CO Clouds around SNR G21.8-0.6 and G32.8-0.1

We made the first CO(I—0) mapping to SNR G21.8-0.6 and SNR G32.8-0.1, both associated with OH 1720 MHz maser.Based on the morphological correspondence and velocity and position agreement between the radio remnant and the CO clouds,we tentatively identify the clouds that are respectively interacting with the two SNRs.     

The Dependence of the Geoeffectiveness of Interplanetary Flux Rope on Its Orientation,with Possible Application to Geomagnetic Storm Prediction

Interplanetary magnetic clouds (MCs) are one of the main sources of large non-recurrent geomagnetic storms. With the aid of a force-free flux rope model, the dependence of the intensity of geomagnetic activity (indicated by Dst index) on the axial orientation (denoted by θ and φ in GSE coordinates) of the magnetic cloud is analyzed theoretically. The distribution of the Dst values in the (θ, φ) plane is calculated by changing the axial orientation for various cases. It is concluded that (i) geomagnetic storms tend to occur in the region of θ<0°, especially in the region of θ≲−45°, where larger geomagnetic activity could be created; (ii) the intensity of geomagnetic activity varies more strongly with θ than with φ; (iii) when the parameters B ₀ (the magnetic field strength at the flux rope axis), R ₀ (the radius of the flux rope), or V (the bulk speed) increase, or |D| (the shortest distance between the flux rope axis and the x-axis in GSE coordinates) decreases, a flux rope not only can increase the intensity of geomagnetic activity, but also is more likely to create a storm, however the variation of n (the density) only has a little effect on the intensity; (iv) the most efficient orientation (MEO) in which a flux rope can cause the largest geomagnetic activity appears at φ∼0° or ∼ 180°, and some value of θ which depends mainly on D; (v) the minimum Dst value that could be caused by a flux rope is the most sensitive to changes in B ₀ and V of the flux rope, and for a stronger and/or faster MC, a wider range of orientations will be geoeffective. Further, through analyzing 20 MC-caused moderate to large geomagnetic storms during 1998 – 2003, a long-term prediction of MC-caused geomagnetic storms on the basis of the flux rope model is proposed and assessed. The comparison between the theoretical results and the observations shows that there is a close linear correlation between the estimated and observed minimum Dst values. This suggests that using the ideal flux rope to predict practical MC-caused geomagnetic storms is applicable. The possibility of the long-term prediction of MC-caused geomagnetic storms is discussed briefly.     

Deep convective clouds over the northern Pacific and their relationship with oceanic cyclones

Based on combined Cloud Sat/CALIPSO detections, the seasonal occurrence of deep convective clouds(DCCs) over the midlatitude North Pacific(NP) and cyclonic activity in winter were compared. In winter, DCCs are more frequent over the central NP, from approximately 30°N to 45°N, than over other regions. The high frequencies are roughly equal to those occurring in this region in summer. Most of these DCCs have cloud tops above a 12 km altitude, and the highest top is approximately 15 km. These wintertime marine DCCs commonly occur during surface circulation conditions of low pressure, high temperature, strong meridional wind, and high relative humidity. Further, the maximum probability of DCCs,according to the high correlation coefficient, was found in the region 10°–20° east and 5°–10° south of the center of the cyclones. The potential relationship between DCCs and cyclones regarding their relative locations and circulation conditions was also identified by a case study. Deep clouds were generated in the warm conveyor belt by strong updrafts from baroclinic flows. The updrafts intensified when latent heat was released during the adjustment of the cyclone circulation current. This indicates that the dynamics of cyclones are the primary energy source for DCCs over the NP in winter.     

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基于LiDAR点云数据的树冠空隙度指数分析

分形维数法是分析空间结构分布的一种典型方法,但它对于区分不同的分布形式还存在缺陷。针对这一问题,该文介绍了空隙度指数的定义和树冠空隙度的计算方法;以模拟的树冠点云数据为对象,提出了一种基于三维凸包和三维滑动盒算法的激光雷达(Li DAR)点云数据空隙度分析方法,详尽分析了不同冠型产生的空隙度指数差异;并利用4棵实测的树冠点云数据做检验;最后阐述了空隙度指数在树冠空间异质性分析研究中的作用,并对其应用范围和前景作了展望。结果表明:划分尺度相同时,在一定的尺度范围内,锥型树冠、半球型和半椭球型树冠的差别可以通过空隙度指数曲线有效地区分,实测树冠的结果也体现了空隙度指数对于判断树冠空间结构的有效性。