【作者】 胡雄； 龚建村； 杨钧烽； 肖存英； 涂翠； 吴小成； 王博； 谢衍新；

【Author】 Xiong Hu;Jiancun Gong;Junfeng Yang;Cunying Xiao;Cui Tu;Xiaocheng Wu;Bo Wang;Yanxin Xie;Center for Space Science and Applied Researches,Chinese Academy of Sciences;University of the Chinese Academy of Sciences;

【机构】 中国科学院空间科学与应用研究中心； 中国科学院大学；

【摘要】 临近空间是日地能量耦合系统的关键区域之一,有着与其他大气层不同的、复杂的辐射、光化学和动力学过程。临近空间大气易受来自下面的低层大气过程、和来自上面的太阳活动/空间天气过程的影响,其预报难度大。中科院空间中心开展了临近空间环境预报方法的探索。一方面,基于单站临近空间环境探测数据的时间序列,采用统计预报方法开展了预报时效为48小时的单站预报实验;另一方面,开展了临近空间大气数据同化方法研究,初步发展了全球临近空间大气同化预报方法,并利用该方法开展了预报时效为7天的全球预报实验;采用地基和卫星数据对预报结果进行了对比分析。结果表明,单站统计预报和全球预报都给出了可靠的预报结果。更多还原

【Abstract】 Near-space has unique and complex radiation-chemical and dynamical processes which are different from other atmospheric layers, and is one of the key regions of the solar-terrestrial energetic coupling system. Either the perturbations from the lower atmosphere or the solar variations and space weathers from the above have influences on it and make its prediction somewhat difficult. The singlesite statistical prediction method and the global dataassimilation numerical prediction method are investigated in CSSAR, CAS. In single site statistics prediction method, the AR prediction model is constructed with the time serial data prepared with the detecting 20-100 km near-space atmospheric temperature, density and wind data at one site. A 48 h prediction experiment with the above method has been completed. In the global prediction method, the near-space numerical prediction frame with data assimilations is constructed preliminarily. A 7d prediction experiment with the global numerical prediction method has been completed. The prediction results are compared with the ground-based and satellite atmospheric observation data, which shows the prediction results are reliable.更多还原