Comparison of the Characteristics of Magnetic Clouds and Magnetic Cloud-Like Structures for the Events of 1995 – 2003

Using nine years of solar wind plasma and magnetic field data from the Wind mission, we investigated the characteristics of both magnetic clouds (MCs) and magnetic cloud-like structures (MCLs) during 1995 – 2003. A MCL structure is an event that is identified by an automatic scheme (Lepping, Wu, and Berdichevsky, Ann. Geophys. 23, 2687, 2005) with the same criteria as for a MC, but it is not usually identifiable as a flux rope by using the MC (Burlaga et al., J. Geophys. Res. 86, 6673, 1981) fitting model developed by Lepping, Jones, and Burlaga (Geophys. Res. Lett. 95(11), 957, 1990). The average occurrence rate is 9.5 for MCs and 13.6 for MCLs per year for the overall period of interest, and there were 82 MCs and 122 MCLs identified during this period. The characteristics of MCs and MCL structures are as follows: (1) The average duration, Δt, of MCs is 21.1 h, which is 40% longer than that for MCLs (Δt=15 h); (2) the average (minimum B _z found in MC/MCL measured in geocentric solar ecliptic coordinates) is −10.2 nT for MCs and −6 nT for MCLs; (3) the average Dst_min (minimum Dst caused by MCs/MCLs) is −82 nT for MCs and −37 nT for MCLs; (4) the average solar wind velocity is 453 km s⁻¹ for MCs and 413 km s⁻¹ for MCLs; (5) the average thermal speed is 24.6 km s⁻¹ for MCs and 27.7 km s⁻¹ for MCLs; (6) the average magnetic field intensity is 12.7 nT for MCs and 9.8 nT for MCLs; (7) the average solar wind density is 9.4 cm⁻³ for MCs and 6.3 cm⁻³ for MCLs; and (8) a MC is one of the most important interplanetary structures capable of causing severe geomagnetic storms. The longer duration, more intense magnetic field and higher solar wind speed of MCs, compared to those properties of the MCLs, are very likely the major reasons for MCs generally causing more severe geomagnetic storms than MCLs. But the fact that a MC is an important interplanetary structure with respect to geomagnetic storms is not new (e.g., Zhang and Burlaga, J. Geophys. Res. 93, 2511, 1988; Bothmer, ESA SP-535, 419, 2003).     

一种基于DCT变换的数字水印算法在“天地图·广东”中的应用

地理信息公共服务通过云平台进行部署和发布,可以使得其应用于政府部门和社会的空间数据服务更加高效和稳定。然而,把对应的地图信息挂载在云平台供应商处同时也加大了防止电子地图被盗用的难度。本文针对"天地图?广东"的电子地图瓦片,提出了一种具有高鲁棒性、基于离散余弦变换(DCT)的数字水印算法,在寄存云端和公开发布的电子地图中隐藏生产单位版权的数字水印图片,藉此来跟踪、抵制"天地图"图片数据的非法流通,非法复制,有效地保护数据生产单位的合法权益。     

关于云安全问题的探讨

云计算面临的最大挑战是安全问题。云计算应用的无边界性、流动性等特点,较之传统的IT模式有很大差异。在云计算环境下,服务方式发生变化,安全的责任主体也发生了根本改变。作为云计算服务提供商,需要建立安全的云计算平台,为云安全服务提供保障;同时,服务一定是开放的、安全的,要保护云用户敏感信息的安全。整合桌面安全管理技术是行之有效的。云安全应用研究主要是从云计算平台系统安全和网络安全设备、安全基础设施的“云化”突破几个方面展开。     

基于点云投影线探测的高墩位姿自动检测方法

针对目前超高桥墩垂直度检测方法存在危险系数较高、精度难以保证或自动化程度与工作效率较低的情况,本文提出一种基于三维激光扫描技术的点云数据超高桥墩位姿自动检测方法.该方法首先将海量墩面点云双向分层;然后依条件选择分层文件探测点云投影线并划分桥墩面缓冲区;最后根据缓冲区自动提取墩面点云并进行位姿检测.本文以某山区高速桥梁高...     

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。