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  • 标题:Tests of a New Solar Flare Model Against D and E Region Ionosphere Data
  • 本地全文:下载
  • 作者:David E.Siskind ; McArthur Jones Jr. ; Jeffrey W.Reep
  • 期刊名称:Space Weather
  • 印刷版ISSN:1542-7390
  • 出版年度:2022
  • 卷号:20
  • 期号:5
  • 页码:1-19
  • DOI:10.1029/2021SW003012
  • 语种:English
  • 出版社:American Geophysical Union
  • 摘要:We present results from a suite of models designed to simulate solar flare effects on the D and E region of the ionosphere. This suite includes models of the solar spectrum, the ionosphere and of HF radiowave propagation. A central component of this system is the development of photoelectron ionization enhancement factors with higher energy resolution in the soft X-ray spectral region that can be used to supplement existing ionization schemes currently implemented in upper atmospheric general circulation models. We tested this photoelectron model in the NCAR Thermosphere-Ionosphere-Mesosphere- Electrodynamics General Circulation Model (TIME-GCM) and in a photochemical model of the D region. In both cases, we compared predicted flare response using two different input solar flare spectra. One is the Flare Irradiance Spectral Model (FISM) and the other is a physics based model called NRLFLARE. Our predictions for the E region were compared with incoherent scatter radar data and suggest that enhanced flux in the 1–2 nm spectral region, as indicated by NRLFLARE, is important for reproducing the observations. For the D region, we combined our theoretical results for the X1.3 flare of 7 September 2017 with ray tracing calculations that suggest 20–40 db of 6.4 MHz absorption. This agrees with previously published observations and model estimates, all of which suggest greater HF absorption than the operational D region absorption prediction model (swpc.noaa.gov/products/d-region-absorption-predictions-d-rap). Finally, our theoretical comparison with previously published empirical models derived from very low frequency data was less clear due, in part, to large differences between the different empirical models.
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