4.5 Article

A novel technique to construct the global distribution of whistler mode chorus wave intensity using low-altitude POES electron data

期刊

JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS
卷 119, 期 7, 页码 5685-5699

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/2014JA019935

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资金

  1. JHU/APL [967399, 921647]
  2. JHU/APL under the NASA [NAS5-01072]
  3. EMFISIS [1001057397:01]
  4. NASA [NNX11AD75G, NNX11AR64G, NNX12AD12G, NNX13AI61G]
  5. NSFC [41204120]
  6. Fundamental Research Funds for the Central Universities [2042014kf0251]

向作者/读者索取更多资源

Although magnetospheric chorus plays a significant role in the acceleration and loss of radiation belt electrons, its global evolution during any specific time period cannot be directly obtained by spacecraft measurements. Using the low-altitude NOAA Polar-orbiting Operational Environmental Satellite (POES) electron data, we develop a novel physics-based methodology to infer the chorus wave intensity and construct its global distribution with a time resolution of less than an hour. We describe in detail how to apply the technique to satellite data by performing two representative analyses, i.e., (i) for one specific time point to visualize the estimation procedure and (ii) for a particular time period to validate the method and construct an illustrative global chorus wave model. We demonstrate that the spatiotemporal evolution of chorus intensity in the equatorial magnetosphere can be reasonably estimated from electron flux measurements made by multiple low-altitude POES satellites with a broad coverage of L shell and magnetic local time. Such a data-based, dynamic model of chorus waves can provide near-real-time wave information on a global scale for any time period where POES electron data are available. A combination of the chorus wave spatiotemporal distribution acquired using this methodology and the direct spaceborne wave measurements can be used to evaluate the quantitative scattering caused by resonant wave-particle interactions and thus model radiation belt electron variability.

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