Bimodal distribution of area-weighted latitude of sunspots and solar North-South asymmetry

We study the latitudinal distribution of sunspots observed from 1874 to 2009 using the center-of-latitude (COL). We calculate COL by taking the area-weighted mean latitude of sunspots for each calendar month. We then form the latitudinal distribution of COL for the sunspots appearing in the northern and southern hemispheres separately, and in both hemispheres with unsigned and signed latitudes, respectively. We repeat the analysis with subsets which are divided based on the criterion of which hemisphere is dominant for a given solar cycle. Our primary findings are as follows: (1) COL is not monotonically decreasing with time in each cycle. Small humps can be seen (or short plateaus) around every solar maxima. (2) The distribution of COL resulting from each hemisphere is bimodal, which can well be represented by the double Gaussian function. (3) As far as the primary component of the double Gaussian function is concerned, for a given data subset, the distributions due to the sunspots appearing in two different hemispheres are alike. Regardless of which hemisphere is magnetically dominant, the primary component of the double Gaussian function seems relatively unchanged. (4) When the northern (southern) hemisphere is dominant the width of the secondary component of the double Gaussian function in the northern (southern) hemisphere case is about twice as wide as that in the southern (northern) hemisphere. (5) For the distribution of the COL averaged with signed latitude, whose distribution is basically described by a single Gaussian function, it is shifted to the positive (negative) side when the northern (southern) hemisphere is dominant. Finally, we conclude by briefly discussing the implications of these findings on the variations in the solar activity.     

A possible active galactic nucleus in M82?

MERLIN and VLA observations of the galaxy M82 have detected a jet-like feature emanating from one of the compact sources, 44.01+59.6. The proximity of this source to the dynamical centre of M82 led us to suspect that it could be a weak active nucleus rather than an SNR. We imaged this source using the EVN at 15 mas and although it shows a compact shell-like structure which could be consistent with an SNR, we note that the EVN image shows a bright region within the source which is elongated along the jet direction. There are distinct similarities between this source and the Sgr A complex at the centre of our own Galaxy which contains the compact AGN, Sgr A^*.     

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北斗三号组网卫星数据质量分析及单系统定轨精度初步评估

选取2018-01-23起10 d内16个iGMAS测站观测数据,对北斗三号卫星的观测数据质量及BDS单系统精密定轨精度进行评估。初步结果表明,老信号B1I、B3I北斗三号卫星的信噪比略强于二号卫星,噪声与多路径基本相当,均在0.1 m量级,新卫星不存在星内多路径偏差。新信号B1C/L1/E1频点GPS信噪比最强,Galileo和BDS卫星相当,B2a/L5/E5a和B2b/E5b各系统基本相当;噪声及多路径方面,B1C/L1/E1频点GPS优于BDS、Galileo卫星0.1 m量级,B2a/L5/E5a和B2b/E5b各系统基本相当,均在0.1 m量级,新信号中北斗三号卫星星内多路径偏差基本消失。单系统精密定轨试验中,分别进行有/无GEO卫星策略、太阳光压模型ECOM 五/九参数策略的比较,并使用卫星激光测距数据进行独立检核。初步结果表明,有GEO卫星、ECOM五参数光压模型的定轨精度最好,C19号卫星7个重叠弧段的平均定轨精度在沿迹向、法向、径向的精度分别为32 cm、16 cm、8 cm,与试验卫星的定轨精度基本相当。     

遗传算法优化的BP神经网络卫星钟差预报

针对BP (Back Propagation)神经网络模型预测卫星钟差中权值和阈值的最优化问题, 提出了基于遗传算法优化的BP神经网络卫星钟差短期预报模型, 给出了遗传算法优化BP神经网络的基本思想、具体方法和实施步骤. 为验证该优化模型的有效性和可行性, 利用北斗卫星导航系统(BeiDou navigation satellite system, BDS)卫星钟差数据进行钟差预报精度分析, 并将其与灰色模型(GM(1,1))和BP神经网络模型预报的结果比较分析. 结果表明: 该模型在短期钟差预报中具有较好的精度, 优于GM(1,1)模型和BP神经网络模型.     

利用反射地震资料中的面波研究剖面浅部结构

本研究利用浅层反射地震数据中的面波信息反演提取近地表横波速度结构,取得了较好的效果。该方法在一定程度上可弥补浅部反射资料的缺失,进而提高近地表结构探测的可靠性,同时也实现了对地震资料的充分利用。     

Wide-field VLBI imaging

We discuss the technique of Wide-field imaging as it applies to Very Long Baseline Interferometry (VLBI). In the past VLBI data sets were usually averaged so severely that the field-of-view was typically restricted to regions extending a few hundred milliarcseconds from the phase centre of the field. Recent advances in data analysis techniques, together with increasing data storage capabilities, and enhanced computer processing power, now permit VLBI images to be made whose angular size represents a significant fraction of an individual antenna's primary beam. This technique has recently been successfully applied to several large separation gravitational lens systems, compact Supernova Remnants in the starburst galaxy M82, and two faint radio sources located within the same VLA FIRST field. It seems likely that other VLBI observing programmes might benefit from this wide-field approach to VLBI data analysis. With the raw sensitivity of global VLBI set to improve by a factor 4–5 over the coming few years, the number of sources that can be detected in a given field will rise considerably. In addition, a continued progression in VLBI's ability to image relatively faint and extended low brightness temperature features (such as hot-spots in large-scale astrophysical jets) is also to be expected. As VLBI sensitivity approaches the μJy level, a wide-field approach to data analysis becomes inevitable.     

Detecting Arctic snow and ice cover with FY-1D global data

Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice samples,2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries.Land and water can be detected by spectral features.Snow-ice and cloud can be classified by textural features.The classifier is Bayes classifier.By synthesizing five d ays classifying result of Arctic snow and ice cover area,complete Arctic snow and ice cover area can be obtained.The result agrees with NOAA/NESDIS IMS products up to 70%.