Dependence of the AGCM Climatology on the Method of Prescribing Surface Boundary Conditions and Its Climatological Implication

By using IAP 9L AGCM, two sets of long-term climatological integration have been performed with the two different interpolation procedures for generating the daily surface boundary conditions. One interpolation procedure is the so-called “traditional” scheme, for which the daily surface boundary conditions are obtained by linearly interpolating between the observed monthly mean values, however the observed monthly means cannot be preserved after interpolation. The other one is the “new” scheme, for which the daily surface boundary conditions are obtained by linearly interpolating between the “artificial” monthly mean values which are based on, but are different from the observed ones, after interpolating with this new scheme, not only the observed monthly mean values are preserved, the time series of the new generated daily values is also more consistent with the observation. Comparison of the model results shows that the differences of the globally or zonally averaged fields between these two integrations are quite small, and this is due to the compensating effect between the different regions. However, the differences of the two patterns (the global or regional geographical distributions), are quite significant, for example, the magnitude of the difference in the JJA mean rainfall between these two integrations can exceed 2 mm/ day over Asian monsoon regions, and the difference in DJF mean surface air temperature can also exceed 2?C over this region. The fact that the model climatology depends quite strongly on the method of prescribing the daily surface boundary conditions suggests that in order to validate the climate model or to predict the short-term climate anomalies, either the “new? interpolation scheme or the high frequency surface boundary conditions (e.g., daily or weekly data instead of the monthly data) should be introduced. Meanwhile, as for the coupled model, the daily coupling scheme between the different component climate models ( e.g., atmospheric and oceanic general circulation models) is preferred in order to partly eliminate the “climate drift” problem which may appear during the course of direct coupling.

电离层内插模型的分析

常见的电离层延迟内插模型有:线性组合法LCM(Linear Combination Model)、距离相关线性内插法DIM(Distance Based Linear Interpolation Model)、线性内插法LIM(Linear Interpolation Model)和低次曲面模型法LSM(Low-order Surface Model)等。文中对4种模型的基本原理和方法进行了详细的介绍,并利用河北省CORS网的实测数据进行计算分析,从而对模型之间的内插精度进行比较。结果表明,LSM模型的内插精度无论是流动站在网内还是在网外都要稍高于其他3种模型;其他3种模型的内插精度相当。当流动站分别位于网内和网外时,LSM模型的精度变化最小;LIM变化次之;LCM变化最大。

GPS网络RTK内插算法分析与比较

在GPS网络RTK中,利用不同的内插算法,生成的流动站误差改正数不同,它们对定位结果的影响也不同。通过算例分析表明,选择合理的内插算法,不仅可以生成与流动站真实误差较为接近的误差改正数,还可以提高整周模糊度的解算成功率和导航定位的精度。

局域差分GPS改正数学模型分析与比较

局域差分中,用户到基准站的距离对定位精度有着决定性影响。利用基准站生成用户误差改正数,其算法很多,介绍了几种常用的方法,并分析了各方法的内插系数和内插质量因子。利用局域差分GPS进行定位时,只有当流动站位于基准站构成的多边形网内时,才可能得到较高的精度。

局域差分GPS的数学模型

局域差分GPS中,用户到基准站的距离对定位精度有着决定性影响。利用基准站生成用户误差改正数,其算法很多。文中针对局域差分GPS的数学模型空间相关性,介绍几种常用的内插方法,如加权平均法、线性内插法、低次曲面模型法及三角形内插法,并分析各种方法的内插系数和内插质量因子。利用局域差分GPS进行定位时,只有当用户站位于基准站构成的多边形网内时,才可能得到较高的精度。

基于不同滤波方法的机载激光雷达数据处理及表面模型构建

利用几种不同的滤波算法对黑龙江省凉水国家级自然保护区的点云数据进行处理,对比分析评价了各滤波算法在东北地区的滤波分类效果及对构建数字高程模型和数字表面模型的影响。指出了各算法的适用范围,并生成了高质量的数字表面模型产品———精确反映地形起伏的DEM和准确反映地物高程及形状信息的DSM。

BDS/GPS伪距差分改正数3种内插方法的比较

针对BDS/GPS融合伪距差分定位中,利用基准站改正数生成用户伪距改正数的各内插方法效率易受用户与基准站距离远近、基准站数量等因素影响的问题,分析当基准站数不同时,反距离权重插值法、线性内插法和低次曲面模型法等3种内插方法用于BDS/GPS融合伪距差分时的定位效率和精度,并提出适合BDS/GPS融合伪距差分定位的最优内插方法。实验结果表明,当用户附近可利用的基准站数不少于3站,采用离用户较近的3个基准站构成多边形网且用户在多边形网内时,利用反距离权重插值法或线性内插法生成伪距改正数来进行BDS/GPS融合伪距差分定位,所获得的定位效率和精度更优。

集成学习支持的复杂地貌类型区土壤全钾含量自适应曲面建模

土壤属性空间分布受复杂地学环境要素影响,空间分异特征十分明显,用单一全局插值模型进行土壤属性模拟,难以实现高精度模拟。对于空间不连续、全局插值模型精度有限及适应性差的特点,本文提出了一种集成学习支持的、融合地学环境变量的土壤属性自适应曲面建模方法(ASM-SP)。利用2013年采集的110个样点数据,使用回归克里金(RK)、贝叶斯克里金(BK)、普通克里金插值法(OK)、反距离加权法(IDW)、ASM-SP,分别对青海湖复杂地貌类型区进行土壤全钾含量的插补。本文采用逐点交叉验证(LOOCV)插值方法模拟精度。结果表明,ASM-SP不仅考虑了地学环境变量与土壤属性的非线性关系,而且融合了多个模型的适应性优势,是实现复杂地貌类型区土壤全钾含量的高精度模拟的一种新方法。