Modeling the climatology of equatorial plasma bubbles observed by DMSP
Modeling the climatology of equatorial plasma bubbles observed by DMSP
复制标题
模拟 DMSP 观测到的赤道等离子体气泡的气候学
DOI：
10.1029/2008rs004057
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发表时间：
2009
期刊：
影响因子：
1.6
通讯作者：
L. Gentile
中科院分区：
文献类型：
--
作者：
J. Retterer;L. Gentile
极轨国防气象卫星计划 (DMSP) 航天器上的空间环境传感器在晚间区域穿越地磁赤道时偶尔会遇到等离子体密度损耗。这些赤道等离子体气泡（EPB）是在赤道扩散F和射电闪烁现象容易发生的时间和地点附近观察到的。观测到的这些损耗频率（在过去 19 年中确定）的太阳周期、季节和纵向变化确实与闪烁的情况相似。为了测试我们对 EPB 形成的理解，我们使用 PBMOD 模拟了观测结果，PBMOD 是一套环境电离层和 EPB 形成的第一原理模型，由其输入参数（例如等离子体漂移速度）的气候模型驱动。 840 km 处的 EPB 频率模型计算图作为季节和经度的函数，显示出与 DMSP 观测结果类似的模式，包括春分点附近 EPB 频率的预期峰值、美洲地区的额外冬季峰值、太平洋地区的夏季峰值以及太阳周期相位的正确趋势。调整模型以详细重现 DMSP EPB 发生频率将使我们能够微调 PBMOD，并提供一种使用 DMSP 数据来增强通信/导航中断预报系统 (C/NOFS) 任务的经验驱动因素的方法。
Space environmental sensors on polar‐orbiting Defense Meteorological Satellite Program (DMSP) spacecraft occasionally encounter plasma density depletions when they cross the geomagnetic equator in the evening sector. These equatorial plasma bubbles (EPBs) are observed around the times and locations when equatorial spread F and radio scintillation phenomena tend to occur. The solar cycle, seasonal, and longitudinal variations in the observed frequency of these depletions (determined over the past 19 years) are indeed similar to those of scintillation. To test our understanding of EPB formation, we simulated the observations using PBMOD, a suite of first‐principle models of the ambient ionosphere and EPB formation, driven by climatological models for its input parameters such as the plasma drift velocity. Maps of the model calculations of EPB frequencies at 840 km as functions of season and longitude exhibit patterns similar to the DMSP observations, including the expected peaks in EPB frequency near the equinoxes, an additional winter peak in the American sector, a summer peak in the Pacific sector, and the proper trends with solar cycle phase. Adjusting the model to reproduce the DMSP EPB occurrence frequencies in detail will allow us to fine tune PBMOD and provides a means for using the DMSP data to enhance the empirical drivers for the Communication/Navigation Outage Forecasting System (C/NOFS) mission.