experimental results on Envisat/advanced synthetic aperture radar data show that the wind speed accuracy of DIRECT is largely affected by the background wind direction errors, but DNVAR can reduce the wind direction errors with minor effect on the wind speed errors in comparison with the background wind errors.

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Advanced geosynchronous radiation imager thermal infrared channel-to-channel co-registration algorithm based on cloud information and phase correlation

et al. 2021

Opt Quant Electron

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Assessing the Bayesian inversion technique of C-band synthetic aperture radar data for the retrieval of wind fields in marine coastal areas

Cited by 15 publications

References 0 publications

On the feasibility of the use of wind SAR to downscale waves on shallow water

On the feasibility of the use of wind SAR to downscale waves on shallow water

A damped Newton variational inversion method for SAR wind retrieval

Advanced geosynchronous radiation imager thermal infrared channel-to-channel co-registration algorithm based on cloud information and phase correlation

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