【摘要】：基于Radarsat-2雷達(dá)數(shù)據(jù)具有多極化方式、多分辨率等成像模式的特點(diǎn),以中國(guó)東部海域?yàn)檠芯繀^(qū)選取多景Radarsat-2影像進(jìn)行海面風(fēng)速反演研究。采用導(dǎo)入ERA-Interim數(shù)據(jù)構(gòu)建初始海面風(fēng)向的方法,針對(duì)不同極化方式的Radarsat-2數(shù)據(jù),利用GMF模型和極化率模型組合進(jìn)行海面風(fēng)速反演,并將反演風(fēng)速與ERA-Interim風(fēng)速數(shù)據(jù)進(jìn)行比較分析。結(jié)果表明:對(duì)于VV極化的Radarsat-2數(shù)據(jù)采用3種GMF模型均可反演出較高精度的海面風(fēng)速,其中CMOD4模型總體表現(xiàn)好于其他二者,其均方根誤差可達(dá)到1.5m/s以內(nèi);HH極化Radarsat-2數(shù)據(jù)采用Kirchhoff模型進(jìn)行極化轉(zhuǎn)換更適用于海面風(fēng)速的反演,3種GMF模型之間反演效果差異不大,其均方根誤差均在2m/s以內(nèi)。同時(shí),研究發(fā)現(xiàn)VV和HH極化的Radarsat-2數(shù)據(jù)均表現(xiàn)出高分辨率成像模式影像的風(fēng)速反演效果優(yōu)于低分辨率成像模式的特點(diǎn)。
[Abstract]:Based on the characteristics of multi-polarization mode and multi-resolution imaging mode of Radarsat-2 radar data, the multi-scene Radarsat-2 images are selected for the study area in the eastern China Sea area for the study of sea surface wind speed inversion. The method of importing ERA-Interim data to construct the initial sea surface wind direction is used to construct the initial sea surface wind direction. Aiming at the Radarsat-2 data of different polarization modes, the sea surface wind speed inversion is carried out by using the combination of GMF model and polarizability model, and the inversion wind speed and ERA-Interim wind speed data are compared and analyzed. The results show that the high precision sea surface wind speed can be obtained by using three kinds of GMF models for VV polarized Radarsat-2 data, in which the CMOD4 model is better than the other two, and its root mean square error can reach less than 1.5m/s, and the polarization conversion of HH polarization Radarsat-2 data is more suitable for the inversion of sea surface wind speed, and the inversion effect of the three GMF models is not different, and the root mean square error is all within 2m/s. At the same time, it is found that both VV and HH polarized Radarsat-2 data show that the wind speed inversion effect of high resolution imaging mode image is better than that of low resolution imaging mode.
【作者單位】： 浙江大學(xué)農(nóng)業(yè)遙感與信息技術(shù)應(yīng)用研究所;江蘇省氣候中心;山東省氣候中心;杭州師范大學(xué)遙感與地球科學(xué)研究院;
【基金】：公益性行業(yè)(氣象)科研專項(xiàng)“多源測(cè)風(fēng)資料融合技術(shù)研究及其在風(fēng)能資源評(píng)估中的應(yīng)用”(GYHY201306050) 浙江省科技計(jì)劃項(xiàng)目“近海面風(fēng)場(chǎng)遙感協(xié)同反演方法研究及其應(yīng)用”(2013C33068)
【分類號(hào)】：P714.2;P715.7

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