非均匀分层下的二阶精度垂直差分方案及其在GRAPES模式中的应用

在非均匀分层下,目前GRAPES（Global/Regional Assimilation and Prediction System）模式中使用的垂直差分方案只能达到一阶精度。本文设计了一种适用于非均匀分层的二阶精度垂直差分方案,并将它应用于改进GRAPES模式动力框架的垂直离散化过程。一维廓线理想试验结果表明:二阶精度方案可以减少差分计算误差,而这种改进的幅度相对于差分计算本身引起的误差来说仍然是比较小的。通过密度流试验对修改后的模式动力框架进行测试,结果表明二阶方案可以保持模式动力框架的准确性和稳定性。进一步利用实际资料开展批量测试,发现二阶方案可以降低模式高空要素场的预报误差,而且这种改进随着预报时间的延长变得更为明显。最后选择一次典型的华南暴雨过程进行模拟,同样发现二阶精度方案对于48小时之后的降水会有一定程度的改进。     

如何提高TSP203系统在应用中的准确性

为了减少地质灾害对隧道施工的影响,采用TSP203超前地质预报系统对隧道掌子面前方进行探测,提供超前地质预报,为后续施工提供指导。但是,在实际应用中出现了很多误报、漏报或者准确性太低的情况,这些问题往往是由于数据采集和数据处理中的不足带来的。通过规范的数据采集和合理的数据处理,可以减少这些不足的不良影响,从而提高TSP203系统在超前地质预报应用中的准确性。     

基于谱修正迭代的Bursa模型

利用Bursa模型进行空间直角坐标转换时,求解的过程中如果法方程的系数矩阵是病态,则求得的转换参数并不可靠.在谱修正迭代法的基础上,推导了基于谱修正迭代的Bursa模型公式,通过算例可知该方法可有效改善病态矩阵对坐标转换的影响,其坐标转换精度比Bursa模型高.     

基于尺度收缩方法的中国县级尺度房屋结构数据推算

以国家统计局公开发布的2005年全国1％人口抽样调查数据为基数,对全国县级尺度农村房屋结构的比例构成进行了推定。针对全国性普查数据存在的问题,开发了基于不同空间精度等级的数据收缩模型,利用中国建筑气候区划、建筑热工区划、人口和社会经济指标等因子,推定了2300多个县级空间单元的农村地区不同建筑结构的房屋比例和数量。同时...     

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Compared performances of different algorithms for estimating annual nutrient loads discharged by the eutrophic River Loire

Good estimates of pollutant fluxes are required for Earth systems sciences and water quality management. The gradual accumulation of water quality data records over the past few decades has increased the value of these data for examining long‐term trends. On many major rivers, however, infrequent sampling of most pollutants makes flux estimates and their analysis difficult. This paper explores the performance of different methods for estimating nutrient fluxes. The objective is to assess the accuracy (bias) and precision (dispersion) of annual nutrient fluxes based on monthly sampling, which is the frequency with which 80% of French water quality surveys have been carried out since 1971. The study is based on a data set of nutrient concentrations surveyed at high frequency during a 5 year pilot study (1981–85) at the Orléans station in the middle reaches of the River Loire, France. The mean specific fluxes were 641 (nitrate‐N), 96 (total‐P) and 37 kg year⁻¹ km⁻² (orthophosphate‐P). For each year, the data set was then ‘resampled’ by randomly simulating 12 sampling dates. 100 simulated monthly samplings were generated, upon which seven estimation methods were tested. The evaluations indicate that, when concentrations of specific substances in large rivers exhibit seasonal variation, a simple method based on linear interpolation between samples taken at approximately monthly intervals is advocated. With the monthly sampling interval, the precision (confidence level of 95%) of annual nutrient fluxes obtained by the appropriate methods was 13% for nitrates, 20% for total‐P, 26% for orthophosphates, and 34% for particulate‐P. The frequency of water quality surveys required to obtain an annual nutrient flux with 10% precision was around 15 days for nitrate, 10 days for orthophosphate‐P and total‐P, and about 5 days in the case of particulate‐P. Copyright © 2004 John Wiley & Sons, Ltd.     

A modified subsurface stormflow model of hillsides in forest catchment

Subsurface flow plays an important role in forest catchment hydrological processes, for which a modified model is established in this paper. Firstly, by taking soil samples from Natural Preserve Forests of Changbai Mountain, two crucial parameters for subsurface flow, the saturated hydraulic conductivity and effective porosity, were measured in the laboratory. Secondly, submodels of the two parameters varying logarithmically with soil depth were established through regressive analysis. Then a modified subsurface stormflow model (Modified model) was founded by substituting the submodels into a storage–discharge model (Sloan's model), established by Sloan in 1983. Finally, to verify the Modified model, five rainfall events on a simulated hillside were carried out. The subsurface flow processes were simulated using the Modified model, Sloan's model and Robinson's model. The comparison of simulated subsurface stormflow processes using the three models respectively with measured ones showed that the Modified model obtained better accuracy for peak flow and total amount of subsurface stormflow than the other two models. Copyright © 2005 John Wiley & Sons, Ltd.     

高精度测频方案设计

介绍了一种基于数字频率计原理 ,以AT89C5 1单片机为控制器件的新型频率测量方法。论述了基本原理和软硬件实现 ,并对其误差进行了分析。克服了通用频率计由于± 1MSB误差在高低频段测量精度不等的缺陷 ,实现了高低频率的等精度测量。由于此方法具有高精度、低成本、易改进的特点 ,因此具有一定的实用性。     

THE METHODS OF EXTRACTING WATER INFORMATION FROM SPOT IMAGE

Some techniques and methods for deriving water information from SPOT-4(XI) image were investigated and discussed in this paper.An algorithmoif decision-tree(DT) classification which includes several classifiers based on the spectral responding characteristics of water bodies and other objects,was developed and put forward to delineate water bodies.Another algorithm of decision-tree classification based on both spectral characteristics and auxiliary information of DEM and slope(DTDS) was also designed for water bodies extraction.In addition,supervised classification method of maximum-likelyhood classification(MLC),and unsupervised method of interactive self -organizing dada analysis technique(ISODATA) were used to extract waterbodies for comparison purpose.An index was designed and used to assess the accuracy of different methods abopted in the research.Results have shown that water extraction accuracy was variable with respect to the various techniques applied.It was low using ISODATA,very high using DT algorithm and much higher using both DTDS and MLC.     

Scientific CMOS Pixels

High performance CMOS pixels are introduced; and their development is discussed. 3T (3-transistor) photodiode, 5T pinned diode, 6T photogate and 6T photogate back illuminated CMOS pixels are examined in detail, and the latter three are considered as scientific pixels. The advantages and disadvantages of these options for scientific CMOS pixels are examined. Pixel characterization, which is used to gain a better understanding of CMOS pixels themselves, is also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.