本文選題：海面鹽度 + 反演算法　； 參考：《華中科技大學(xué)》2016年碩士論文

【摘要】：海面鹽度是海洋系統(tǒng)中一個(gè)極其重要的參數(shù),它對(duì)研究海洋環(huán)境、全球水循環(huán)以及氣候的監(jiān)測(cè)和預(yù)測(cè)等有著巨大貢獻(xiàn)。近年來(lái),衛(wèi)星微波遙感測(cè)量海面鹽度的技術(shù)取得了快速的發(fā)展,使得大范圍全天候的鹽度觀測(cè)成為現(xiàn)實(shí)。但是目前在軌運(yùn)行的鹽度微波遙感衛(wèi)星SMOS和Aquarius的鹽度數(shù)據(jù)產(chǎn)品在全球范圍內(nèi)尚未達(dá)到預(yù)期精度,因此深入開展鹽度反演算法的研究具有良好的應(yīng)用價(jià)值。本文以實(shí)孔徑微波輻射計(jì)海面鹽度反演算法為主線,首先介紹了被動(dòng)微波遙感觀測(cè)海面鹽度的理論基礎(chǔ);在考慮了海面、大氣層、電離層和太空中眾多影響因素的條件下,建立了海面微波輻射正向傳輸模型,并仿真分析了入射角度、海面溫度、風(fēng)速和風(fēng)向等因素對(duì)海面亮溫貢獻(xiàn)的影響;接著在正向模型的基礎(chǔ)上對(duì)海面鹽度反演的統(tǒng)計(jì)回歸算法、神經(jīng)網(wǎng)絡(luò)算法和基于代價(jià)函數(shù)的迭代理論算法進(jìn)行了研究,并分別基于三種鹽度反演算法仿真分析了亮溫、海面溫度和風(fēng)速等參數(shù)誤差對(duì)鹽度反演精度的影響;最后,將利用Aquarius衛(wèi)星公布的鹽度數(shù)據(jù)以及其他輔助數(shù)據(jù)通過(guò)正向模型計(jì)算得到海面模擬亮溫值與Aquarius衛(wèi)星公布的實(shí)測(cè)亮溫?cái)?shù)據(jù)進(jìn)行比較,所得的亮溫誤差較小,從而驗(yàn)證了海面微波輻射正向模型的準(zhǔn)確性;此外,將利用Aquarius衛(wèi)星公布的實(shí)測(cè)亮溫?cái)?shù)據(jù)通過(guò)三種鹽度反演算法計(jì)算得到的鹽度值與Aquarius公布的鹽度數(shù)據(jù)進(jìn)行比較,結(jié)果表明,在低緯度開闊海域,單次鹽度反演所得的鹽度值與Aquarius公布的鹽度數(shù)據(jù)之間的均方根誤差約為0.36psu,從而驗(yàn)證了統(tǒng)計(jì)回歸反演算法、神經(jīng)網(wǎng)絡(luò)反演算法和基于代價(jià)函數(shù)的迭代反演算法的有效性。
[Abstract]:Sea surface salinity is a very important parameter in ocean system. It has great contribution to the study of marine environment, global water cycle and climate monitoring and prediction. In recent years, the satellite microwave remote sensing technology for sea surface salinity measurement has made rapid development, making the large-scale all-weather salinity observation become a reality. However, the expected precision of salinity data products of the salinity microwave remote sensing satellite SMOS and Aquarius in orbit has not reached the expected precision in the world, so the further research on salinity inversion algorithm has good application value. Based on the inversion algorithm of sea surface salinity of real aperture microwave radiometer, this paper first introduces the theoretical basis of passive microwave remote sensing observation of sea surface salinity, taking into account many influence factors in sea surface, atmosphere, ionosphere and space. The forward transmission model of sea surface microwave radiation is established, and the effects of incident angle, sea surface temperature, wind speed and wind direction on the contribution of sea surface brightness temperature are simulated, and then the statistical regression algorithm for sea surface salinity inversion based on the forward model is presented. The neural network algorithm and iterative algorithm based on cost function are studied, and the effects of parameter errors such as brightness temperature, sea surface temperature and wind speed on the accuracy of salinity inversion are simulated based on three salinity inversion algorithms. The salinity data published by Aquarius satellite and other auxiliary data are compared with the measured brightness temperature data published by Aquarius satellite through forward model calculation, and the brightness temperature error is small. The accuracy of the forward model of sea surface microwave radiation is verified. In addition, the salinity values calculated by three salinities inversion algorithms using the measured brightness temperature data published by Aquarius satellite are compared with the salinity data published by Aquarius, and the results show that, In the open sea area of low latitude, the root mean square error between the salinity value obtained by single salinity inversion and the salinity data published by Aquarius is about 0.36 psu. thus the statistical regression inversion algorithm is verified. The effectiveness of neural network inversion algorithm and cost function based iterative inversion algorithm.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：P715.7

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