【摘要】：GPS探測(cè)大氣水汽的技術(shù)迅速發(fā)展和逐漸成熟,使得地基GPS氣象學(xué)基本理論得以發(fā)展和完善,地基GPS大氣水汽監(jiān)測(cè)網(wǎng)的積極建設(shè)以及其觀測(cè)資料的共享也為獲取高時(shí)間分辨率的大氣水汽資料奠定了基礎(chǔ),地基GPS氣象學(xué)正逐漸從技術(shù)研究階段步入業(yè)務(wù)化應(yīng)用階段。本論文的目標(biāo)是研究如何基于高密度的觀測(cè)資料獲取高精度的水汽產(chǎn)品,并結(jié)合探空資料、NECP再分析資料、多普勒雷達(dá)資料以及衛(wèi)星資料有效地應(yīng)用于災(zāi)害性天氣預(yù)報(bào)分析中,研究?jī)?nèi)容包括地基GPS不同水汽反演方法的改進(jìn)及誤差分析、地基GPS大氣水汽解算系統(tǒng)開發(fā)和建立、GPS大氣水汽探測(cè)資料在天氣預(yù)報(bào)分析中的應(yīng)用等方面。方法與結(jié)果如下： 1.結(jié)合2007-2008年探空資料對(duì)大氣加權(quán)平均溫度和天頂靜力延遲模型進(jìn)行本地化訂正。加權(quán)平均溫度本地化訂正后可以明顯地減小其與探空Tm的偏差,計(jì)算精度與Bevis Tm模型等方法相比明顯提高。在對(duì)天頂靜力延遲模型進(jìn)行本地化訂正后可顯著減小其與探空可降水量的偏差,提高其準(zhǔn)確度,上述兩種改進(jìn)都不會(huì)不影響大氣可降水量反演模型的精度。同時(shí),研究發(fā)現(xiàn)天頂靜力延遲模型精度受地面氣壓比地面溫度的影響大。因此,減小地面氣壓的測(cè)量誤差可提高天頂靜力延遲ZHD誤差的精度。 2.基于上述改進(jìn),建立地基GPS大氣水汽解算系統(tǒng)。實(shí)現(xiàn)每30分鐘一次高精度水汽解算數(shù)據(jù)。得到各測(cè)站每半時(shí)的高精度水汽分布。編寫的自動(dòng)化解算腳本適用于Linux系統(tǒng),移植性很強(qiáng)。 3.利用成都2007-2008年的地基GPS/MET網(wǎng)的觀測(cè)資料,并根據(jù)改進(jìn)的大氣加權(quán)平均溫度模型和天頂靜力延遲模型計(jì)算大氣可降水量,結(jié)合降雨資料分析其日變化、季節(jié)性變化以及降雨發(fā)生前后的變化特征,從中統(tǒng)計(jì)出降水和強(qiáng)降水閾值準(zhǔn)確性較高,可靠性好,可為預(yù)報(bào)員的臨近預(yù)報(bào)服務(wù)提供參考信息； 4.由于地基GPS僅提供大氣中的水汽條件,要想全面分析災(zāi)害性天氣發(fā)生過程,就要結(jié)合大氣中的動(dòng)力和熱力結(jié)構(gòu)特征。本研究充分利用探空資料、NECP再分析資料、多普勒雷達(dá)資料以及風(fēng)云衛(wèi)星資料進(jìn)行了分析,結(jié)果表明：暴雨發(fā)生前對(duì)流層呈現(xiàn)上干下濕的結(jié)構(gòu)特征,且低層大氣不穩(wěn)定能量較明顯；高時(shí)間分辨率的地基GPS資料不僅可以獲得水汽的實(shí)時(shí)變化的信息,而且對(duì)于暴雨的發(fā)生時(shí)間和暴雨的強(qiáng)度都有一定的指示性；結(jié)合中尺度數(shù)值模擬的結(jié)果,分析發(fā)現(xiàn)降水與否或降水大小不僅取決于大氣中水汽含量的多少,水汽輻合的強(qiáng)弱以及云團(tuán)的發(fā)展具有關(guān)鍵作用。
[Abstract]:The technology of detecting atmospheric water vapor by GPS has developed rapidly and gradually matured, which makes the basic theory of ground-based GPS meteorology develop and perfect. The active construction of ground-based GPS atmospheric water vapor monitoring network and the sharing of its observation data also lay the foundation for obtaining atmospheric water vapor data with high temporal resolution. The ground-based GPS meteorology is gradually moving from the technical research stage to the operational application stage. The purpose of this paper is to study how to obtain high precision water vapor products based on high density observation data, and to effectively apply the NECP reanalysis data, Doppler radar data and satellite data to the analysis of disastrous weather. The research contents include the improvement and error analysis of different water vapor inversion methods for foundation GPS, the development of ground-based GPS atmospheric water vapor calculation system and the establishment of the application of GPS atmospheric water vapor detection data in weather forecast and analysis. Methods and results are as follows: 1. The atmospheric weighted mean temperature and zenith static delay model are localized based on the 2007-2008 radiosonde data. The deviation between weighted mean temperature and sounding TM can be obviously reduced after localization correction, and the calculation precision is improved obviously compared with Bevis TM model. After localized correction of the zenith static delay model, the deviation from the radiosonde precipitable water can be significantly reduced, and its accuracy can be improved. Neither of the above two improvements will affect the accuracy of the atmospheric precipitable water inversion model. At the same time, it is found that the accuracy of the zenith static delay model is more affected by the surface pressure than the surface temperature. Therefore, the accuracy of ZHD error of zenith static delay can be improved by reducing the measurement error of ground pressure. Based on the above improvements, a ground-based GPS atmospheric vapor solution system is established. The high precision water vapor solution data is realized every 30 minutes. The high accuracy water vapor distribution of each station is obtained every half hour. The automatic solution script written for Linux system, portability is very strong. 3. Based on the observation data of GPS/MET network in Chengdu from 2007 to 2008, and based on the improved atmospheric weighted mean temperature model and the zenith static delay model, the precipitation of the atmosphere is calculated, and the daily variation of precipitation is analyzed by combining the rainfall data. Seasonal variation and change characteristics before and after the occurrence of rainfall, from which the high accuracy of precipitation and strong precipitation threshold, good reliability, can provide reference information for forecasters' near forecast service; 4. Because the ground-based GPS only provides the water vapor condition in the atmosphere, in order to analyze the occurrence process of the disastrous weather, it is necessary to combine the characteristics of the dynamic and thermal structure in the atmosphere. This study makes full use of sounding data and NECP reanalysis data, Doppler radar data and wind-cloud satellite data for analysis. The results show that the troposphere presents the structural characteristics of upper dryness and wetness before the rainstorm occurs. The low layer atmospheric instability energy is obvious, the high time resolution ground-based GPS data can not only obtain the information of the real time variation of water vapor, but also can indicate the occurrence time and the intensity of rainstorm. Based on the results of mesoscale numerical simulation, it is found that the precipitation or not depends not only on the amount of water vapor in the atmosphere, but also on the convergence of water vapor and the development of cloud clusters.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P228.4;P405

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本文編號(hào)：2185600