本文選題：葉面積指數(shù)　切入點(diǎn)：陸面模型　出處：《南京大學(xué)》2016年博士論文

【摘要】：作為表征地表植被特性的一個(gè)重要參數(shù),葉面積指數(shù)(LAI),是影響地表輻射傳輸、物質(zhì)能量平衡的重要植被生物物理學(xué)參數(shù),同時(shí)也是連接植被光合作用、呼吸作用等微觀生物地球化學(xué)過程的重要參數(shù)。由于陸地下表面強(qiáng)烈的不均勻性,正確描述地表植被的冠層結(jié)構(gòu),以及物理、生物地球化學(xué)過程,是正確描述地表輻射特征、以及陸-氣相互作用的基礎(chǔ)和前提。直接觀測是目前認(rèn)為可以獲得LAI最精確的方法,但是短期內(nèi)還無法實(shí)現(xiàn)LAI在區(qū)域乃至全球范圍內(nèi)的統(tǒng)一臺(tái)站觀測;隨著生物地球化學(xué)模塊的應(yīng)用和發(fā)展,越來越多的陸面模式能模擬出LAI等植被參數(shù)的動(dòng)態(tài)演變,但模擬結(jié)果嚴(yán)重依賴于陸面過程模式的模塊和參數(shù)化過程,以及模擬的初始條件等因素。陸面數(shù)據(jù)同化,利用濾波/變分方法將模型和觀測融合在一起,同時(shí)結(jié)合陸面過程的動(dòng)力框架進(jìn)行約束,達(dá)到對(duì)目的狀態(tài)量的最優(yōu)估計(jì),并實(shí)現(xiàn)資料的時(shí)空尺度擴(kuò)展。現(xiàn)存的很多衛(wèi)星遙感數(shù)據(jù)都可以提供時(shí)空連續(xù)的區(qū)域/全球分布的LAI,并且經(jīng)過了嚴(yán)格的質(zhì)量評(píng)估和校驗(yàn),這為數(shù)據(jù)同化改善陸面模型中生物地球化學(xué)模塊的模擬能力提供了數(shù)據(jù)基礎(chǔ)。本文擬利用美國大氣研究中心(NCAR)開發(fā)的公用陸面模式(CLM4)和數(shù)據(jù)同化研究平臺(tái)(DART),將衛(wèi)星遙感觀測的全球LAI數(shù)據(jù)(GLASS LAI)同化到CLM4的碳-氮循環(huán)模塊(CLM4-CN)中,并在同化的基礎(chǔ)上進(jìn)一步分析LAI的改變在全球尺度和區(qū)域尺度上對(duì)地表能量、水分平衡、植被-大氣相互作用以及氣候變化產(chǎn)生的影響。鑒于模型的初始條件分布為集合同化提供了初始誤差,其發(fā)散程度對(duì)同化的進(jìn)行和同化結(jié)果都會(huì)產(chǎn)生很大的影響,本論文首先對(duì)模型進(jìn)行了單個(gè)大氣數(shù)據(jù)和集合大氣數(shù)據(jù)分別驅(qū)動(dòng)CLM4-CN的模型初始化過程,以獲得相應(yīng)的初始條件集合。結(jié)果表明,在熱帶低緯度的森林覆蓋地區(qū)、及草地、農(nóng)田下墊面,集合模式足夠發(fā)散,而在北方常綠針葉林和溫帶落葉闊葉灌木下墊面,集合模式的離散度則相對(duì)偏�。毫硗�,模式模擬LAI的發(fā)散程度在植被的生長季明顯優(yōu)于非生長季。LAI值波動(dòng)范圍越大的季節(jié)或地區(qū),初始條件集合的發(fā)散程度越高,越有利于同化過程的進(jìn)行。為了找到有效的同化方案,本文設(shè)計(jì)了三組對(duì)比實(shí)驗(yàn),分別為：①?zèng)]有進(jìn)行同化的控制實(shí)驗(yàn)(CTL實(shí)驗(yàn))、②在同化的過程中不進(jìn)行碳-氮約束的NO-CN實(shí)驗(yàn),和③在同化過程中進(jìn)行碳-氮約束的C-N實(shí)驗(yàn)。結(jié)果顯示,未進(jìn)行同化時(shí),CLM4-CN模擬的LAI系統(tǒng)性高估了全球的LAI分布,且在低緯度地區(qū)尤其明顯,最大偏差甚至超過5 m2/m2。在同化過程中沒有進(jìn)行碳-氮約束時(shí),同化效果并不明顯;而在啟動(dòng)了碳-氮循環(huán)模塊之后,同化的LAI值與觀測的偏差明顯降低,且在低緯度的偏差能夠控制在±1 m2/m2。由此可見植被動(dòng)態(tài)物理約束過程(C-N循環(huán))的加入對(duì)同化過程具有很好的約束和修正作用。作為數(shù)據(jù)同化研究平臺(tái),DART可以同時(shí)提供各種集合同化算法為研究所用,因此本文分別對(duì)集合調(diào)整卡爾曼濾波(EAKF)、集合卡爾曼濾波(EnKF)、卡爾曼濾波(KF)和粒子濾波(PF)這四種同化算法進(jìn)行了對(duì)比分析,結(jié)果表明,集合同化(EAKF、EnKF)的結(jié)果優(yōu)于單個(gè)變量數(shù)目的同化算法(KF);另外,由于模型模擬的LAI系統(tǒng)偏高于觀測,PF法在迭代的過程中逐步減小了LAI觀測的權(quán)重,也就是降低了觀測值對(duì)同化過程中后驗(yàn)概率的計(jì)算貢獻(xiàn)。由于EAKF在每一步都對(duì)增益矩陣的更新進(jìn)行了調(diào)整,使其在不低估分析誤差協(xié)方差的前提下對(duì)觀測場產(chǎn)生盡量小的擾動(dòng),所以,確定在用EAKF方法同化的過程中,同時(shí)考慮C-N模塊的約束,才是最優(yōu)的同化方案。在挑選出最優(yōu)同化方案方法的基礎(chǔ)上,本文對(duì)模型輸出LAI的能力進(jìn)行了評(píng)估,結(jié)果得到：同化不僅能夠很好地模擬出LAI的空間分布,也能夠改進(jìn)不同緯度區(qū)域平均LAI的年變化(23°S以南除外)。另外,同化后LAI改進(jìn)最明顯的典型植被覆蓋區(qū)羅列如下：同化后LAI顯著減小的區(qū)域分別為非洲中部、亞馬遜東部、歐亞大陸南部、中國東北、和歐洲西部,主要覆蓋下墊面為常綠/落葉闊葉林、混合森林;LAI顯著增加的區(qū)域分別為歐亞中部、北美西部、和澳大利亞西部地區(qū),主要覆蓋下墊面是開放式灌木叢和草地。在挑選出最優(yōu)同化方案的基礎(chǔ)上,本文首先利用單向耦合的方法分析了2002年北半球夏季LAI對(duì)地表狀態(tài)量、陸-氣相互交換通量的影響。結(jié)果得到,在亞馬遜中部、北美北部地區(qū)、非洲北部及中部、以及歐亞大陸大部分地區(qū),模型均低估了地表2m溫度;而在北美中部及南部,歐亞大陸東部及東南部地區(qū),以及澳大利亞大部分地區(qū),模型則嚴(yán)重高估地表2m溫度。就改進(jìn)效果而言,在北美西部地區(qū)、亞馬遜大部分區(qū)域、非洲中部地區(qū)、歐亞大陸的中東部及南部,改進(jìn)后的LAI使得這種低估的形式有所緩解;而對(duì)于非洲南部,亞馬遜中部地區(qū)、以及歐亞大陸的中西部地區(qū),改進(jìn)后的LAI緩解了高估地表溫度的情況。總體而言,同化后的LAI對(duì)低估地表氣溫的改進(jìn)效果明顯好于對(duì)高估地表氣溫的改進(jìn)效果,這大概與葉面積指數(shù)的全球效應(yīng)有關(guān)。具體而言,LAI在全球范圍內(nèi)的減小,會(huì)導(dǎo)致地表2m氣溫增高,且在歐亞大陸西部地區(qū)達(dá)到最高(1.6℃),其次是亞馬遜東部和非洲中部,偏差分別為1.1℃和1.0℃;區(qū)域LAI的升高會(huì)造成當(dāng)?shù)?m氣溫的降低,其中影響最大的地區(qū)為美國西部,偏差達(dá)-0.5℃。除了亞馬遜東部地區(qū),LAI減小的區(qū)域,表層土壤濕度增大,反之亦成立;這可能是由于亞馬遜東部地區(qū)的土壤濕度受地表徑流等因素的影響更大。值得說明的是,在低緯等LAI改變最大的區(qū)域,并不是地表狀態(tài)量和陸-氣通量改變最明顯的區(qū)域,這主要與該區(qū)域的植被覆蓋類型和氣候平均態(tài)有關(guān)。利用LAI同化結(jié)果,本文還分別對(duì)比分析了在陸-氣耦合、海-氣-陸-冰耦合情況下LAI改變對(duì)地表狀態(tài)量、物質(zhì)能量平衡、以及氣象條件的影響,以分析植被變化對(duì)天氣和氣候過程的反饋效應(yīng)。結(jié)果表明,在耦合了大氣和陸面模式的情況下,同化后的LAI不僅改善了模型對(duì)低緯度2m氣溫的模擬能力,還能改善對(duì)高緯度2m氣溫的模擬能力,模擬偏差從-5℃-4℃減小到-3℃-2℃。耦合了大氣的陸面模型同時(shí)能夠改善在非洲中部、東南亞群島、亞馬遜北部、阿拉伯半島和澳大利亞西部地區(qū)對(duì)降水的模擬能力。另外,加入了海-冰耦合的模型,在熱帶地區(qū)LAI改變的地表溫度、降水等特征量變化的影響有所削減,卻加強(qiáng)了中高緯度地區(qū)LAI改變對(duì)區(qū)域氣候的影響。由于本文積分時(shí)間較短,對(duì)海氣耦合以及海氣陸冰耦合結(jié)論的分析還有待深入;另外,對(duì)LAI導(dǎo)致的氣候變化的機(jī)理解釋還有待進(jìn)一步驗(yàn)證。
[Abstract]:As an important parameter for characterizing the surface vegetation characteristics, leaf area index (LAI), is the effect of surface radiative transfer, important vegetation biophysical parameters material and energy balance, but also the connection of vegetation photosynthesis, respiration and other important parameters of micro biogeochemical processes. Due to the nonuniformity of land surface strong, correct description of the canopy the structure, surface vegetation and physical and biogeochemical processes, is the correct description of surface radiation characteristics, and land atmosphere interaction is the basis and premise. Direct observation is that LAI method can get the most accurate, but the short term can not achieve LAI in regional and global unification Observatory; with the application and the development of biogeochemical module, land surface model and more can simulate the dynamic evolution of LAI vegetation parameters, but the simulation results rely heavily on Module and parameterization in the land surface model, and the simulation of the initial conditions and other factors. Land data assimilation, using filter / variational method to model and observation together, combined with the dynamic framework of the land surface process constraints, achieve optimal estimation of objective state quantity, and realize the spatial and temporal scales data expansion. Many existing satellite remote sensing data can provide continuous spatio-temporal regional / global distribution of LAI, and after a strict quality assessment and verification, which provide the data basis for data assimilation to improve the simulation ability of biogeochemical module land surface model. This paper intends to use the National Center for Atmospheric Research (NCAR) the development of public land surface model (CLM4) and data assimilation research platform (DART), the satellite observations of global LAI (GLASS LAI) data assimilation to carbon nitrogen cycle CLM4 module (CLM4-CN), and in the same On the basis of further analysis of the change of LAI in the global and regional scale on surface energy, water balance, influence vegetation atmosphere interaction and climate change. In view of the distribution of the initial conditions of the model provides the initial error for collection and assimilation, assimilation results on the assimilation of the divergence degree will have a great effect of model initialization process firstly carried out on the model of single atmospheric data and atmospheric data set respectively to drive CLM4-CN, to obtain the corresponding set of initial conditions. The results show that the coverage area in the low latitude tropical forest and grassland, farmland surface, collection mode enough divergence, while in the north temperate evergreen needle Ye Linhe deciduous shrub surface, discrete degree set model is relatively small. In addition, the degree of divergence in the LAI model to simulate the growth of vegetation in non Ji Mingxianyou Long season.LAI value fluctuation range more seasons or regions, the higher the level of divergence of the initial conditions set, more conducive to the assimilation process. In order to find the effective assimilation scheme, this paper designs three groups of experiments, respectively: no control experiment of assimilation (CTL experiment), NO-CN experiment II for carbon and nitrogen assimilation in the constraints in the process of C-N experiment of carbon nitrogen and the constraints in the assimilation process. The results showed that, without assimilation, CLM4-CN simulation system of LAI overestimates LAI global distribution, and is especially evident in the low latitude region, the maximum deviation even more than 5 m2/m2. carbon - nitrogen constraint in the process of assimilation, assimilation effect is not obvious; and after the start of the cycle of carbon and nitrogen assimilation module, the LAI value and the observed deviation is significantly reduced, and the deviation in the low latitude can be controlled within 1 m2/m2. in vegetation The dynamic process of physical constraints (C-N cycle) with good correction effect on the constraint and assimilation process. As the data assimilation research platform, DART can also provide a variety of ensemble algorithm used for research, so this paper set adjustment (EAKF), a collection of Calman filter Calman filter (EnKF), Calman filter (KF) and particle filter (PF) of the four assimilation algorithms are compared, the results show that the set of contracts (EAKF, EnKF) assimilation algorithm results is better than that of single variable number (KF); in addition, because the model simulation of LAI system is higher than observation, PF in the iterative process of gradually reduced the weight of LAI observations, is reduced in the process of assimilation of observations to calculate the posterior probability contribution. Because EAKF has been adjusted in every step of the gain matrix is updated, so that it does not underestimate the premise of the analysis of the error covariance The observation field as far as possible small disturbance, so determined by EAKF method in the process of assimilation, taking into account the C-N module constraints, is optimal. In the selection of assimilation scheme based on the method of optimal assimilation scheme, the ability of the model output of LAI was evaluated, the results can not only obtain: assimilation good simulation of the spatial distribution of LAI, also can change in different latitude areas improved average LAI (23 degrees south of S except). In addition, LAI after assimilating the most obvious improvement of the typical vegetation coverage area are as follows: the eastern region decreased significantly after LAI assimilation were central Africa, south of the Amazon, the Eurasian Chinese northeast, and Western Europe, mainly covering the surface for the evergreen / deciduous broad-leaved forest, mixed forest; LAI increased significantly in the region were central Eurasia in western North America, Australia, and the western region, covering the main surface is open Put the bushes and grass. In the selected optimal assimilation scheme based on the one-way coupling method of 2002 in the northern hemisphere summer LAI on surface state, land surface fluxes. Results show that in the Amazon region of northern North America, central, northern and Central Africa, and most of the Eurasia area model underestimates the surface temperature of 2m; while in the north central and southern, Eastern and southeastern regions of Eurasia, and Australia in most areas, the model overestimated 2m temperature. The improved surface effect, in the areas of western North America, most of the Amazon region, Central Africa, the Middle East and south part of Eurasia part, the improved LAI makes this underestimation form eased; and for South Africa, the central region of Eurasia, Amazon, and the central and western regions, the improved LAI mitigation The surface temperature of the overestimation. In general, the improvement effect after assimilation of LAI to underestimate the surface temperature is significantly better than the improvement effect on the overestimation of surface temperature and this is probably related with leaf area index of the global effect. Specifically, the decrease of LAI in the global scope, will lead to surface 2m temperature increased, and in the area the Western Eurasian continent reached the highest (1.6 DEG C), followed by Amazon in eastern and Central Africa, deviations were 1.1 degrees and 1 degrees; the increase of LAI area will decrease the local temperature 2m, one of the most influential area for the western United States, deviation of -0.5 degrees. In addition to the Eastern Amazon, LAI reduced surface area the soil moisture increases, and vice versa; this may be due to the soil moisture of the Eastern Amazon is affected by surface runoff factors. It is worth, the biggest change in the low latitude region such as LAI, and not The surface state and land air fluxes change the most obvious area, this mainly in the region and the type of vegetation cover and climate mean state. Using LAI assimilation results, this paper analyzed the land atmosphere coupling, air sea land ice under the condition of coupling LAI change of surface state, material the energy balance, and the influence of meteorological conditions, to analyze the feedback effects of vegetation change on weather and climate processes. The results show that, in the coupling of the atmosphere and land surface model under the condition of assimilation after LAI can improve not only the ability to simulate the low latitude 2m temperature model, also can improve the simulation ability of high latitude temperature 2m the simulation error is reduced from -5 to -3 DEG -4 DEG -2 DEG C. Coupled with land surface model and can improve the atmosphere in Central Africa, Southeast Asian islands, north of the Amazon, the simulation of precipitation in Arabia Peninsula and Western Australia. The other , joined the sea ice coupling model, the surface temperature change of LAI in the tropics, changes in precipitation characteristic quantity has reduced, but increased in the high latitudes of LAI influence on regional climate. The integral time is short, and the analysis of the coupled air sea ice coupling and conclusion further; in addition, explain the mechanism of climate change caused by LAI remains to be further verified.

【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：Q948
，

本文編號(hào)：1713026