本文選題：地基GPS + 大氣可降水量��； 參考：《昆明理工大學(xué)》2013年碩士論文

【摘要】：目前,地基GPS反演大氣可降水量技術(shù)已經(jīng)在氣象領(lǐng)域開始得到廣泛的研究應(yīng)用。本文主要利用bjfs站、shao站、1haz站和kunm站四個(gè)IGS站還有l(wèi)qua站、tanz站、xiah站、shil站和qinl站五個(gè)區(qū)域CORS站共九個(gè)站2012年全年的連續(xù)觀測(cè)數(shù)據(jù),對(duì)大氣可降水量測(cè)定的理論、方法以及誤差進(jìn)行分析。而本文的重點(diǎn)內(nèi)容是如何利用GAMIT軟件對(duì)大批量GPS觀測(cè)數(shù)據(jù)進(jìn)行自動(dòng)批處理及相關(guān)數(shù)據(jù)提取,并對(duì)解算結(jié)果進(jìn)行綜合分析,從而得到了有益的結(jié)論。本文主要的研究?jī)?nèi)容有： (1)首先介紹了大氣水汽監(jiān)測(cè)的重要性以及傳統(tǒng)探測(cè)大氣水汽的手段及不足,重點(diǎn)說(shuō)明地基GPS探測(cè)大氣水汽的特點(diǎn)以及優(yōu)勢(shì),并對(duì)GPS反演大氣水汽含量的過(guò)程進(jìn)行了論述。 (2)GAMIT軟件是處理GPS數(shù)據(jù)的高精度解算軟件,在應(yīng)用過(guò)程中如何通過(guò)編寫數(shù)據(jù)自動(dòng)批處理命名腳本來(lái)完成數(shù)據(jù)處理解算以及相關(guān)數(shù)據(jù)提取的自動(dòng)化,從而提高數(shù)據(jù)處理流程的效率是本文的研究?jī)?nèi)容之一。 (3)將加權(quán)平均溫度局地化是本文的重點(diǎn)之一。本文利用昆明的探空資料,通過(guò)統(tǒng)計(jì)的方法,建立可昆明地區(qū)局部加權(quán)平均溫度計(jì)算模型,并對(duì)其精度進(jìn)行分析。對(duì)Bevis經(jīng)驗(yàn)?zāi)Ｐ凸皆诶ッ鞯貐^(qū)的適用性分析表明Bevis經(jīng)驗(yàn)?zāi)Ｐ驮诶ッ饕彩沁m用的。 (4)通過(guò)對(duì)bjfs站有無(wú)實(shí)時(shí)氣象數(shù)據(jù)參與的兩種處理結(jié)果的分析,得到了有無(wú)實(shí)時(shí)氣象數(shù)據(jù)對(duì)GPS反演大氣可降水量精度的影響。對(duì)不同測(cè)站之間的數(shù)據(jù)解算結(jié)果進(jìn)行分析表明GPS/PWV總量除了受到海拔高度的影響,局部GPS/PWV總量還將受到地理緯度、大氣環(huán)流、地形地貌等其他因素的影響。 (5)對(duì)Kunm站、lqua站、qinl站、shil站、tanz站、xiah站這六個(gè)CORS站的數(shù)據(jù)分析表明,昆明GPS/PWV月變化明顯,12月GPS/PWV值維持在一年中的最低位置,3月開始逐漸增加,7月達(dá)到全年最高,8-12月GPS/PWV值逐漸變小。而且昆明地區(qū)平均GPS/PWV值的季節(jié)變化特征與季風(fēng)氣候下低緯度高原干濕季分明,干季一般為11月到次年4月,雨季一般為5月到10月的氣候特征對(duì)應(yīng)較好。 (6)對(duì)Kunm站、lqua站、qinl站、shil站、tanz站、xiah站這六個(gè)CORS站的數(shù)據(jù)分析表明滇池對(duì)周邊區(qū)域上空的大氣可降水量有影響,處在滇池周邊不同方向的位置所受影響的程度不一樣,主要受到滇池流域氣候風(fēng)向的影響。 (7)對(duì)昆明5.24和北京7.21暴雨過(guò)程進(jìn)行研究表明當(dāng)GPS可降水量的快速增加、呈現(xiàn)高值以及相對(duì)于平均值出現(xiàn)較大偏差時(shí)說(shuō)明大氣中水汽在急劇上升,這就為降雨提供充沛的水汽條件,滿足了降雨的條件之一。所以這對(duì)強(qiáng)降水天氣預(yù)報(bào)具有較好的指示意義。
[Abstract]:At present, ground-based GPS inversion of atmospheric precipitable water has been widely used in the field of meteorology. In this paper, the theory of atmospheric precipitation measurement is based on the continuous data of nine stations in 2012 from four bjfs stations and four kunm stations, as well as the five regional cors stations from lqua station, Guanz station, Shishil station and qinl station, in the whole year of 2012. Method and error analysis. The key content of this paper is how to use Gamit software to carry on the automatic batch processing and the correlation data extraction to the massive GPS observation data, and carries on the synthesis analysis to the solution result, thus obtains the beneficial conclusion. The main research contents of this paper are as follows: firstly, the importance of atmospheric water vapor monitoring and the traditional methods and shortcomings of detecting atmospheric water vapor are introduced, and the characteristics and advantages of ground-based GPS in detecting atmospheric water vapor are emphasized. The process of inversion of atmospheric water vapor content by GPS is also discussed. In the process of application, how to write automatic batch naming script to complete the automation of data processing solution and related data extraction, Therefore, improving the efficiency of the data processing process is one of the research contents in this paper, and the localization of weighted average temperature is one of the emphases of this paper. Based on the sounding data of Kunming and the statistical method, a local weighted average temperature calculation model for Kunming area is established and its accuracy is analyzed. An analysis of the applicability of the Bevis empirical model formula in Kunming area shows that the Bevis empirical model is also applicable in Kunming. The influence of real-time meteorological data on the accuracy of GPS retrieval of atmospheric precipitable water is obtained. The analysis of the data solution between different stations shows that apart from the influence of altitude, the local GPS / PWV will also be affected by geographical latitude and atmospheric circulation. Effect of other factors, such as topography and geomorphology. The monthly change of Kunming GPS / PWV is obvious. In December, the value of GPS / PWV kept at the lowest position in a year, and gradually increased in March, and reached the highest in July. The value of GPS / PWV gradually decreased in August to December. Moreover, the seasonal variation characteristics of the average GPS / PWV value in Kunming are distinct from the dry and wet seasons in the low-latitude plateau in the monsoon climate. The dry season is usually from November to April of the following year. In the rainy season, the climatic characteristics from May to October correspond well. The data analysis of the six cors stations at Qulqua station and Qinl station in Kunm station and Shishil station in Huixiah station shows that Dianchi Lake has an effect on the precipitation of the atmosphere over the surrounding area. The influence of different directions around Dianchi Lake is different, which is mainly affected by the climatic wind direction of Dianchi Lake Basin. The study on the heavy rain process of Kunming 5.24 and Beijing 7.21 shows that the precipitation of GPS increases rapidly. The high value and the large deviation from the average value indicate that the water vapor in the atmosphere is rising sharply, which provides abundant water vapor conditions for rainfall and satisfies one of the conditions of rainfall. Therefore, it has a good indicative significance for the forecast of heavy precipitation weather.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P228.4;P426.6

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相關(guān)期刊論文 前1條

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本文編號(hào)：1998782