From the Sun to the Earth: The 13 May 2005 Coronal Mass Ejection

We report the results of a multi-instrument, multi-technique, coordinated study of the solar eruptive event of 13 May 2005. We discuss the resultant Earth-directed (halo) coronal mass ejection (CME), and the effects on the terrestrial space environment and upper Earth atmosphere. The interplanetary CME (ICME) impacted the Earth’s magnetosphere and caused the most-intense geomagnetic storm of 2005 with a Disturbed Storm Time (Dst) index reaching ?263 nT at its peak. The terrestrial environment responded to the storm on a global scale. We have combined observations and measurements from coronal and interplanetary remote-sensing instruments, interplanetary and near-Earth in-situ measurements, remote-sensing observations and in-situ measurements of the terrestrial magnetosphere and ionosphere, along with coronal and heliospheric modelling. These analyses are used to trace the origin, development, propagation, terrestrial impact, and subsequent consequences of this event to obtain the most comprehensive view of a geo-effective solar eruption to date. This particular event is also part of a NASA-sponsored Living With a Star (LWS) study and an on-going US NSF-sponsored Solar, Heliospheric, and INterplanetary Environment (SHINE) community investigation.     

Geoinformational Mapping of Landscapes in the Northwestern Part of Western Siberia Using the Hansen Mosaic Dataset

Presented are the technique and results of studying the landscape structure of the north-west of Western Siberia on the basis of the Hansen mosaic dataset consisting of elements covering the entire territory of the Earth. To study this area used a synthesis of classical methods of thematic system mapping as described in the doctrine of geosystems of V. B. Sochava, and automated interpretation of remote sensing data and mapping using GIS technologies. The method of geoinformational mapping of the landscape structure with the use of MultiSpec and Quantum GIS software programs for the purpose of drawing up real-time raster landscape maps is shown. In drawing up the map and the legend, the principle of geomic system-hierarchical representation of the territory as a complex multi-level “bottom-up” structure from topological-level geosystems (groups and classes of landscape facies) to regional-level geosystems (geoms, groups and classes of geoms) was used. Compilation of operational raster landscape maps of the north-west of Western Siberia involved multilevel automated interpretation of the Hansen mosaic dataset and mapping of areas (clusters) on images with different brightness characteristics, with the landscape structure of key areas and stationary physical and geographical profiles. A characteristic of this approach also implies using a dynamic classification of geosystems based on the study of their variable states. Such an approach permits a monitoring of changes in landscape structure and its areas and the intensity of anthropogenic impacts on forest and marsh landscapes, and determination of permissible pressure on geosystems in areas with high technogenic pressure of the oil and gas complex represented by the north-west of Siberia. An automated processing of data based on a supervised classification of territorial objects allows for the elimination of inaccuracies arising in visual image interpretation. Raster landscape maps can be used both for a further generation of vector maps and as a real-time information base for purposes of environmental management and protection.     

Magnetic properties of x-ray bright points

Using high resolution KPNO magnetograms and sequences of simultaneous S-054 soft X-ray solar images we have compared the properties of X-ray bright points (XBP) and ephemeral active regions (ER). All XBP appear on the magnetograms as bipolar features, except for very newly emerged or old and decayed XBP. We find that the separation of the magnetic bipoles increases with the age of the XBP, with an average emergence growth rate of 2.2 ± 0.4 km s^–1. The total magnetic flux in a typical XBP living about 8 hr is found to be 2 x 10¹⁹ Mx. A proportionality is found between XBP lifetime and total magnetic flux, equivalent to 10²⁰ Mx per day of lifetime.Operated by the Association of Universities for Research in Astronomy, Inc. under contract with the National Science Foundation.     

Focusing and spatial resolution of electromagnetic three-coil sounders

Doklady Earth Sciences - Distribution density functions for the sensitivity of a three-coil sounder are constructed as the weighted mean rock volume between the in-phase surfaces of running...     

Some characteristics of astronomical climate on Mount Koshka,Simeiz

Coefficients of atmospheric extinction in the Johnson-Cousins system are determined for the astronomical point at Mount Koshka (Simeiz, Crimea). The astronomical point is characterized by high transparency and frequent periods of low quality of the image, which is explained by its position between the Crimean Range and the Black Sea.     

基于深度学习的GF-1卫星WFV影像赤潮探测方法

赤潮是我国主要的海洋生态灾害,有效监测赤潮的发生和空间分布对于赤潮的防治具有重要意义。传统的赤潮监测以低空间分辨率的水色卫星为主,但是其对于频发的小规模赤潮存在监控盲区。GF-1卫星WFV影像具有空间分辨率高、成像幅宽大和重访周期短等优点,在小规模赤潮监测中表现出较大的潜力。然而,GF-1卫星WFV影像的光谱分辨率较低,波段少,传统面向水色卫星的赤潮探测方法无法应用于GF-1卫星WFV数据。而且赤潮具有形态多变、尺度不一的特点,难以精确提取。基于此,本文提出了一种面向GF-1卫星WFV影像的尺度自适应赤潮探测网络（SARTNet）。该网络采用双层主干结构以融合赤潮水体的形状特征与细节特征,并引入注意力机制挖掘不同尺度赤潮特征之间的相关性,提高网络对复杂分布赤潮的探测能力。实验结果表明,SARTNet赤潮探测精度优于现有方法,F1分数达到0.89以上,对不同尺度的赤潮漏提和误提较少,且受环境因素的影响较小。     

Polarization observations of giant radio pulses from the millisecond pulsar B1937+21 at a frequency of 600 MHz

We performed polarization observations of giant radio pulses from the millisecond pulsar B1937+21. The observations were carried out in July 2002 with the 64-m Kalyazin radio telescope at a frequency of 600 MHz in two polarization channels with left-and right-hand circular polarizations (RCP and LCP). We used the S2 data acquisition system with a time resolution of 125 ns. The duration of an observing session was 20 min. We detected twelve giant radio pulses with peak flux densities higher than 1000 Jy; five and seven of these pulses appeared in the RCP and LCP channels, respectively. We found no event that exceeded the established detection threshold simultaneously in the two polarization channels. Thus, we may conclude that the detected giant pulses have a high degree of circular polarization, with the frequency of occurrence of RCP and LCP pulses being the same.     

Identification of the “source” and “sink” patterns influencing non-point source pollution in the Three Gorges Reservoir Area

Non-point source pollution is one of the primarily ecological issues affecting the Three Gorges Reservoir Area. In this paper, landscape resistance and motivation coefficient, which integrated various landscape elements, such as land use, soil, hydrology, topography, and vegetation, was established based on the effects of large-scale resistance and motivation on the formation of non-point source pollution. In addition, cost models of the landscape resistance and motivation coefficients were constructed based on the distances from the landscape units to the sub-basin outlets in order to identify the “source” and “sink” patterns affecting the formation of non-point source pollution. The results indicated that the changes in the landscape resistance and motivation coefficients of the 16 sub-basins exhibited inverse relationships to their spatial distributions. The landscape resistance and motivation cost curves were more volatile than the landscape resistance and motivation coefficient curves. The landscape resistance and motivation cost trends of the 16 sub-basins became increasingly apparent along the flow of the Yangtze River. The landscape resistance and motivation cost models proposed in this paper could be used to identify large-scale non-point source pollution “source” and “sink” patterns. Moreover, the proposed model could be used to describe the large-scale spatial characteristics of non-point source pollution formation based on “source” and “sink” landscape pattern indices, spatial localization, and landscape resistance and motivation coefficients.