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Impact of rain on wave retrieval from Sentinel-1 synthetic aperture radar images in tropical cyclones
Advances in Space Research ( IF 2.8 ) Pub Date : 2021-02-18 , DOI: 10.1016/j.asr.2021.01.050
X.B. Zhao , W.Z. Shao , L.B. Zhao , Y. Gao , Y.Y. Hu , X.Z. Yuan

The main objective of our work was to investigate the impact of rain on wave observations from C-band (~5.3 GHz) synthetic aperture radar (SAR) in tropical cyclones. In this study, 10 Sentinel-1 SAR images were available from the Satellite Hurricane Observation Campaign, which were taken under cyclonic conditions during the 2016 hurricane season. The third-generation wave model, known as Simulating WAves Nearshore (SWAN) (version 41.31), was used to simulate the wave fields corresponding to these Sentinel-1 SAR images. In addition, rainfall data from the Tropical Rainfall Measuring Mission satellite passing over the spatial coverage of the Sentinel-1 SAR images were collected. The simulated results were validated against significant wave heights (SWHs) from the Jason-2 altimeter and European Centre for Medium-Range Weather Forecasts data, revealing a root mean square error (RMSE) of ~0.5 m with a 0.25 scatter index. Winds retrieved from the VH-polarized Sentinel-1 SAR images using the Sentinel-1 Extra Wide-swath Mode Wind Speed Retrieval Model after Noise Removal were taken as prior information for wave retrieval. It was discovered that rain did indeed affect the SAR wave retrieval, as evidenced by the 3.21-m RMSE of SWHs between the SAR images and the SWAN model, which was obtained for the ~1000 match-ups with raindrops. The raindrops dampened the wave retrieval when the rain rate was < ~5 mm/hr; however, they enhanced wave retrieval for higher rain rates. It was also found that the portion of the rain-induced ring wave with a wave number > 0.05 rad/m (~125 m wavelength) was clearly observed in the SAR-derived wave spectra.



中文翻译:

雨水对热带气旋中Sentinel-1合成孔径雷达图像反演波的影响

我们工作的主要目的是研究降雨对热带气旋C波段(〜5.3 GHz)合成孔径雷达(SAR)的波观测的影响。在这项研究中,从卫星飓风观察运动获得了10张Sentinel-1 SAR图像,这些图像是在2016年飓风季节的气旋条件下拍摄的。第三代波浪模型,称为“近岸模拟波浪”(SWAN)(版本41.31),用于模拟与这些Sentinel-1 SAR图像相对应的波场。此外,还收集了来自热带雨量测量团卫星的降雨数据,这些卫星经过了Sentinel-1 SAR图像的空间覆盖。根据Jason-2高度计和欧洲中距离天气预报中心的数据,针对明显的波高(SWH)验证了模拟结果,揭示〜0.5 m的均方根误差(RMSE)和0.25分散指数。在去除噪声后,使用Sentinel-1超宽幅模式风速反演模型从VH极化的Sentinel-1 SAR图像中检索到的风被用作波浪检索的先验信息。据发现,降雨确实影响了SAR波的反演,如SAR图像和SWAN模型之间SWH的3.21-m RMSE所证明的那样,这是在约1000个与雨滴匹配的情况下获得的。当降雨速率<〜5 mm / hr时,雨滴阻碍了波浪的恢复;但是,它们提高了波浪检索的效率,从而提高了降雨率。还发现,在SAR派生的波谱中清楚地观察到了雨致环形波的部分,其波数> 0.05 rad / m(〜125 m波长)。25个散点索引。在去除噪声后,使用Sentinel-1超宽幅模式风速反演模型从VH极化的Sentinel-1 SAR图像中检索到的风被用作波浪检索的先验信息。据发现,降雨确实影响了SAR波的反演,如SAR图像和SWAN模型之间SWH的3.21-m RMSE所证明的那样,这是在约1000个与雨滴匹配的情况下获得的。当降雨速率<〜5 mm / hr时,雨滴阻碍了波浪的恢复;但是,它们增强了波浪检索功能,以提高降雨率。还发现,在SAR派生的波谱中清楚地观察到了雨致环形波的部分,其波数> 0.05 rad / m(〜125 m波长)。25个散点索引。在去除噪声后,使用Sentinel-1超宽幅模式风速反演模型从VH极化的Sentinel-1 SAR图像中检索到的风被用作波浪检索的先验信息。据发现,降雨确实影响了SAR波的反演,如SAR图像和SWAN模型之间SWH的3.21-m RMSE所证明的那样,这是在约1000个与雨滴匹配的情况下获得的。当降雨速率<〜5 mm / hr时,雨滴阻碍了波浪的恢复;但是,它们增强了波浪检索功能,以提高降雨率。还发现,在SAR派生的波谱中清楚地观察到了雨致环形波的部分,其波数> 0.05 rad / m(〜125 m波长)。在去除噪声后,使用Sentinel-1超宽幅模式风速反演模型从VH极化的Sentinel-1 SAR图像中检索到的风被用作波浪检索的先验信息。据发现,降雨确实影响了SAR波的反演,如SAR图像和SWAN模型之间SWH的3.21-m RMSE所证明的那样,这是在约1000个与雨滴匹配的情况下获得的。当降雨速率<〜5 mm / hr时,雨滴阻碍了波浪的恢复;但是,它们增强了波浪检索功能,以提高降雨率。还发现,在SAR派生的波谱中清楚地观察到了雨致环形波的部分,其波数> 0.05 rad / m(〜125 m波长)。在去除噪声后,使用Sentinel-1超宽幅模式风速反演模型从VH极化的Sentinel-1 SAR图像中检索到的风被用作波浪检索的先验信息。据发现,降雨确实影响了SAR波的反演,如SAR图像和SWAN模型之间SWH的3.21-m RMSE所证明的那样,这是在约1000个与雨滴匹配的情况下获得的。当降雨速率<〜5 mm / hr时,雨滴阻碍了波浪的恢复;但是,它们增强了波浪检索功能,以提高降雨率。还发现,在SAR派生的波谱中清楚地观察到了雨致环形波的部分,其波数> 0.05 rad / m(〜125 m波长)。据发现,降雨确实影响了SAR波的反演,如SAR图像和SWAN模型之间SWH的3.21-m RMSE所证明的那样,这是在约1000个与雨滴匹配的情况下获得的。当降雨速率<〜5 mm / hr时,雨滴阻碍了波浪的恢复;但是,它们增强了波浪检索功能,以提高降雨率。还发现,在SAR派生的波谱中清楚地观察到了雨致环形波的部分,其波数> 0.05 rad / m(〜125 m波长)。据发现,降雨确实影响了SAR波的反演,如SAR图像和SWAN模型之间SWH的3.21-m RMSE所证明的那样,这是在约1000个与雨滴匹配的情况下获得的。当降雨速率<〜5 mm / hr时,雨滴阻碍了波浪的恢复;但是,它们增强了波浪检索功能,以提高降雨率。还发现,在SAR派生的波谱中清楚地观察到了雨致环形波的部分,其波数> 0.05 rad / m(〜125 m波长)。

更新日期:2021-04-16
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