本文選題：FY-3B + 微波遙感�。� 參考：《南京信息工程大學(xué)》2017年碩士論文

【摘要】：土壤濕度通過改變地表反照率、感熱、潛熱、調(diào)節(jié)和控制陸地與底層大氣之間的水汽和能量交換,從而對氣候和天氣過程產(chǎn)生重要影響。本文基于風(fēng)云三號(FY-3B)衛(wèi)星微波資料反演了我國青藏高原地區(qū)逐目地表土壤濕度。隨后將地表參數(shù)反演模型(Land Parameter Retrieval Model,LPRM)的土壤濕度數(shù)據(jù)與 VIC (Variable Infiltration Capacity)水文模型模擬的土.壤濕度數(shù)據(jù)以及Era-Interim再分析資料進(jìn)行對比分析;基于那曲地區(qū)地表溫度站點觀測數(shù)據(jù)對LPRM模型中的地表溫度反演模塊進(jìn)行改進(jìn),從而提高LPRM模型在青藏高原地區(qū)反演的十壤濕度的精度;利用傳統(tǒng)統(tǒng)計學(xué)方法和TC評估方法對LPRMV06數(shù)據(jù)在青藏高原地區(qū)的十壤濕度數(shù)據(jù)進(jìn)行驗證分析。得到主要結(jié)論如下:(1)就絕對量而言, LPRM反演十壤濕度與那曲地區(qū)站點觀測數(shù)據(jù)的偏差較大。ERA-Interim再分析資料與VIC水文模型模型模擬資料的絕對量偏差顯著低于LPRM反演土壤濕度。就時間變化而言,LPRM 土壤濕度數(shù)據(jù)與那曲地區(qū)觀測數(shù)據(jù)的相關(guān)系數(shù)最高,ERA-Interim再分析資料次之,VIC水文模型模擬資料最低。這表明LPRM十壤濕度與觀測資料的時間變化最為一致。(2)從時間變化上來看,通過對比暖季期間原始LPRM反演出的十壤濕度數(shù)據(jù)和改進(jìn)后的LPRM反演出的土壤濕度數(shù)據(jù),結(jié)果表明相關(guān)系數(shù)沒有改變,但是絕對量方面得到有效的降低,其中RMSD降低30%, ubRMSD降低10%。(3) LPRMV06土壤濕度數(shù)據(jù)、ECV 土壤濕度數(shù)據(jù)和ERA-Interim 土壤濕度數(shù)據(jù)在三季年際平均分布圖中均呈現(xiàn)著青藏高原東南向西北遞減的變化特征,而TMI 土壤濕度數(shù)據(jù)切呈現(xiàn)著自青藏高原東南向西北遞減的變化特征。LPRMV06 土壤濕度數(shù)據(jù)與ECV 土壤濕度數(shù)據(jù)在青藏高原地區(qū)的時間變化一致性最好,與ERA-Interim 土壤濕度數(shù)據(jù)的時間變化一致性較好,與TMI 土壤濕度數(shù)據(jù)的時間變化一致性較差;從各個土壤濕度數(shù)據(jù)的自身空間分布方面而言,四套數(shù)據(jù)均呈現(xiàn)了東部地區(qū)與西部地區(qū)的土壤濕度時間變化相反這一特點;從TC比較結(jié)果而言,LPRMV06 土壤濕度數(shù)據(jù)與假設(shè)真值的時間變化一致性最好,ECV數(shù)據(jù)其次,ERA-Interim 土壤濕度數(shù)據(jù)在青藏高原地區(qū)與假設(shè)真值的時間變化一致性較差。
[Abstract]:Soil moisture influences the climate and weather process by changing the surface albedo, sensible heat, latent heat, regulating and controlling the water vapor and energy exchange between the land and the lower atmosphere. Based on the FY-3B satellite microwave data of Fengyun No. 3, the surface soil moisture of Qinghai-Xizang Plateau has been retrieved. Then the soil moisture data of Land Parameter Retrieval Model and the soil of VIC variable Infiltration capacity model are simulated. The soil moisture data and Era-Interim reanalysis data are compared and analyzed, and the inversion module of surface temperature in LPRM model is improved based on the ground temperature observation data of Naqu area. In order to improve the accuracy of LPRM model inversion of soil moisture in Qinghai-Tibet Plateau, the traditional statistical method and TC evaluation method are used to verify and analyze the ten soil moisture data from LPRMV06 data in Qinghai-Xizang Plateau. The main conclusions are as follows: (1) in terms of absolute quantity, the deviation between LPRM inversion of soil moisture and the observed data of Naqu station is larger. The absolute deviation of ERA-Interim reanalysis data and VIC hydrological model simulation data is significantly lower than that of LPRM inversion soil moisture. In terms of time variation, the correlation coefficient between soil moisture data of LPRM and observed data in Naqu area is the highest. The simulation data of VIC hydrological model is the lowest, followed by ERA-Interim reanalysis data. This indicates that the temporal variation of LPRM ten soil moisture is the most consistent with that of observed data. (2) from the point of view of time variation, the soil moisture data of the original LPRM reverse performance during warm season and the improved LPRM reverse performance are compared. The results show that the correlation coefficient has not changed, but the absolute quantity has been reduced effectively. Among them, RMSD decreased 30%, ubRMSD decreased 10%) LPRMV06 soil moisture data and ERA-Interim soil moisture data showed the characteristics of decreasing from southeast to northwest of Qinghai-Xizang Plateau in three seasons. However, TMI soil moisture data showed a decreasing trend from southeast to northwest of Qinghai-Xizang Plateau. The temporal variation of LPRMV06 soil moisture data and ECV soil moisture data in Qinghai-Xizang Plateau was the best. The consistency of time variation with ERA-Interim soil moisture data is better than that with TMI soil moisture data. The four sets of data all showed the opposite change of soil moisture time between the eastern region and the western region. From the TC comparison results, the time variation of LPRMV06 soil moisture data and the assumed true value is the best. Secondly, the ERA-Interim soil moisture data in the Qinghai-Xizang Plateau is less consistent with the assumed true value.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S152.71

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 解承瑩;李敏姣;張雪芹;關(guān)學(xué)鋒;;青藏高原南緣關(guān)鍵區(qū)夏季水汽輸送特征及其與高原降水的關(guān)系[J];高原氣象;2015年02期

2 劉強(qiáng);杜今陽;施建成;蔣玲梅;;青藏高原表層土壤濕度遙感反演及其空間分布和多年變化趨勢分析[J];中國科學(xué):地球科學(xué);2013年10期

3 何媛;文軍;張?zhí)锰?田輝;劉蓉;呂少寧;賴欣;;衛(wèi)星微波遙感結(jié)合可見光遙感估算黃河源區(qū)土壤濕度研究[J];遙感技術(shù)與應(yīng)用;2013年02期

4 陳書林;劉元波;溫作民;;衛(wèi)星遙感反演土壤水分研究綜述[J];地球科學(xué)進(jìn)展;2012年11期

5 施建成;杜陽;杜今陽;蔣玲梅;柴琳娜;毛克彪;徐鵬;倪文儉;熊川;劉強(qiáng);劉晨洲;郭鵬;崔倩;李云青;陳晶;王安琪;羅禾佳;王殷輝;;微波遙感地表參數(shù)反演進(jìn)展[J];中國科學(xué):地球科學(xué);2012年06期

6 盧麾;施建成;;基于遙感觀測的21世紀(jì)初中國區(qū)域地表土壤水及其變化趨勢分析[J];科學(xué)通報;2012年16期

7 伍漫春;丁建麗;王高峰;;基于地表溫度-植被指數(shù)特征空間的區(qū)域土壤水分反演[J];中國沙漠;2012年01期

8 李明星;馬柱國;牛國躍;;中國區(qū)域土壤濕度變化的時空特征模擬研究[J];科學(xué)通報;2011年16期

9 賈文雄;;祁連山氣候的空間差異與地理位置和地形的關(guān)系[J];干旱區(qū)研究;2010年04期

10 左志燕;張人禾;;中國東部春季土壤濕度的時空變化特征[J];中國科學(xué)(D輯:地球科學(xué));2008年11期

相關(guān)會議論文 前1條

1 李理;李棟梁;;青藏高原土壤濕度對黃河流域夏季降水的影響[A];S4 青藏高原及鄰近地區(qū)天氣氣候影響[C];2012年

相關(guān)碩士學(xué)位論文 前1條

1 陳立波;中國區(qū)域衛(wèi)星遙感土壤濕度的時空變化及其對東部夏季降水的可能影響[D];南京信息工程大學(xué);2015年

，

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