Effects of Interpolation Errors on the Analysis of DEMs

A suite of methods to interpolate a digital elevation model from a ground survey was evaluated with respect to precision and ability to maintain the shape of the original height data. This shape reliability was evaluated by comparing the spatial patterns of secondary terrain parameters derived from the interpolated elevation data. The best interpolation method for this study area was found to be a spline interpolation, which is somewhat contradictory to findings in the literature. The error and uncertainty found in the results for terrain analysis and modelling tools is important and sometimes distressingly high, even for some frequently used local or context operations on altitude. Positional operations, in which the output is determined more by the position in the topographic structure, seem to give more reliable results. Therefore, the results obtained by terrain analysis and spatial modelling need careful interpretation. © 1997 John Wiley & Sons, Ltd.     

宽带太阳漫射辐射法反演辐射加权平均的气溶胶一次散射反照率研究

引入了一个辐射加权平均的宽带气溶胶一次散射反照率(SSA)的定义,提出了一个从宽带的漫射信息反演该SSA的方法.数值模拟结果表明,在Junge气溶胶谱分布情形下,对气溶胶光学厚度、(A)ngstr(o)m 指数与气溶胶虚部的通常变化范围,应用该SSA所计算的2160组宽带太阳辐射反射率、漫射透过率、总透过率和吸收率的相对标准误差都在1.107%以内; 绝对标准差在0.00287以内.对非Junge的大陆性和都市工业污染气溶胶模式(由水溶性、沙尘和碳粒子组成),在72组反射率、漫射透过率、总透过率和吸收率计算中,相对标准差都在2.047%以内,绝对标准差在0.0075以内.在Junge气溶胶假设下,作者提出了一个综合应用宽带太阳直射和漫射信息同时反演气溶胶光学厚度与辐射加权平均SSA的方法,并通过模拟反演分析了SSA反演的3个主要误差因子.从反演结果可以看出:(1)如果(A)ngstr(o)m指数误差在±0.2以内,对0.55 μm气溶胶光学厚度大于0.312大陆性气溶胶,SSA误差在±0.0418以内;(2)波长无关的宽带地表反照率适用于SSA反演;(3)气溶胶光学厚度越大,辐射资料误差所引起的SSA解误差越小.当辐射误差在±2%以内以及0.55 μm气溶胶光学厚度大于0.312时,SSA解的误差在±0.0149以内; 辐射误差在±4%以内时,SSA解的误差在±0.0317以内.     

ON THE NECESSITY OF APPLYING A ROTATION TO INSTANTANEOUS VELOCITY MEASUREMENTS IN RIVER FLOWS

In studies on river channel flow turbulence, it is often the case that the measured mean vertical velocity is different from zero, indicating that the frame of reference of the current meter is not parallel to the flow streamline. This situation affects the estimate of Reynolds shear stress in the streamwise and vertical planes and consequently the analysis of the flow turbulent structure. One way to solve this problem is to correct data by applying a rotation and this is reviewed in the first part of the paper. However, in fluvial geomorphology, the studied flow is often complex and streamlines may exhibit significant changes from one point of measurement to the other. In this context, applying a rotation complicates the situation more than it simplifies it. The second part of this paper examines the question of velocity data correction in complex flows using a field example of the turbulent boundary layer over a very rough gravel bed and a laboratory example taken from flow at a river channel confluence. In both cases, velocity vectors are spatially variable. In the first case, errors in the Reynolds shear stress estimates are relatively low (ranging from −13 to 7 per cent/deg) while in the second case, they are much larger (−200 to 164 per cent/deg). The significance of these errors on the interpretation of turbulence statistics in river channel flows is discussed. We propose that corrections should be applied in all clear cases of sensor misalignment and when the frame of reference changes spatially and temporally. However, no corrections should be used where different flow velocity vector orientations, not sensor misalignment, are responsible for the mean vertical velocity differing from zero.     

大间距地震数据重建方法研究

介绍了一种基于稀疏约束最小二乘方法的大间距地震道数据重建方法,通过对大间距地震数据空间加滑动窗口,对每个窗口的数据结果采用预测误差算子计算加权系数进行加权叠加处理而得到空道的结果,通过试验表明,该方法能够用来进行大间距地震道数据的重建.     

全球降水计划IMERG和GSMaP反演降水在四川地区的精度评估

IMERG和GSMaP是全球降水计划（GPM）时代最主要的高分辨率降水产品。为研究其在中国四川地区的适用性,以中国气象局提供的自动气象站融合降水数据为参考基准,采用6种统计指数分析了IMERG（IMERG_Uncal, IMERG_Cal）和GSMaP（GSMaP_MVK, GSMaP_Gauge）系列产品在四川的误差特征。结果表明：① 在日和小时尺度上,GSMaP系列产品均高估地面降水观测,GSMaP_MVK高估最显著,校正产品GSMaP_Gauge的相关系数（CC）、相对偏差（BIAS）和均方根误差（RMSE）较GSMaP_MVK均有较大提高,尤其对川西高原降水的高估现象改善明显,而IMERG_Uncal存在低估川西高原降水、轻微高估四川盆地降水的问题,校正产品IMERG_Cal一定程度上降低了对川西高原降水的低估现象,但整体精度（CC, RMSE）提高不明显。② IMERG系列产品对降水事件的探测准确性更好,GSMaP_Gauge虽然在四川表现出较高的命中率（POD）,但存在较多的误报降水,在盆地和四川南部各产品均表现出较高的POD和关键成功指数（CSI）以及低误报率（FAR）,而四川西北部表现最差,尤其是在无自动站分布地区。③ 4套降水产品中,IMERG_Cal表现出最好的探测强降水和弱降水的能力,具有一定的监测极端降水的潜力。总体上,IMERG和GSMaP在盆地的反演精度优于高原山区,校正产品精度优于纯卫星产品,不同地形地区精度差异明显,表明对卫星降水产品进行不同地形误差订正仍是未来降水反演工作的重点和难点。     

利用星载InSAR技术获取DEM及误差来源分析

星载干涉合成孔径雷达(InSAR)技术是一种高效的数字高程模型(DEM)获取方法,对其展开探讨具有十分重要的意义。本文对InSAR高程测量原理进行简要概述,提出获取DEM的相关技术流程,并分析了利用星载InSAR技术获取DEM的误差来源。     

地动噪声RMS值计算方法的适用性及误差概率分析

对比两种计算RMS值的方法,结合误差概率统计给出结果的误差概率分布。在使用有限脉冲响应（FIR）带通滤波器进行滤波并计算RMS值的过程中,滤波器窗口函数和阶数是影响计算结果误差的主要因素,其中阶数的作用更大。通过计算功率谱密度（PSD）反算RMS值的误差主要受pwelch函数的窗口函数类型、窗口长度及重叠率等参数影响,其中窗口长度作用更大。从同等误差水平的概率分布看,在合理设置参数的前提下,使用PSD反算RMS值的方法更优。     

病态数据处理的岭估计迭代解法

岭估计通常无法单次计算使得均方误差达到最小,因此提出岭估计迭代法。将岭估计参数估值代入平差模型,更新观测向量,再次用岭估计法求解参数。依此迭代,每次迭代计算方差和偏差,当均方误差达到最小或收敛时终止。模拟算例验证结果表明,该方法有效、可行。     

青藏高原观测地表温度与ERA-Interim再分析资料的差异及归因分析

再分析资料评估对观测资料稀少的青藏高原具有重要意义,是开展青藏高原相关研究的基础。本文分析了2012—2016年观测与ERA-Interim再分析地表温度资料在青藏高原的时空分布差异,同时讨论了产生差异的可能原因。结果表明,两种资料变化趋势基本一致,极值出现月份相同,相关性的空间分布表现为北高南低。ERA-Interim再分析资料对地表温度存在低估,年平均值比观测资料低8.86℃,其中春季绝对误差最大。年平均绝对误差呈北低南高的空间分布形态,且绝对误差极值中心的强度及范围具有明显的季节变化。ERA-Interim与观测地表温度之间的偏差随气象站海拔高度的变化是非单调的,分析认为气象站与所在格点的海拔差是导致偏差出现南北差异的原因之一,而春季青藏高原南部的偏差异常可能与积雪有关。ERA-Interim再分析地表温度资料在青藏高原北部具有较好的适用性,南部受地形影响适用性相对较差。