Shortwave cloud radiative forcing on major stratus cloud regions in AMIP-type simulations of CMIP3 and CMIP5 models

Cloud and its radiative effects are major sources of uncertainty that lead to simulation discrepancies in climate models. In this study, shortwave cloud radiative forcing (SWCF) over major stratus regions is evaluated for Atmospheric Models Intercomparison Project (AMIP)-type simulations of models involved in the third and fifth phases of the Coupled Models Intercomparison Project (CMIP3 and CMIP5). Over stratus regions, large deviations in both climatological mean and seasonal cycle of SWCF are found among the models. An ambient field sorted by dynamic (vertical motion) and thermodynamic (inversion strength or stability) regimes is constructed and used to measure the response of SWCF to large-scale controls. In marine boundary layer regions, despite both CMIP3 and CMIP5 models being able to capture well the center and range of occurrence frequency for the ambient field, most of the models fail to simulate the dependence of SWCF on boundary layer inversion and the insensitivity of SWCF to vertical motion. For eastern China, there are large differences even in the simulated ambient fields. Moreover, almost no model can reproduce intense SWCF in rising motion and high stability regimes. It is also found that models with a finer grid resolution have no evident superiority than their lower resolution versions. The uncertainties relating to SWCF in state-of-the-art models may limit their performance in IPCC experiments.     

基于MODIS的春、夏季中国近海气溶胶对于云参数的影响差异研究

通过分析中国近海MODIS数据中气溶胶参数与云参数的相互关系,讨论了该区域气溶胶的间接效应及其对于云的可能影响.结果表明,在中国近海,气溶胶具有明显的间接效应,而且由于气溶胶种类和水汽的季节变化,使得气溶胶的间接作用具有很强的时间变化特征.在夏季,由于人为气溶胶占主导,它作为有效的云凝结核,使得气溶胶光学厚度（AOT）分别与云凝结核数（CCN）有正相关、与云滴有效半径（CER）有负相关性、与云光学厚度（COT）也存在着正相关,气溶胶的间接效应明显;在春季,由于沙尘气溶胶盛行,同时沙尘并不是很好的云凝结核,使得气溶胶光学厚度（AOT）分别与云凝结核数（CCN）的正相关减弱、与云滴有效半径（CER）则由夏季的负相关变为正相关、与云光学厚度（COT）存在弱的负相关,气溶胶的间接效应不明显.     

Monitoring soil surface roughness under growing winter wheat with low-altitude UAV sensing: Potential and limitations

Soil surface roughness (SSR) is an important factor in controlling sediment and runoff generation, influencing directly a wide spectrum of erosion parameters. SSR is highly variable in time and space under natural conditions, and characterizing SSR to improve the parameterization of hydrological and erosion models has proved challenging. Our study uses recent technological and algorithmic developments in capturing and processing close aerial sensing data to evaluate how high-resolution imagery can assist the temporally and spatially explicit monitoring of SSR. We evaluated the evolution of SSR under natural rainfall and growing vegetation conditions on two arable fields in Denmark. Unmanned aerial vehicle (UAV) photogrammetry was used to monitor small field plots over 7 months after seeding of winter wheat following conventional and reduced tillage treatments. Field campaigns were conducted at least once a month from October until April, resulting in nine time steps of data acquisition. Structure from motion photogrammetry was used to derive high-resolution point clouds with an average ground sampling distance of 2.7 mm and a mean ground control point accuracy of 1.8 mm. A comprehensive workflow was developed to process the point clouds, including the detection of vegetation and the removal of vegetation-induced point cloud noise. Rasterized and filtered point clouds were then used to determine SSR geostatistically as the standard deviation of height, applying different kernel sizes and using semivariograms. The results showed an influence of kernel size on roughness, with a value range of 0.2–1 cm of average height deviation during the monitoring period. Semivariograms showed a measurable decrease in sill variance and an increase in range over time. This research demonstrated multiple challenges to measuring SSR with UAV under natural conditions with increasing vegetation cover. The proposed workflow represents a step forward in tackling those challenges and provides a knowledge base for future research. © 2020 John Wiley & Sons, Ltd.     

NUMERICAL STUDY OF REMOTE SENSING OF CLOUD LIQUID WATER CONTENT BY SPACE-BORNE COMBINED RADAR-RADIOMETER

A retrieval method of microwave(MW)space-borne remote sensing of cloud liquid watercontent by the combined radar-radiometer is suggested.A three-layer cloud model is chosen torepresent the typical stratified precipitating cloud.The retrieval method mainly follows ourpreviously suggested scheme with some modifications.Numerical comparative study shows that inspace-borne remote sensing of cloud liquid water content by the combined method is much betterthan by radar only;Also the retrieval accuracy of cloud liquid water content may be improvedwhen using the three-layer cloud model in the combined method.     

“云指数法”云检测研究

针对FY-2C数据的特点,提出了一种基于云指数进行云检测的方法。实验结果表明,该方法能在光谱信息较少、空间分辨率较低的情况下,对大空间尺度的FY-2C遥感数据提供较好的云检测结果。     

基于Mallat算法遥感图像去云雾处理的改进方法

遥感图像云雾处于相对低频、景物处于相对高频。根据小波变换多分辨率的特点,分析云雾和景物在小波系数中的分布,得出景物信息包含于低层细节系数,而云雾信息包含于高层细节系数和近似系数。本文通过增大图像的低层细节系数,减小高层细节系数,并适当减小近似系数,达到去除云雾的目的。最后评价了图像处理结果,并与同态滤波做比较,表明本文方法是有效的。     

三维激光扫描在建设工程竣工规划核实中的应用研究

本文介绍了建设工程竣工规划核实的主要方式,阐述了测量在竣工规划核实中的重要性,及目前核实方式中存在的问题.然后,针对三维激光扫描的技术原理,分析了三维激光扫描技术在竣工规划核实中应用的可行性,并通过对控制点布设、点云配准、建筑物特征点提取等技术方法的研究,实现了三维激光扫描在竣工规划核实中的应用,具有一定理论意义和实用价值.     

三维激光扫描技术在复杂地质隧道岩体信息获取中的优化

为了更高效、高精度地获取岩体结构面信息,借助三维激光扫描技术,提出并建立一种基于Kriging算子和最小二乘法组合的点云插值方法。首先对获取的隧道点云数据利用单一的最小二乘法进行插值,并以此为基础,结合Kriging算子的适应度函数建立组合插值模型。在利用三维激光扫描仪已获取的某岩溶隧道的原始点云数据的基础上,运用组合模型进行插值处理,以此获取岩体结构面信息,并将组合方法得到的结果与单一的插值方法进行对比,发现组合方法插值效果较好,误差也较小。基于Kriging算法和最小二乘法结合的插值方法,在利用三维激光扫描技术获取岩溶隧道岩体几何信息—结构面产状的过程中能更加精确、全面,并可以用于岩体稳定性评价。     

基于激光点云数据的古建筑BIM几何模型构建

针对古建筑BIM各种信息模型中几何模型构建的问题,提出应用三维激光点云数据和CloudWorx软件进行建模的方法。应用Cyclone软件对点云数据进行去噪、配准,按构件进行分割;应用CloudWorx软件进行模型的构建。研究古建筑的瓦片、柱体、梁、墙体、围栏等构件的建模方法,通过模型合并生成古建筑的整体几何模型。     

电力巡线LiDAR点云电塔自动定位和提取算法

针对电力巡线机载激光雷达(LiDAR)激光点云电塔自动提取问题,提出了一种电塔自动定位和点云提取算法。首先,基于点云进行二维空间网格划分,利用网格点云高程偏差和方差特征提取潜在电塔网格;其次,基于电塔点云的高程连续特性完成电塔自动定位和点云粗提取;然后,利用点云分层密度信息和图像开运算,实现电塔精细提取;最后,利用轻小型无人机载激光雷达数据验证本文算法的有效性。试验结果表明,本文所提出的自动提取算法,能够有效解决LiDAR数据中电塔自动定位和点云提取问题,在LiDAR数据质量较差时仍能够取得良好效果,算法对于噪点数据具有较强的稳健性。本文所提出的电塔自动提取算法在LiDAR电力巡检数据处理中具有一定的应用价值。