降水和温度MOS预报方法探讨

文中分析了庆阳地区春季降水气候特征和环流形势 ,用 1995～ 1998年 3～ 5月T10 6资料建立了该区 8县 (市 )春季降水、温度MOS预报方程 ,进行了回代检验和试报 ,并提出了模式更换后的处理方法     

藏北高原陆面过程的模拟试验

利用NCAR陆面过程模式(Land Surface Model)和1998年"青藏高原能量与水分观测实验"加强观测期(GAME/Tibet IOP)的观测资料对青藏高原地区陆面过程进行了模拟研究.结果表明,在观测资料的强迫下模式能够较好地模拟出地表特征量的变化趋势,深层的土壤温度的模拟对初始场在0℃左右的变化敏感.模拟的感热通量、潜热通量以及地表反射的太阳辐射较观测值偏大.在高原地区地表类型分布状况的真实描述及植被、土壤参数的选取可能是提高该地区效果的首要问题;草地下垫面的陆面特征有待进一步研究;对土壤水热运动的真实描述,及冻土过程的加入对大气环流模式(GCM)跨季节的数值模拟会有所改进.     

北京地区春末-秋初气溶胶理化特性的观测研究

分析了1997年5～9月和1998年4～9月北京整层大气气溶胶光学厚度、近地面气溶胶粒子数浓度的日变化、季节变化及其与气象要素的关系,还分析了 1997年5月16日、7月21日和8月2日收集的北京单个气溶胶粒子样品的形态、大小和化学元素组成.结果显示,北京地区春末-秋初整层大气气溶胶光学厚度在0.1～1.6之间变化;气溶胶数浓度(D>0.3μm)为几～几百个/cm3;整层大气气溶胶光学厚度的日变化型式与近地面气溶胶数浓度呈现相反的走向;气溶胶光学厚度和数浓度的日、季节变化显示了整层大气和近地面大气气溶胶与该地区气象、气候条件的关系.气溶胶数浓度与大气相对湿度呈正相关,与风向的关系是偏东风数浓度大,西、西南风数浓度小.电子显微镜分析的结果表明:颗粒物的形态以不规则形、丸形、液态滴形和方形为主;颗粒物化学元素组成有Si、K、S、Al、Mg、Ca、Fe等元素;人类活动排放的Zn、P、Ti、pb、Ba等元素也探测到;北京近地面粒子的一个显著特点是富含Ca和K元素,它们可能分别来自建筑粉尘和有机物的燃烧;给出了一个典型的碳黑粒子和一个粒子经过凝结过程的"卫星"滴环绕的矿物粒子的照片和元素谱图.     

高密度电法测量系统作常规联合剖面的研究

研究了运用高密度电法观测系统作常规电法联合剖面的野外工作方法及数据整理过程，运用高密度电法观测系统，将高密度电法测量与常规联合剖面测量同时进行，有利于对异常体作分析解释。     

剪切带倾角尺度律与局部化启动跳跃稳定研究

研究了剪切带倾角是如何依赖于岩样高度以及剪切带的不稳定性。建立了准脆性材料试件剪切带倾角尺度效应模型,得到了剪切带倾角尺度效应的解析解,且与实验结果比较相符。研究结果表明:剪切带倾角随着试件高度的增加而增加,但其增加幅逐渐减缓,最终趋于稳定值。笔者还对剪应变局部化启动、跳跃和稳定进行了理论分析,解释了实验所观测到的剪切带跳跃现象和砂岩岩样应变局部化较煤样滞后的原因。剪应变局部化是否发生跳跃,关键取决于全程应力-应变曲线软化段是否存在拐点。对于没有拐点的情形,宏观剪切带图案不跳跃。局部化是导致准脆性材料试件剪切带倾角尺度效应的原因。     

Use of high spectral resolution remote sensing to determine leaf palatability of eucalypt trees for folivorous marsupials

In this study we assess the feasibility of remotely measuring canopy biochemistry, and thus the potential for conducting large-scale mapping of habitat quality. A number of studies have found nutrient composition of eucalypt foliage to be a major determinant of the distribution of folivorous marsupials. More recently it has been demonstrated that a specific group of secondary plant chemicals, the diformylphloroglucinols (DFPs), are the most important feeding deterrents, and are thus vital determinants of habitat quality. We report on the use of laboratory spectroscopy to attempt to identify one such DFP, sideroxylonal-A, in the foliage of Eucalyptus melliodora, one of the few eucalypt species browsed by folivorous marsupials. Reflectance spectra were obtained for freeze-dried, ground leaves using near infrared spectroscopy (NIRS) and for both oven-dried and fresh whole leaves using a laboratory-based (FieldSpec) spectroradiometer. Modified partial least squares (MPLS) regression was used to develop calibration equations for sideroxylonal-A concentration based on the reflectance spectra transformed as both the first and second difference of absorbance (Log 1/R). The predictive ability of the calibration equations was assessed using the standard error of calibration statistic (SECV). Coefficients of determination (r²) were highest for the ground leaf spectra (0.98), followed by the fresh leaf and dry leaf spectra (0.94 and 0.87, respectively). When applied to independent validation sub-sets, sideroxylonal-A was most accurately predicted from the ground leaf spectra (r² = 0.94), followed by the dry leaf and fresh leaf spectra (0.72 and 0.53, respectively). Two spectral regions, centred on 674 nm and 1394 nm, were found to be highly correlated with sideroxylonal-A concentration for each of the three spectral data sets studied. Results from this study suggest that calibration equations derived from modified partial least squares regression may be used to predict sideroxylonal-A concentration, and hence leaf palatability, of Eucalyptus melliodora trees, thereby indicating that the remote estimation of habitat quality of eucalypt forests for marsupial folivores is feasible.     

Thematic mapping from remotely sensed data with neural networks: MLP, RBF and PNN based approaches

 Neural networks are attractive tools for the derivation of thematic maps from remotely sensed data. Most attention has focused on the multilayer perceptron (MLP) network but other network types are available and have different properties that may sometimes be more appropriate for some applications. Here a MLP, radial basis function (RBF) and probabilistic neural network (PNN) were used to classify remotely sensed data of an agricultural site. The accuracy of these classifications ranged from 86.25–91.25%. The accuracy of the PNN classification could be increased through the incorporation of prior probabilities of class membership but the accuracy of each classification could also be degraded by the presence of an untrained class. Post-classification analyses, however, could be used to identify potentially misclassified cases, including those belonging to an untrained class, to increase accuracy. The effect of the post-classification analysis on the accuracy of the classification derived from each of the three network types investigated differed and it is suggested that network type be selected carefully to meet the requirements of the application in-hand. Received: 23 March 2000 / Accepted: 9 July 2000     

Linear drift and periodic variations observed in long time series of polar motion

 Two long time series were analysed: the C01 series of the International Earth Rotation Service and the pole series obtained by re-analysis of the classical astronomical observations using the HIPPARCOS reference frame. The linear drift of the pole was determined to be 3.31 ± 0.05 milliarcseconds/year towards 76.1 ± 0.80° west longitude. For the least-squares fit the a priori correlations between simultaneous pole coordinates x _p , y _p were taken into account, and the weighting function was calculated by estimating empirical variance components. The decadal variations of the pole path were investigated by Fourier and wavelet analysis. Using sliding windows, the periods and amplitudes of the Chandler wobble and annual wobble were determined. Typical periods in the variable Chandler wobble and annual wobble parameters were obtained from wavelet analyses. Received: 21 January 2000 / Accepted: 28 August 2000     

非线性最小二乘参数平差迭代算法

在非线性最小二乘问题现有的3类主要算法－－高斯－牛顿法、阻尼最小二乘法和最小二乘的拟牛顿法的基础上，引入了综合性能更优的非线性规划的SQPM（序列二次规划法）算法，并且为进一步提高SQPM算法迭代的收敛性，对其步长策略进行了改进。改进的SQPM算法成为无需精确计算参数概略值的非线性最小二乘参数平差的实用和有效算法。     

Integer estimation in the presence of biases

 Carrier phase ambiguity resolution is the key to fast and high-precision GNSS (Global Navigation Satellite System) kinematic positioning. Critical in the application of ambiguity resolution is the quality of the computed integer ambiguities. Unsuccessful ambiguity resolution, when passed unnoticed, will too often lead to unacceptable errors in the positioning results. Very high success rates are therefore required for ambiguity resolution to be reliable. Biases which are unaccounted for will lower the success rate and thus increase the chance of unsuccessful ambiguity resolution. The performance of integer ambiguity estimation in the presence of such biases is studied. Particular attention is given to integer rounding, integer bootstrapping and integer least squares. Lower and upper bounds, as well as an exact and easy-to-compute formula for the bias-affected success rate, are presented. These results will enable the evaluation of the bias robustness of ambiguity resolution. Received: 28 September 2000 / Accepted: 29 March 2001