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利用ACE卫星数据对太阳质子事件预警方法的研究
引用本文:熊森林,崔延美,刘四清.利用ACE卫星数据对太阳质子事件预警方法的研究[J].空间科学学报,2013,33(4):387-395.
作者姓名:熊森林  崔延美  刘四清
作者单位:1.中国科学院空间科学与应用研究中心 北京 100190
基金项目:国家高技术研究发展计划重点项目(2009AA122205)和国家重点基础研究发展计划项目(2012CBB25606)共同资助
摘    要:通过分析GOES和ACE卫星大于10MeV能量段的5min平均质子通量数据,发现两者有很好的相关性,最佳相关系数显示,GOES通量数据较ACE卫星数据有数十分钟至几小时的时间延迟.这为利用ACE数据进行质子事件预警提供了依据.本文提出一种利用ACE卫星大于10MeV能量段的通量数据对质子事件进行预警的方法.该方法在2001年8月7日至2012年2月20日这11年多时间的试验中,表现出较高的报准率(76.3%)和较低的虚报率(14.7%),预警提前时间在数十分钟至几小时不等.该方法的结果与美国国家海洋和大气管理局(NOAA)空间天气预测中心(SWPC)使用的预警模型对比,具有更高的报准率,较低的虚报率,在预警时间提前量方面两者相当. 

关 键 词:质子通量    质子事件预警    太阳质子事件
收稿时间:2012-05-04

Research on Sloar Proton Event Warning With Observation Data of ACE Satellite
Institution:1.Center for Space Science and Applied Research, Chinese Academy of Sciences, Beijing 1001902.University of Chinese Academy of Sciences, Beijing 100049
Abstract:Solar Proton Event (SPE) can bring significant radiation hazards to astronauts and spacecrafts in space. An accuracy SPE warning model is meaningful since some effective actions on basis of the warning results could be done to reduce the abundant radiation from which astronauts and spacecrafts would suffer. Therefore, a number of researchers try to build reliable SPE warning models, and some of the results are quite satisfactory. Five-minute- average real-time integral energetic solar protons flux data (mainly above 10MeV) from ACE satellite and GOES in Solar Proton Event periods were analyzed. Besides, correlation coefficients between two kinds of data were calculated. The optimal correlation coefficients were satisfactory, and they showed that the flux data from GOES have tens of minutes up to several hours lag time compared with that from ACE. This paper tries to use the ACE satellite data described above to build a new SPE onset warning method. Furthermore, five-minute- average real time integral energetic proton flux on GOES from Aug. 7, 2001 to Feb. 20, 2012 were utilized to check the new method's validity. This new method has low false probabilities (14.7%) and fairly good detection probabilities (76.3%) in SPE onset warning. Moreover, it has a prior time from tens of minutes up to couple hours. The results were compared with SPE warning results of SWPC, which shows this new method is superior to the latter in some extent. 
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