136 resultados para empirical correlation


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Second order nonlinear optical (NLO) properties of single crystals with complex structures are studied, from the chemical bond viewpoint. Contributions of each type of constituent chemical bond to the total linearity and nonlinearity are calculated from the actual crystal structure, using the chemical bond theory of complex crystals and the modified bond charge model. We have quantitatively proposed certain relationships between the crystal structure and its NLO properties. Several relations have been established from the calculation. Our method makes it possible for us to identify, predict and modify new NLO materials according to our needs. (C) 1999 Elsevier Science B.V. All rights reserved.

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An organo-soluble polyimide was successfully synthesized by two step polycondensation accompanied with chemical imidization. Optical anisotropy of thin films was detected by a prism-coupler technique. The results showed that the optical anisotropic properties of thin films prepared from solutions in different solvents depend on the solution properties. It is concluded that the more expanded the chain conformation in solution, the larger the negative birefringence of thin films. (C) 1997 Elsevier Science Ltd.

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This approach is undertaken to examine the correlation ability of the general a(N)-index (GAI) to predict chromatographic behavior. The test is performed on various types of organophosphorus compounds. The results demonstrate that the GAI possesses a good correlation with chromatographic properties.

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The relationship between the alpha-N index and physical properties of neutral phosphorus extractants is studied. Using the general alpha-N index which could describe extractants with minute difference in structure, the good correlation between it and various physical properties of the neutral phosphorus extractants (e.g., densities, refractive index, shift ratio of paper chromatography and IR frequencies of bond P = O) is obtained. The result indicates that general alpha-N index is a good topological index of organic compounds.

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Diatom data of 192 surface sediment samples from the marginal seas in the western Pacific together with modern summer and winter sea surface temperature and salinity data were analyzed. The results of canonical correspondence analysis show that summer sea-surface salinity (SSS) is highly positively correlated with winter SSS and so is summer sea-surface temperature (SST) with winter SST. The correlations between SSSs and SSTs are less positively correlated, which may be due to interactions of regional current pattern and monsoon climate. The correlations between diatom species, sample sites and environmental variables concur with known diatom ecology and regional oceanographic characters. The results of forward selection of the environmental variables and associated Monte Carlo permutation tests of the statistical significance of each variable suggest that summer SSS and winter SST are the main environmental factors affecting the diatom distribution in the area and therefore preserved diatom data from down core could be used for reconstructions of summer SSS and winter SST in the region.

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Empirical Orthogonal Function (EOF) analysis is used in this study to generate main eigenvector fields of historical temperature for the China Seas (here referring to Chinese marine territories) and adjacent waters from 1930 to 2002 (510 143 profiles). A good temperature profile is reconstructed based on several subsurface in situ temperature observations and the thermocline was estimated using the model. The results show that: 1) For the study area, the former four principal components can explain 95% of the overall variance, and the vertical distribution of temperature is most stable using the in situ temperature observations near the surface. 2) The model verifications based on the observed CTD data from the East China Sea (ECS), South China Sea (SCS) and the areas around Taiwan Island show that the reconstructed profiles have high correlation with the observed ones with the confidence level > 95%, especially to describe the characteristics of the thermocline well. The average errors between the reconstructed and observed profiles in these three areas are 0.69A degrees C, 0.52A degrees C and 1.18A degrees C respectively. It also shows the model RMS error is less than or close to the climatological error. The statistical model can be used to well estimate the temperature profile vertical structure. 3) Comparing the thermocline characteristics between the reconstructed and observed profiles, the results in the ECS show that the average absolute errors are 1.5m, 1.4 m and 0.17A degrees C/m, and the average relative errors are 24.7%, 8.9% and 22.6% for the upper, lower thermocline boundaries and the gradient, respectively. Although the relative errors are obvious, the absolute error is small. In the SCS, the average absolute errors are 4.1 m, 27.7 m and 0.007A degrees C/m, and the average relative errors are 16.1%, 16.8% and 9.5% for the upper, lower thermocline boundaries and the gradient, respectively. The average relative errors are all < 20%. Although the average absolute error of the lower thermocline boundary is considerable, but contrast to the spatial scale of average depth of the lower thermocline boundary (165 m), the average relative error is small (16.8%). Therefore the model can be used to well estimate the thermocline.

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An equivalent-barotropic (EB) description of the tropospheric temperature field is derived from the geostrophic empirical mode (GEM) in the form of a scalar function Gamma(p, phi), where p is pressure and phi is 300-850-mb thickness. Baroclinic parameter phi plays the role of latitude at each longitudinal section. Compared with traditional Eulerian-mean methods, GEM defines a mean field in baroclinic streamfunction space with a time scale much longer than synoptic variability. It prompts an EB concept that is only based on a baroclinic field. Monthly GEM fields are diagnosed from NCEP-NCAR reanalysis data and account for more than 90% of the tropospheric thermal variance. The circumglobal composite of GEM fields exhibits seasonal, zonal, and hemispheric asymmetries, with larger rms errors occurring in winter and in the Northern Hemisphere (NH). Zonally asymmetric features and planetary deviation from EB are seen in the NH winter GEM. Reconstruction of synoptic sections and correlation analysis reveal that the tropospheric temperature field is EB at the leading order and has a 1-day phase lag behind barotropic variations in extratropical regions.

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A vertical 2-D water-mud numerical model is developed for estimating the rate of mud mass transport under wave action. A nonlinear semi-empirical rheology model featured by remarkable hysteresis loops in the relationships of the shear stress versus both the shear strain and the rate of shear strain of mud is applied to this water mud model. A logarithmic grid in the vertical direction is employed for numerical treatment, which increases the resolution of the flow in the neighborhood of both sides of the interface. Model verifications are given through comparisons between the calculated and the measured mud mass transport velocities as well as wave height changes. (C) 2006 Elsevier Ltd. All rights reserved.

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Sea surface salinity is a key physical parameter in ocean science. It is important in the ocean remote sensing to retrieve sea surface salinity by the microwave probe technology. Based on the in situ measurement data and remote sensing data of the Yellow Sea, we have built a new empirical model in this paper, which can be used to retrieve sea surface salinity of the Yellow Sea by means of the brightness temperature of the sea water at L-band. In this model, the influence of the roughness of the sea surface is considered, and the retrieved result is in good agreement with the in situ measurement data, where the mean absolute error of the retrieved sea surface salinity is about 0.288 psu. This result shows that our model has greater retrieval precision compared with similar models.

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本文依据收集到的392个地面验潮站8个主要分潮(M2、S2、K1、O1、N2、K2、P1及Q1)的调和常数,对现有7个全球大洋潮汐模式的准确度进行了检验,结果显示各模式在深海区域均达到了比较高的准确度,相互之间差别也不大。经验模式GOT00和CSR4.0、同化模式NAO99、反演同化模式TPXO7.0、数值同化模式FES2002和FES2004的M2分潮均方根偏差在3 cm左右,其它分潮(S2、K1、O1、N2、K2、P1及Q1)大约在1~2 cm。本文还依据中国近海18个岛屿的调和常数对其中的5个大洋潮汐模式的准确度进行了检验,结果表明,M2分潮均方根偏差在6~14 cm,明显高于大洋部分的偏差,其中日本国家天文台的潮汐模式NAO99在中国近海的结果相对较准确。 我们利用1992年8月至2008年8月的TOPEX/POSEIDON和JASON-1(T/P-J)卫星高度计资料,对沿卫星轨道的302816个站点进行了14个分潮的潮汐调和分析,得到了全球大洋潮汐的8个主要分潮以及2个气象分潮Sa、Ssa的经验同潮图。主要结果有:(1)各分潮在卫星上升轨道与下降轨道的交叉点(约7000个)相关性分析表明:M2分潮的振幅和迟角的相关系数很高(分别为0.9965和0.9961);S2,K1,O1和Sa分潮也有较好的相关性(相关系数为0.94~0.99);(2)该结果与392地面个验潮站吻合较好,其中M2分潮的振幅、迟角和向量的均方根偏差分别为:1.73 cm,2.340和2.93 cm;S2,K1和O1分潮的振幅、迟角和向量的均方根偏差为1 cm左右,5.250~7.270和1.5~2.1 cm,该精度与最近几年国际上的主要大洋潮汐模式的准确度相近;(3)首次通过卫星资料获得了Sa、Ssa分潮的同潮图。周期为1年的Sa分潮与大洋105个地面站相比,振幅、迟角和向量的均方根偏差分别为1.50 cm、18.360和2.16 cm。在此基础上,进一步分析了构成Sa、Ssa气象分潮的两个主要因素(海水密度以及海面气压)在全球的分布。 在T/P-J等卫星资料无法覆盖到南大洋和北冰洋,本文利用Princeton Ocean Model(POM)进行了数值模拟,模拟结果与162个地面实测站(其中南大洋30个,北冰洋132个)的观测比较一致。基于卫星资料分析的结果和数值模拟结果合并得到了全球大洋的8个主要分潮同潮图。在此基础上通过全球潮汐能量耗散的计算得到潮能通量的分布,并得到全球M2、S2、K1和O1分潮的潮汐能量耗散率为2.431TW、0.401TW、0.336TW和0.176TW。 本文还利用卫星资料对南海潮汐进行了研究,在中国南海,获得了主要的半日潮、全日潮、四分日分潮和长周期分潮(M2,S2,N2,K2,K1,O1,P1,Q1,M4, MS4,Sa, Ssa)的经验同潮图。与南海沿岸94个地面验潮站的数据符合得比较好,M2,S2,K1及O1等4个主要分潮的平均振幅差为2~4 cm,均方根偏差分别是9~11 cm.其它4个主要分潮N2,K2,P1,Q1的平均振幅差为1~2 cm,均方根偏差为2~4 cm。此外,本文还利用卫星高度计资料潮汐分析结果沿卫星轨道进行高通滤波,分离得出中国近海的M2,S2,K1及O1分潮的内潮信息。

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温度跃层是反映海洋温度场的重要物理特性指标,对水下通讯、潜艇活动及渔业养殖、捕捞等有重要影响。本文利用中国科学院海洋研究所“中国海洋科学数据库”在中国近海及西北太平洋(110ºE-140ºE,10ºN-40ºN)的多年历史资料(1930-2002年,510143站次),基于一种改进的温跃层判定方法,分析了该海域温跃层特征量的时空分布状况。同时利用Princeton Ocean Model(POM),对中国近海,特别是东南沿海的水文结构进行了模拟,研究了海洋水文环境对逆温跃层的影响。最后根据历史海温观测资料,利用EOF分解统计技术,提出了一种适于我国近海及毗邻海域,基于现场有限层实测海温数据,快速重构海洋水温垂直结构的统计预报方法,以达到对现场温跃层的快速估计。 历史资料分析结果表明,受太阳辐射和风应力的影响,20°N以北研究海域,温跃层季节变化明显,夏季温跃层最浅、最强,冬季相反,温跃层厚度的相位明显滞后于其他变量,其在春季最薄、秋季最厚。12月份到翌年3月份,渤、黄及东海西岸,呈无跃层结构,西北太平洋部分海域从1月到3月份,也基本无跃层结构。在黄海西和东岸以及台湾海峡附近的浅滩海域,由于风力搅拌和潮混合作用,温跃层出现概率常年较低。夏季,海水层化现象在近海陆架海域得到了加强,陆架海域温跃层强度季节性变化幅度(0.31°C/m)明显大于深水区(约0.05°C/m),而前者温跃层深度和厚度的季节性变化幅度小于后者。20°N以南研究海域,温跃层季节变化不明显。逆温跃层主要出现在冬、春季节(10月-翌年5月)。受长江冲淡水和台湾暖流的影响,东南沿海区域逆温跃层持续时间最长,出现概率最大,而在山东半岛北及东沿岸、朝鲜半岛西及北岸,逆温跃层消长过程似乎和黄海暖流有关。多温跃层结构常年出现于北赤道流及对马暖流区。在黑潮入侵黄、东、南海的区域,多温跃层呈现明显不同的季节变化。在黄海中部,春季多温跃层发生概率高于夏季和秋季,在东海西部,多跃层主要出现在夏季,在南海北部,冬季和春季多温跃层发生概率大于夏季和秋季。这些变化可能主要受海表面温度变化和风力驱动的表层流的影响。 利用Princeton Ocean Model(POM),对中国东南沿海逆温跃层结构进行了模拟,模拟结果显示,长江冲淡水的季节性变化以及夏季转向与实际结果符合较好,基本再现了渤、黄、东海海域主要的环流、温盐场以及逆温跃层的分布特征和季节变化。通过数值实验发现,若无长江、黄河淡水输入,则在整个研究海域基本无逆温跃层出现,因此陆源淡水可能是河口附近逆温跃层出现的基本因素之一。长江以及暖流(黑潮和台湾暖流)流量的增加,均可在不同程度上使逆温跃层出现概率及强度、深度和厚度增加,且暖流的影响更加明显。长江对东南沿海逆温跃层的出现,特别是秋季到冬季初期,有明显的影响,使长江口海域逆温跃层位置偏向东南。暖流对于中国东南沿海的逆温跃层结构,特别是初春时期,有较大影响,使长江口海域的逆温跃层位置向东北偏移。 通过对温跃层长期变化分析得出,黄海冷水团区域,夏季温跃层强度存在3.8年左右的年际变化及18.9年左右的年代际变化,此变化可能主要表现为对当年夏季和前冬东亚地区大气气温的热力响应。东海冷涡区域,夏季温跃层强度存在3.7年的年际变化,在El Nino年为正的强度异常,其可能主要受局地气旋式大气环流变异所影响。谱分析同时表明,该海域夏季温跃层强度还存在33.2年的年代际变化,上世纪70年代中期,温跃层强度由弱转强,而此变化可能与黑潮流量的年代际变化有关。 海洋水温垂直结构的统计预报结果显示,EOF分解的前四个主分量即能够解释原空间点温度距平总方差的95%以上,以海洋表层附近观测资料求解的特征系数推断温度垂直结构分布的结果最稳定。利用东海陆架区、南海深水区和台湾周边海域三个不同区域的实测CTD样本廓线资料,对重构模型的检验结果表明,重构与实测廓线的相关程度超过95%的置信水平。三个区重构与实测温度廓线值的平均误差分别为0.69℃,0.52℃,1.18℃,平均重构廓线误差小于平均气候偏差,统计模式可以很好的估算温度廓线垂直结构。东海陆架海区温度垂直重构廓线与CTD观测廓线获得的温跃层结果对比表明,重构温跃层上界、下界深度和强度的平均绝对误差分别为1.51m、1.36m和0.17℃/m,它们的平均相对误差分别为24.7%、8.9%和22.6%,虽然温跃层深度和强度的平均相对误差较大,但其绝对误差量值较小。而在南海海区,模型重构温跃层上界、下界和强度的平均绝对预报误差分别为4.1m、27.7m和0.007℃/m,它们的平均相对误差分别为16.1%、16.8%和9.5%,重构温跃层各特征值的平均相对误差都在20%以内。虽然南海区温跃层下界深度平均绝对预报误差较大,但相对于温跃层下界深度的空间尺度变化而言(平均温跃层下界深度为168m),平均相对误差仅为16.8%。因此说模型重构的温度廓线可以达到对我国陆架海域、深水区温跃层的较好估算。 基于对历史水文温度廓线观测资料的分析及自主温跃层统计预报模型,研制了实时可利用微机简单、快捷地进行温跃层估算及查询的可视化系统,这是迄今进行大范围海域温跃层统计与实时预报研究的较系统成果。

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In the production tail of oilfield, water-cut is very high in thick channel sand oil reservoir, but recovery efficiency is relative low, and recoverable remaining oil reserves is more abundant, so these reserves is potential target of additional development. The remaining oil generally distributed with accumulation in certain areas, controlled by the reservoir architecture that mainly is the lateral accretion shale beddings in the point bar, so the study of reservoir architecture and the remaining oil distribution patterns controlled by architecture are very significant. In this paper, taking the Minghuazhen formation of Gangxi oilfield as a case, using the method of hierarchy analysis, pattern fitting and multidimensional interaction, the architecture of the meandering river reservoir is precisely anatomized, and the remaining oil distribution patterns controlled by the different hierarchy architecture are summarized, which will help to guide the additional development of oil fields. Not only is the study significant to the remaining oil forecasting, but also it is important for the theory development of reservoir geology. With the knowledge of sequence correlation and fluvial correlation model, taking many factors into account, such as combination of well and seismic data, hierarchical controlling, sedimentary facies restraint, performance verification and 3-D closure, an accurate sequence frame of the study area was established. On the basis of high-resolution stratigraphic correlation, single layer and oil sand body are correlated within this frame, and four architecture hierarchies, composite channel, single channels, point bars and lateral accretion sandbody are identified, The result indicates that Minghuazhen Formation of Gangxi oilfield are dominated by meandering river deposition, including two types of channel sandbodies, narrow band and wide band channel sandbody, and each of them has different characteristics of facies variation laterally. Based on the identification of composite channel, according to the spatial combination patterns and identified signs of single channel, combined with channel sandbody distribution and tracer material data, single channel sandbodies are identified. According to empirical formula, point-bar scales of the study area are predicted, and three identification signs are summarized, that is, positive rhythm in depositional sequence, the maximum thick sand and near close to the abandoned channel, and point bars are identified. On the basis of point bar recognition, quantitative architecture models inner point bar are ascertained, taking the lateral accretion sand body and lateral accretion shale beddings in single well as foundation, and quantitative architecture models inner point bar as guidance, and result of tracer material data as controlling, the the lateral accretion sand body and lateral accretion shale beddings are forecasted interwell, so inner architecture of point bar is anatomied. 3-D structural model, 3-D facies model and 3-D petrophysical properties models are set up, spatial distribution characteristics of sedimentary facies and petrophysical properties is reappeared. On the basis of reservoir architecture analysis and performance production data, remaining oil distribution patterns controlled by different hierarchy architecture units, stacked channel, single channel and inner architecture of point bar, are summarized, which will help to guide the additional development of oil fields.

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Solar ultraviolet (UV) radiation at wavelengths less than 400 nm is an important source of energy for aeronomic processes throughout the solar system. Solar UV photons are absorbed in planetary atmospheres, as well as throughout the heliosphere, via photodissociation of molecules, photoionization of molecules and atoms, and photoexcitation toexcitation including resonance scattering. In this paper, the solar irradiances data measured by TIMED SEE, as well as the solar proxies such as F10.7 and Mg II, thermosphere neutral density of CHAMP measurements and topside ionospheric plasmas densities from DMSP, are used to analyze solar irradiance effects on the variabilities of the thermosphere and the ionosphere. First, thermosphere densities near 410 km altitude are analyzed for solar irradiance variability effects during the period 2002-2004. Correlations between the densities and the solar irradiances for different spectral lines and wavelength ranges reveal significantly different characteristics. The density correlates remarkably well with all the selected solar irradiances except the lower chromospheric O I (130.4 nm) emission. Among the chosen solar proxies, the Mg II core-to-wing ratio index, EUV (30-120 nm) and F10.7 show the highest correlations with the density for short-term (< ~27 days) variations. For both long- (> ~27 days) and short-term variations, linear correlation coefficients exhibit a decreasing trend from low latitudes towards high latitudes. The density variability can be effectively modeled (capturing 71% of the variance) using multiple solar irradiance indices, including F10.7, SEUV (the EUV 30-120 nm index), and SFUV (the FUV 120-193 nm index), in which a lag time of 1 day was used for both F10.7 and SEUV, and 5 days for SFUV. In our regression formulation SEUV has the largest contribution to the density variation (40%), with the F10.7 having the next largest contribution (32%) and SFUV accounting for the rest (28%). Furthermore, a pronounced period of about 27.2 days (mean period of the Sun's rotation) is present in both density and solar irradiance data of 2003 and 2004, and a pronounced period of about 54.4 days (doubled period of the solar rotation) is also revealed in 2004. However, soft X-ray and FUV irradiances did not present a pronounced 54.4 day period in 2004, in spite of their high correlation with the densities. The Ap index also shows 54-day periodicities in 2004, and magnetic activity, together with solar irradiance, affects the 54-day variation in density significantly. In addition, NRLMSISE00, DTM-2000 and JB2006 model predictions are compared with density measurements from CHAMP to assess their accuracy, and the results show that these models underestimate the response of the thermosphere to variations induced by solar rotation. Next, the equatorial topside ionospheric plasmas densities Ni are analyzed for solar irradiance variability effects during the period 2002-2005. Linear correlations between Ni and the solar irradiances for different wavelength ranges reveal significantly different characteristics. XUV (0-35 nm) and EUV (115-130 nm) show higher correlation with Ni for the long-term variations, whereas EUV (35-115 nm) show higher correlation for the short-term variations. Moreover, partial correlation analysis shows that the long-term variations of Ni are affected by both XUV (0-35 nm) and EUV (35-115 nm), whereas XUV (0-35 nm) play a more important role; the short-term variations of Ni are mostly affected by EUV (35-115 nm). Furthermore, a pronounced period of about 27 days is present in both Ni and solar irradiance data of 2003 and 2004, and a pronounced period of about 54 days is also revealed in 2004. Finally, prompted by previous studies that have suggested solar EUV radiation as a means of driving the semiannual variation, we investigate the intra-annual variation in thermosphere neutral density near 400 km during 2002-2005. The intra-annual variation, commonly referred to as the ‘semiannual variation’, is characterized by significant latitude structure, hemispheric asymmetries, and inter-annual variability. The magnitude of the maximum yearly difference, from the yearly minimum to the yearly maximum, varies by as much as 60% from year to year, and the phases of the minima and maxima also change by 20-40 days from year to year. Each annual harmonic of the intra-annual variation, namely, annual, semiannual, ter-annual and quatra-annual, exhibits a decreasing trend from 2002 through 2005 that is correlated with the decline in solar activity. In addition, some variations in these harmonics are correlated with geomagnetic activity, as represented by the daily mean value of Kp. Recent empirical models of the thermosphere are found to be deficient in capturing most of the latitude dependencies discovered in our data. In addition, the solar flux and geomagnetic activity proxies that we have employed do not capture some latitude and inter-annual variations detected in our data. It is possible that these variations are partly due to other effects, such as seasonal-latitudinal variations in turbopause altitude (and hence O/N2 composition) and ionosphere coupling processes that remain to be discovered in the context of influencing the intra-annual variations depicted here. Our results provide a new dataset to challenge and validate thermosphere-ionosphere general circulation models that seek to delineate the thermosphere intra-annual variation and to understand the various competing mechanisms that may contribute to its existence and variability. We furthermore suggest that the term “intra-annual” variation be adopted to describe the variability in thermosphere and ionosphere parameters that is well-captured through a superposition of annual, semiannual, ter-annual, and quatra-annual harmonic terms, and that “semiannual’ be used strictly in reference to a pure 6-monthly sinusoidal variation. Moreover, we propose the term “intra-seasonal” to refer to those shorter-term variations that arise as residuals from the above Fourier representation.