航空重力测量数据向下延拓中空间协方差函数特性研究

本文通过对航空重力测量数据的分析,建立起具有空间相关特性的空间协方差函数模型。利用所建立的模型,将航空重力测量试验数据采用最小二乘配置的方法向下延拓到地面,与地面已知重力数据进行比较。由比较结果,分析了空间协方差函数模型对航空重力测量数据向下延拓结果的影响,并表明所建立的空间协方差函数模型,满足协方差函数特性,且在局部区域使用能够达到满意的精度要求。     

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。     

确定大地水准面的Tikhonov最小二乘配置法

LSC法（最小二乘配置法）因能融合不同种类重力观测数据确定大地水准面的特性而受到广泛关注,但由于协方差矩阵存在病态性,微小的观测误差将被协方差矩阵的小奇异值放大,导致计算的配置结果不稳定且精度偏低。本文提出Tikhonov_LSC法,即在LSC法中引入Tikhonov正则化算法,基于GCV法选择协方差矩阵的正则化参数,利用正则化参数修正协方差矩阵的小奇异值,以抑制其对观测误差的放大影响。基于Tikhonov_LSC法计算大地水准面,能有效提高其稳定性和精度。通过以EGM2008重力场模型分别计算山区、丘陵和海域重力异常作为基础数据确定相应区域大地水准面的实验,验证了该方法的有效性。     

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.     

LOLAS: an optical turbulence profiler in the atmospheric boundary layer with extreme altitude resolution

We report the development and first results of an instrument called Low Layer SCIDAR (Scintillation Detection and Ranging) (LOLAS) which is aimed at the measurement of optical-turbulence profiles in the atmospheric boundary layer with high altitude resolution. The method is based on the Generalized SCIDAR (GS) concept, but unlike the GS instruments which need a 1-m or larger telescope, LOLAS is implemented on a dedicated 40-cm telescope, making it an independent instrument. The system is designed for widely separated double-star targets, which enables the high altitude resolution. Using a 200-arcsec-separation double star, we have obtained turbulence profiles with unprecedented 12-m resolution. The system incorporates necessary novel algorithms for autoguiding, autofocus and image stabilization. The results presented here were obtained at Mauna Kea Observatory. They show LOLAS capabilities but cannot be considered as representative of the site. A forthcoming paper will be devoted to the site characterization. The instrument was built as part of the Ground Layer Turbulence Monitoring Campaign on Mauna Kea for Gemini Observatory.