A Backscattering Model of Rainfall Over Rough Sea Surface for Synthetic Aperture Radar

Xu, Feng; Li, Xiaofeng; Wang, Peng; Yang, Jingsong; Pichel, William G.; Jin, Ya‐Qiu

doi:10.1109/tgrs.2014.2367654

Cited by 69 publications

(34 citation statements)

References 40 publications

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“…The effects of wind waves on radar backscattering are examined by using a backscattering model of rainfall over rough sea surface for synthetic aperture radar recently developed by Xu et al . []. In the model, the effects of the raindrops in the air, rain‐induced ring‐waves, and wind‐induced short waves on radar backscattering are investigated.…”

Section: Discussionmentioning

confidence: 94%

“…In the model, the effects of the raindrops in the air, rain‐induced ring‐waves, and wind‐induced short waves on radar backscattering are investigated. Dominating factors at different wind/rain circumstances for VV polarization backscattering at C‐band are predicted [see Xu et al ., , Figure 14]. As for the SAR image shown in Figure of the present paper, the weather charts (see section 4) show that at the time the SAR image was taken, the wind speed for the most region of the rain system was approximately equal or less than 6 m/s.…”

Section: Discussionmentioning

confidence: 94%

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A study of radar backscattering from water surface in response to rainfall

et al. 2016

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In this paper, radar backscattering from a water surface in response to rainfall was studied. The paper consists of two parts. First, the spatial characteristics of raindrops in rain fields were analyzed based on published data and the response of a water surface to rainfall was experimentally studied in the laboratory. Rain‐generated surface features including stalks, crowns, ring waves, and secondary drops were measured. It was found that stalks and crowns are dominant in terms of their height and energy. Second, the radar signatures of a rainfall event simultaneously observed by C band ENVISAT (European satellite), ASAR (Advanced Synthetic Aperture Radar), and ground‐based weather radar in the Northwest Pacific were investigated. The relationship between the radar return intensity extracted from the C band ASAR image and the reflectivity factor (rain rate) obtained from ground‐based weather radar was analyzed. For light/moderate rain (with low reflectivity factors), the radar backscattering intensity increases as the reflectivity factor increases. For heavy rain (with high reflectivity factors), the radar backscattering intensity decreases as the reflectivity factor increases. The maximum radar backscattering intensity occurs at a reflectivity factor of 45 dBZ (with rain rate of 24 mm/h). It was found that the spaceborne radar backscattering intensity strongly correlates with the average distance between the stalks on the water surface in the rain field in a nonlinear manner. The physics of the radar signatures of the rain event are explored.

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 94%

A study of radar backscattering from water surface in response to rainfall

et al. 2016

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“…Almost all mean biases are less than 1 dB, and most maximal biases are restrained in 1 dB. For an analytical approximate model, these indicate a good accuracy of our model at L-band [17,20,23,24]. In the range of 3-8 m/s wind speed, the NUC asymmetry of the L-band sea surface backscatter, which may also be called "M-shape" feature, was simulated well.…”

Section: Resultsmentioning

confidence: 52%

“…In practical computations, this range also depends on the selection of scattering model and wave spectrum. The range for the IEM/Fung-Lee model was suggested by Xu et al [20] and Marrazzo et al [42] as (k 0 *0.4, k 0 *10). Accordingly, by comparing with the in situ measured sea surface geometric data and the satellite observations, we generally believe that the wavenumber range of waves coupled with microwaves is between k 0 /10 and k 0 *10, where the microwave wavenumber k 0 = 26.39 rad/m in 1.26 GHz (also shown in Figure 1).…”

Section: Scattering Modelmentioning

confidence: 99%

An Improved Spectrum Model for Sea Surface Radar Backscattering at L-Band

Yang

Chen

et al. 2017

Remote Sensing

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L-band active microwave remote sensing is one of the most important technical methods of ocean environmental monitoring and dynamic parameter retrieval. Recently, a unique negative upwind-crosswind (NUC) asymmetry of L-band ocean backscatter over a low wind speed range was observed. To study the directional features of L-band ocean surface backscattering, a new directional spectrum model is proposed and built into the advanced integral equation method (AIEM). This spectrum combines Apel's omnidirectional spectrum and an improved empirical angular spreading function (ASF). The coefficients in the ASF were determined by the fitting of radar observations so that it provides a better description of wave directionality, especially over wavenumber ranges from short-gravity waves to capillary waves. Based on the improved spectrum and the AIEM scattering model, L-band NUC asymmetry at low wind speeds and positive upwind-crosswind (PUC) asymmetry at higher wind speeds are simulated successfully. The model outputs are validated against Aquarius/SAC-D observations under different incidence angles, azimuth angles and wind speed conditions.

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“…With regard to this, S-band radar is a promising tool since, due to its longer wavelength, it can yield wave measurements under rain conditions [119]. Recently, models for SAR backscatter from the ocean surface under rainfall have been developed [120,121]. X-band marine radar sea surface imaging mechanisms in rain events are also worth exploring.…”

Section: Discussionmentioning

confidence: 99%

Ocean Wind and Wave Measurements Using X-Band Marine Radar: A Comprehensive Review

2017

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Ocean wind and wave parameters can be measured by in-situ sensors such as anemometers and buoys. Since the 1980s, X-band marine radar has evolved as one of the remote sensing instruments for such purposes since its sea surface images contain considerable wind and wave information. The maturity and accuracy of X-band marine radar wind and wave measurements have already enabled relevant commercial products to be used in real-world applications. The goal of this paper is to provide a comprehensive review of the state of the art algorithms for ocean wind and wave information extraction from X-band marine radar data. Wind measurements are mainly based on the dependence of radar image intensities on wind direction and speed. Wave parameters can be obtained from radar-derived wave spectra or radar image textures for non-coherent radar and from surface radial velocity for coherent radar. In this review, the principles of the methodologies are described, the performances are compared, and the pros and cons are discussed. Specifically, recent developments for wind and wave measurements are highlighted. These include the mitigation of rain effects on wind measurements and wave height estimation without external calibrations. Finally, remaining challenges and future trends are discussed.

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A Backscattering Model of Rainfall Over Rough Sea Surface for Synthetic Aperture Radar

Cited by 69 publications

References 40 publications

A study of radar backscattering from water surface in response to rainfall

A study of radar backscattering from water surface in response to rainfall

An Improved Spectrum Model for Sea Surface Radar Backscattering at L-Band

Ocean Wind and Wave Measurements Using X-Band Marine Radar: A Comprehensive Review

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