Excel在GPS基线解算精度统计中的应用

GPS基线解算就是利用GPS观测值,通过数据处理,得到测站间的基线向量值。基线解算是GPS网平差的基础和关键,基线解算精度直接关系着GPS网的精度,所以,基线解算精度统计是一项很有必要的工作。Excel中大量的公式函数可以应用选择,主要用来进行有繁重计算任务的预算、财务、数据处理等工作,借助于Excel的数据筛选和条件格式功能,可以方便、高效、准确无误地进行GPS精度统计,这在GPS广泛大量使用的今天,有一定的现实意义。     

网络地图服务自适应层次研究

针对当前网络地图服务现状,认为在网络地图服务中引入自适应理论与技术是提升地图服务智能水平与服务质量的一个重要途径.在分析地图可视化领域自适应相关研究基础上,立足于自适应环境和主体多元需求的阶段性改变,梳理与客体相应的自适应因素,提出了网络地图服务自适应层次模型.阐明了该模型中5个自适应层次的关键研究内容及其技术要点,进...     

干旱程度对C3植物红砂和C4植物珍珠光合生理参数的影响

 C3和C4植物混生在草地生态系统中较多,而在荒漠生态系统少见。在中国荒漠地区,C3小灌木红砂和C4半灌木珍珠在特定生境下混生在一起,以独特方式适应高温强光和干旱的极端环境。通过在不同干旱程度下测定它们生长期叶片的光合气体交换参数,探讨它们在混生条件下对极端环境的生理响应特征。结果表明,红砂的净光合速率(Pn)、蒸腾速率(E)、气孔导度(Gs)均要高于珍珠;而珍珠的水分利用效率(WUE)则要高于红砂。这表明珍珠和红砂在水分匮乏的荒漠生境下采取了不同的生存策略。红砂通过维持较高净光合速率和较高蒸腾速率来生存;而珍珠则通过高水分利用效率生存。     

渭河流域一次致洪暴雨过程的中尺度滤波分析

利用常规高空观测资料和NCEP/NCAR 1°×1°的再分析资料以及25点低通滤波技术,对2003年8月28—29日发生在渭河流域的一次致洪暴雨进行了中尺度分析和探讨,分析出中尺度环流演变特征,总结了渭河流域致洪暴雨的概念模型,认为这次暴雨过程中在以西南气流为主的平均气流场上隐藏着尺度较中尺度平均流场小得多的涡旋,其移动方向和发展程度决定了强降水落区及其强度;高空西风风速脉动与低层南风风速脉动耦合形成了中尺度次级环流圈,其上升支为强降水提供了足够的动力抬升机制;而850 hPa低空急流、700 hPa中尺度低涡、南风脉动以及高空西风风速脉动等条件的合理配置是中尺度次级环流形成的必备因素;地面中尺度辐合线是本次暴雨的触发机制。     

带有低通滤波的广义S变换在探地雷达层位识别中的应用

同其它分析时变信号的方法相比,S变换具有独特的优点.但是S变换的时窗函数形式固定,限制了其在信号分析和处理中的应用.针对这一问题,本文对S变换进行了改进和推广,在S变换的时窗函数中引入调节参数,同时将低通滤波函数融入其中,提出了一种广义S变换.通过调节参数大小来调节广义S变换的时间分辨率和频率分辨率,从而使该变换具有很强的适用性.本文使用该变换对实测探地雷达数据进行了层位识别研究,取得了较好的效果.     

A Comparison Study of the Contributions of Additional Observations in the Sensitive Regions Identified by CNOP and FSV to Reducing Forecast Error Variance for the Typhoon Morakot

The sensitive regions of conditional nonlinear optimal perturbations (CNOPs) and the first singular vector (FSV) for a northwest Pacific typhoon case are reported in this paper. A large number of probes have been designed in the above regions and the ensemble transform Kalman filter (ETKF) techniques are utilized to examine which approach can locate more appropriate regions for typhoon adaptive observations. The results show that, in general, the majority of the probes in the sensitive regions of CNOPs can reduce more forecast error variance than the probes in the sensitive regions of FSV. This implies that adaptive observations in the sensitive regions of CNOPs are more effective than in the sensitive regions of FSV. Furthermore, the reduction of the forecast error variance obtained by the best probe identified by CNOPs is twice the reduction of the forecast error variance obtained by FSV. This implies that dropping sondes, which is the best probe identified by CNOPs, can improve the forecast more than the best probe identified by FSV. These results indicate that the sensitive regions identified by CNOPs are more appropriate for adaptive observations than those identified by FSV.     

The Durham/ESO SLODAR optical turbulence profiler

An instrument for monitoring of the vertical profile of atmospheric optical turbulence strength, employing the Slope Detection and Ranging (SLODAR) double star technique applied to a small telescope, has been developed by Durham University and the European South Observatory. The system has been deployed at the Cerro Paranal observatory in Chile for statistical characterization of the site. The instrument is configured to sample the turbulence at altitudes below 1.5 km with a vertical resolution of approximately 170 m. The system also functions as a general-purpose seeing monitor, measuring the integrated optical turbulence strength for the whole atmosphere, and hence the seeing width. We give technical details of the prototype and present data to characterize its performance. Comparisons with contemporaneous measurements from a differential image motion monitor (DIMM) and a multi-aperture scintillation sensor (MASS) are discussed. Statistical results for the optical turbulence profile at the Paranal site are presented. We find that, in the median case, 49 per cent of the total optical turbulence strength is associated with the surface layer (below 100 m), 35 per cent with the 'free atmosphere' (above 1500 m) and 16 per cent with the intermediate altitudes (100–1500 m).     

Adaptive Optics Image Restoration Based on Frame Selection and Multi-frame Blind Deconvolution

Restricted by the observational condition and the hardware, adaptive optics can only make a partial correction of the optical images blurred by atmospheric turbulence. A postprocessing method based on frame selection and multi-frame blind deconvolution is proposed for the restoration of high-resolution adaptive optics images. By frame selection we mean we first make a selection of the degraded (blurred) images for participation in the iterative blind deconvolution calculation, with no need of any a priori knowledge, and with only a positivity constraint. This method has been applied to the restoration of some stellar images observed by the 61-element adaptive optics system installed on the Yunnan Observatory 1.2m telescope. The experimental results indicate that this method can effectively compensate for the residual errors of the adaptive optics system on the image, and the restored image can reach the diffraction-limited quality.     

An Adaptive Nonhydrostatic Atmospheric Dynamical Core Using a Multi-Moment Constrained Finite Volume Method

An adaptive 2 D nonhydrostatic dynamical core is proposed by using the multi-moment constrained finite-volume(MCV) scheme and the Berger-Oliger adaptive mesh refinement(AMR) algorithm. The MCV scheme takes several pointwise values within each computational cell as the predicted variables to build high-order schemes based on single-cell reconstruction. Two types of moments, such as the volume-integrated average(VIA) and point value(PV), are defined as constraint conditions to derive the updating formulations of the unknowns, and the constraint condition on VIA guarantees the rigorous conservation of the proposed model. In this study, the MCV scheme is implemented on a height-based, terrainfollowing grid with variable resolution to solve the nonhydrostatic governing equations of atmospheric dynamics. The AMR grid of Berger-Oliger consists of several groups of blocks with different resolutions, where the MCV model developed on a fixed structured mesh can be used directly. Numerical formulations are designed to implement the coarsefine interpolation and the flux correction for properly exchanging the solution information among different blocks. Widely used benchmark tests are carried out to evaluate the proposed model. The numerical experiments on uniform and AMR grids indicate that the adaptive model has promising potential for improving computational efficiency without losing accuracy.