Role of snow depth in spring of Tibetan Plateau in onset of South China Sea summer monsoon

The role of snow depth of Tibetan Plateau in the onset of South China Sea summer monsoon and the influence of ENSO on snow depth of Tibetan Plateau are investigated with use of data from ECMWF reanalysis and NCEP/NCAR reanalysis. The results are as follows: (1) The snow depth data from ECMWF reanalysis are tested and reliable, and can be used to study the influence of snow depth of Tibetan Plateau on the onset of South China Sea summer monsoon; (2) Anomaly of snow depth of Tibetan Plateau causes anomaly in air temperature and its contrast between the Indian Ocean and the continent resulting in easterly wind anomaly over 500 hPa and hence as well as in the atmospheric circulation in the lower layer. For the year of negative anomaly of snow depth a westerly wind anomaly with a cyclone pair takes place, while for positive anomaly of snow depth an easterly anomaly occurs with an anticyclone pair; (3) While positive anomaly of SST occurs in the eastern Pacific Ocean, positive anomaly of air pressure also takes place over the eastern Indian Ocean and the South China Sea, causing stronger meridional pressure gradient between the ocean and continent and then westerly wind anomaly. At the same time, the atmospheric pressure increases in the northern Tibetan Plateau, northerly wind gets stronger, and subtropical front strengthens. All of these are favorable for snowfall over Tibetan Plateau.

高寒草甸不同土地利用格局土壤CO_2的释放量

分析高寒草甸不同土地利用格局下土壤CO2的释放量大小表明,在植物生长季的5～9 月,土壤CO2 释放量大小排序为:金露梅灌丛草甸(1871.40g/ m2) > 矮嵩草草甸(1769.63g/ m2) > 退化金露梅灌丛草甸(1495.60g/m2) > 退化矮嵩草草甸(1191.26g/ m2) ；而在植物非生长季的10月到翌年4月,其土壤CO2 释放量大小与植物生长季略有差异, 表现出矮嵩草草甸(661.46g/ m2 ) > 金露梅灌丛草甸( 550.90g/ m2 ) > 退化矮嵩草草甸(502.50g/ m2) > 退化金露梅灌丛草甸(384.50g/ m2) 的特点;全年内表现为矮嵩草草甸(2431.09g/ m2 ) > 金露梅灌丛草甸(2422.30g/ m2) > 退化金露梅灌丛草甸(1880.10g/ m2 ) > 退化矮嵩草草甸(1694.06g/ m2 ) . 高寒草甸地区不同土地利用格局土壤CO2 释放数量的差异及季节变化,不仅与各利用格局的土壤生物活性及土壤物理化学性状有关,而且与气象条件(特别是温度) 及其土壤冬季冻结期长短关系极为密切。

HHT在电磁信号处理中的应用

In modem signal Processing，non－linear，non－Gaussian and non－stable signals are usually the analyzed and Processed objects，especially non－stable signals. The convention always to analyze and Process non－stable signals are： short time Fourier transform，Wigner－Ville distribution，wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform，so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert－Huang Transform is a new non－stable signal processing technology，proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing，any non－stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non－stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence，this algorithm makes the non－stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case，the shortcoming of using many fake harmonic waves to describe non－linear and non－stable signals in Fourier Transform can be avoided. This Paper researches in the following parts： Firstly，This paper introduce the history and development of HHT，subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert－Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.

波动方程偏移速度分析

On the subject of oil and gas exploration, migration is an efficacious technique for imagining structures underground. Wave-equation migration (WEM) dominates over other migration methods in accuracy, despite of higher computational cost. However, the advantages of WEM will emerge as the progress of computer technology. WEM is sensitive to velocity model more than others. Small velocity perturbations result in grate divergence in the image pad. Currently, Kirrchhoff method is still very popular in the exploration industry for the reason of difficult to provide precise velocity model. It is very urgent to figure out a way to migration velocity modeling. This dissertation is mainly devoted to migration velocity analysis method for WEM: 1. In this dissertation, we cataloged wave equation prestack depth migration. The concept of migration is introduced. Then, the analysis is applied to different kinds of extrapolate operator to demonstrate their accuracy and applicability. We derived the DSR and SSR migration method and apply both to 2D model. 2. The output of prestack WEM is in form of common image gathers (CIGs). Angle domain common image gathers (ADCIGs) gained by wave equation are proved to be free of artifacts. They are also the most potential candidates for migration velocity analysis. We discussed how to get ADCIGs by DSR and SSR, and obtained ADCIGs before and after imaging separately. The quality of post stack image is affected by CIGs, only the focused or flattened CIGs generate the correct image. Based on wave equation migration, image could be enhanced by special measures. In this dissertation we use both prestack depth residual migration and time shift imaging condition to improve the image quality. 3. Inaccurate velocities lead to errors of imaging depth and curvature of coherent events in CIGs. The ultimate goal of migration velocity analysis (MVA) is to focus scattered event to correct depth and flatten curving event by updating velocities. The kinematic figures are implicitly presented by focus depth aberration and kinetic figure by amplitude. The initial model of Wave-equation migration velocity analysis (WEMVA) is the output of RMO velocity analysis. For integrity of MVA, we review RMO method in this dissertation. The dissertation discusses the general ideal of RMO velocity analysis for flat and dipping events and the corresponding velocity update formula. Migration velocity analysis is a very time consuming work. Respect to computational convenience, we discus how RMO works for synthetic source record migration. In some extremely situation, RMO method fails. Especially in the areas of poorly illuminated or steep structure, it is very difficult to obtain enough angle information for RMO. WEMVA based on wave extrapolate theory, which successfully overcome the drawback of ray based methods. WEMVA inverses residual velocities with residual images. Based on migration regression, we studied the linearized scattering operator and linearized residual image. The key to WEMVA is the linearized residual image. Residual image obtained by Prestack residual migration, which based on DSR is very inefficient. In this dissertation, we proposed obtaining residual migration by time shift image condition, so that, WEMVA could be implemented by SSR. It evidently reduce the computational cost for this method.