本文關(guān)鍵詞：基于衛(wèi)星觀測的臨近空間大氣變分?jǐn)?shù)據(jù)同化研究　出處：《中國科學(xué)院國家空間科學(xué)中心》2017年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 臨近空間 衛(wèi)星數(shù)據(jù) 變分同化 大氣環(huán)境 統(tǒng)計(jì)特性

【摘要】：20-100km臨近空間的戰(zhàn)略價(jià)值已經(jīng)逐漸引起各國的關(guān)注和重視。對臨近空間環(huán)境的研究,可為臨近空間的開發(fā)和利用提供科學(xué)依據(jù)和保障,成為當(dāng)前的熱點(diǎn)問題。衛(wèi)星探測數(shù)據(jù)分析及其在數(shù)據(jù)同化中的應(yīng)用,可幫助我們對大氣的特征和規(guī)律進(jìn)行深入了解,同時(shí)還可提高數(shù)值模式預(yù)報(bào)精度。近年來已有許多覆蓋全球的衛(wèi)星探測資料,但利用這些資料開展臨近空間大氣數(shù)據(jù)同化,以進(jìn)一步了解其運(yùn)動特征和變化趨勢、促進(jìn)臨近空間數(shù)值預(yù)報(bào)技術(shù)發(fā)展的工作還很不充分�；诖�,本文利用衛(wèi)星遙感探測資料進(jìn)行臨近空間大氣環(huán)境特征的研究,同時(shí)基于衛(wèi)星探測數(shù)據(jù)進(jìn)行臨近空間數(shù)據(jù)同化的研究,為臨近空間大氣數(shù)值模式提供更為精確的初值場。主要研究內(nèi)容如下:(1)GPS信號的相位延遲中包含了低層大氣和臨近空間大氣信息。利用地基GPS相位延遲數(shù)據(jù),提出一種結(jié)合經(jīng)驗(yàn)?zāi)Ｊ降囊痪S變分同化獲取大氣折射率的方法,利用GPS相位延遲模擬數(shù)據(jù)進(jìn)行了同化實(shí)驗(yàn),討論了背景誤差的設(shè)置對同化結(jié)果的影響,并用實(shí)測個(gè)例對該方法進(jìn)行了驗(yàn)證,獲得了高精度的0-60km大氣折射率。結(jié)果表明,該一維變分同化方法可行。首次將同化獲取的大氣折射率應(yīng)用于無線電波折射修正實(shí)驗(yàn),取得了很好的修正效果,修正精度可達(dá)1mm量級。(2)以TIMED\SABER(V1.07)的紅外溫度探測數(shù)據(jù)為觀測值,NSSC臨近空間大氣數(shù)據(jù)同化預(yù)報(bào)實(shí)驗(yàn)系統(tǒng)的預(yù)報(bào)場為溫度背景值,采用三維變分同化方法,獲取了2013年10月1日00:00的20-100km臨近空間全球大氣溫度場。利用統(tǒng)計(jì)學(xué)方法對同化結(jié)果進(jìn)行評估,結(jié)果顯示,三維變分同化后臨近空間全球溫度場誤差整體減小,三維變分同化前的溫度背景場誤差最大可達(dá)17K,三維變分同化后的溫度分析場最大誤差減小至7K以內(nèi),效果明顯。此算法可用于為臨近空間大氣環(huán)境預(yù)報(bào)模式提供更精確的初值場。(3)基于AURA\MLS衛(wèi)星溫度觀測數(shù)據(jù)和NSSC臨近空間大氣數(shù)據(jù)同化預(yù)報(bào)實(shí)驗(yàn)系統(tǒng),開展了三維變分連續(xù)同化試驗(yàn),獲取了20-100km臨近空間全球大氣溫度場。利用統(tǒng)計(jì)學(xué)方法對同化結(jié)果進(jìn)行評估,結(jié)果顯示,三維變分同化后,20-100km臨近空間全球溫度場的誤差整體減小,80km以下最大誤差由同化前的10K減小至同化后的4K以內(nèi),80km以上最大誤差由同化前的22K減小至同化后的7K以內(nèi),同化效果明顯。與單次三維變分同化相比,三維變分連續(xù)同化在保證了同化效果的同時(shí),可增加觀測數(shù)據(jù)作用范圍。(4)利用AURA\MLS數(shù)據(jù)(V4.2)和TIMED\SABERSABER數(shù)據(jù)(V2.0)對20-92km的大氣溫度進(jìn)行統(tǒng)計(jì)比較分析,計(jì)算AURA\MLS減去TIMED\SABER的溫度絕對偏差,并對平均溫度偏差在不同季節(jié)中隨經(jīng)度、緯度和高度的變化特征進(jìn)行討論,為衛(wèi)星數(shù)據(jù)的應(yīng)用提供參考依據(jù)。結(jié)果表明:20-80km的平均溫度偏差在6K以內(nèi),相對偏差在3%以內(nèi),80-90km平均溫度偏差為-10k,相對偏差在9%以內(nèi)。中低緯度地區(qū)平均溫度偏差廓線的變化趨勢較為一致,從20km的-3k左右的負(fù)偏差逐漸增加,在45-50km的平流層頂處有較為明顯的3k左右的正偏差峰值。平均溫度偏差隨緯度的變化明顯,隨經(jīng)度的變化很小。(5)基于AURA\MLS數(shù)據(jù)(V4.2)和TIMED\SABERSABER數(shù)據(jù)(V2.0)偏差的統(tǒng)計(jì)分析結(jié)果,提出了消除AURA\MLS和TIMED\SABER兩種衛(wèi)星數(shù)據(jù)的系統(tǒng)誤差偏差的方法。將消除了系統(tǒng)誤差的兩種衛(wèi)星溫度探測數(shù)據(jù)作為觀測值,以NSSC臨近空間大氣數(shù)據(jù)同化預(yù)報(bào)實(shí)驗(yàn)系統(tǒng)的溫度預(yù)報(bào)場為溫度背景場,進(jìn)行基于AURA\MLS和TIMED\SABER聯(lián)合溫度觀測數(shù)據(jù)的三維變分同化,獲取了20-100km臨近空間全球大氣溫度場。對比三維變分同化前后的臨近空間全球溫度場分布,變化較為明顯,經(jīng)驗(yàn)證算法可行。利用統(tǒng)計(jì)學(xué)方法進(jìn)行同化評估,結(jié)果表明,三維變分同化后,20-100km臨近空間全球溫度場的誤差整體減小,最大誤差由三維變分同化前的10K減小至三維變分同化后的4K以內(nèi),同化后的溫度分析場相對于溫度背景場更接近真值,同化效果明顯。該方法彌補(bǔ)了單顆衛(wèi)星的探測數(shù)據(jù)難以覆蓋全球的不足。(6)基于AURA\MLS(V4.2)從2004年8月到2016年12月共12年(149個(gè)月份)的溫度、位勢高度、壓強(qiáng)等數(shù)據(jù),計(jì)算分析了臨近空間大氣溫度、大氣密度及大氣溫度標(biāo)準(zhǔn)偏差的變化規(guī)律,并著重對大氣溫度標(biāo)準(zhǔn)偏差變化規(guī)律的原因進(jìn)行了研究。結(jié)果表明,在30km平流層,冬半球的中高緯度地區(qū)大氣擾動顯著增大,是行星波和重力波作用的結(jié)果。在1月份和7月份,大氣擾動在低緯度地區(qū)大于夏半球的中高緯度地區(qū),是重力波和行星波作用的結(jié)果。重力波作用對赤道地區(qū)大氣擾動的貢獻(xiàn),在4月份和11月份也有所體現(xiàn)。在70km的中間層,冬半球中高緯度地區(qū)的大氣擾動依然顯著,是行星波和重力波的貢獻(xiàn)所致。中低緯度地區(qū)的大氣擾動相對于平流層有所增加,是重力波活動增強(qiáng)以及大氣潮汐開始出現(xiàn)的結(jié)果。在92km的低熱層,赤道低緯度地區(qū)的大氣擾動偏大,是非遷移性周日潮汐(DE3)貢獻(xiàn)的結(jié)果。夏半球的中高緯度的地區(qū)大氣擾動較強(qiáng)是重力波的貢獻(xiàn)所致。
[Abstract]:The 20-100km strategic value of near space has gradually aroused the concern and attention. The research of near space environment, for the development of near space and provide scientific basis for the utilization and protection, has become a hot issue at present. The satellite data analysis and its application in data assimilation, can help us on the characteristics and laws of the atmosphere understand, also can improve the prediction accuracy of numerical model. In recent years there have been many global coverage of satellite data, but the use of these information to carry out the near space atmospheric data assimilation, in order to further understand its movement characteristics and trends, and promote the development of near space forecasting technology are still not fully. Based on this, this paper uses satellite study of near atmospheric environment feature space remote sensing data, and based on the satellite data with the data of near space Study for near space atmospheric numerical model provides a more accurate initial field. The main contents are as follows: (1) GPS signal phase delay is included in the lower atmosphere and the near space atmospheric information. Using GPS phase delay data foundation, put forward a kind of variational assimilation method to obtain the atmospheric refractive index with a dimension of experience the model of delay, simulation data assimilation experiments using the GPS phase, the influence of background error setting on the assimilation results are discussed, and by actual case to verify this method, a high precision 0-60km atmospheric refraction rate. The results show that the one-dimensional variational assimilation method is feasible for the first time. To obtain atmospheric assimilation the refractive index is applied to radio wave refraction correction experiment, achieved good correction effect, correction precision can reach the magnitude of 1mm. (2) to TIMEDSABER (V1.07) infrared temperature detection data for measurements, approaching NSSC Space atmosphere data assimilation and forecast system for temperature field prediction experiment background value, assimilation method using three-dimensional variable, obtained by 00:00 in October 1, 2013 20-100km near the air temperature field of global space. To evaluate the assimilation results using statistical methods results show that three-dimensional variational assimilation after global temperature error near the whole space is reduced, the three-dimensional variational the temperature background before the assimilation field the maximum error is 17K, three-dimensional variational assimilation after the temperature field analysis of the maximum error is reduced to less than 7K, the effect is obvious. This algorithm can be used for the near space environment prediction model provides more accurate initial field. (3) AURAMLS satellite temperature data and NSSC near space atmospheric data assimilation and forecast the experimental system based on the three-dimensional variational continual assimilation test, the 20-100km is near the air temperature field of global space. By using statistical method The assimilation results are evaluated, results show that the three-dimensional variational assimilation, the overall error decreases 20-100km near space global temperature below 80km, the maximum error is reduced from 10K to the initial assimilation after less than 4K, 80km more than the maximum error by assimilation of 22K before assimilation after reduced to less than 7K, compared with assimilation effect is obvious. With a single three-dimensional variational assimilation, three-dimensional variational assimilation in the continuous assimilation effect at the same time, can increase the scope of data. (4) using AURAMLS data (V4.2) and TIMEDSABERSABER data (V2.0) of 20-92km high temperature were compared and analyzed, the absolute temperature deviation calculation AURAMLS minus TIMEDSABER, and the average deviation of temperature in different seasons with the longitude, latitude and altitude variation characteristics are discussed, and provide the reference for the application of satellite data. The results show that the 20-80km average temperature deviation in 6K Inside, the relative deviation was less than 3% 80-90km, the average temperature deviation is -10k, the relative deviation is less than 9%. The change trend of low and middle latitude area average temperature deviation profile is more uniform, increase gradually from negative deviation of 20km about -3k, a positive deviation peak obviously about 3K 45-50km in the stratosphere at the top of average. The temperature deviation with latitude changes significantly, with the longitude changes is very small. (5) based on the data of AURAMLS (V4.2) and TIMEDSABERSABER data (V2.0) deviation of the results of statistical analysis, and puts forward the method of eliminating system error deviation of AURAMLS and TIMEDSABER two satellite data. The system will eliminate the error of the two satellite temperature detection the data as the observed value, with NSSC near space atmospheric data assimilation and forecast experiments the temperature of the system temperature forecast field as background field, 3D AURAMLS and TIMEDSABER temperature observation data based on the same 20-100km, get close to the atmospheric temperature. The global spatial contrast three-dimensional variational assimilation of near space before and after the distribution of global temperature, the more obvious changes, and proved the algorithm is feasible. The assimilation evaluation, using statistical methods. The results show that the three-dimensional variational assimilation, the overall error decreases 20-100km in near space, global temperature, maximum error by 3DVAR before 10K is reduced to three dimensional variational assimilation after less than 4K, the temperature field analysis of assimilation temperature relative to the background field closer to the true value, the assimilation effect is obvious. This method overcomes the shortcoming of detection data of single satellite to cover the world. (6) based on AURAMLS (V4.2) from August 2004 to December 2016 a total of 12 years (149 months) of the geopotential height, temperature, pressure and other data, analysis of the near space atmospheric temperature calculation, atmospheric density and atmospheric temperature scale changes and deviations. Focuses on the variation of air temperature standard deviation reasons were studied. The results showed that 30km in the stratosphere, the winter hemisphere high latitudes in atmospheric disturbance is significantly increased, planetary wave and gravity wave effect. In January and July, the atmospheric disturbance at lower latitudes than in the summer hemisphere high latitudes, is gravity wave and planetary wave effect. The effect of gravity waves on the equatorial atmospheric disturbance contribution, also reflected in the April and November. In the middle layer of 70km, high latitude winter hemisphere in atmospheric turbulence is still significant, planetary and gravity waves. The contribution caused by the low latitude regions relative to atmospheric disturbances the increase is the gravity wave activity enhancement and atmospheric tides began to appear in the results. At low 92KM, the low latitude atmospheric disturbance is relatively large, non migrating tides (DE3 Sunday The result of the contribution is that the atmospheric disturbance in the middle and high latitudes of the summer hemisphere is the result of the contribution of the gravity wave.

【學(xué)位授予單位】：中國科學(xué)院國家空間科學(xué)中心
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：P412.27

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