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https://doi.org/10.1016/s1364-6826(96)00037-5
Copy DOIPublication Date: Jan 1, 1997 | |
Citations: 14 |
Abstract Historically, the high latitude ionosphere has been viewed as the most complex of the ionospheric regions because it is driven by both magnetospheric and solar inputs. At lower latitudes the direct, and highly variable, magnetospheric input is relatively unimportant, which makes these other regions amenable to empirical modeling. To date, however, no empirical model of the high latitude ionosphere is available which includes these complex dependencies. On the other hand, numerical models that include the physics of this region have been developed and have proven to be successful at the climatology level. In this study we present the climatological results of one of these models, namely the Utah State University (USU) timedependent ionospheric model (TDIM). A total of 108 separate TDIM simulations for different ionospheric conditions were used to elucidate the high latitude ionospheric trends. These trends depend on solar cycle, season, universal time (UT), magnetic activity, interplanetary magnetic field (IMF) orientation, and hemisphere. The ionospheric climatology is not dominated by any one of these parameters. The solar cycle ( F 10.7 index), season (day), and magnetic activity ( K p index) compete on an even footing for control of the high latitude ionosphere. Mean variations of over an order of magnitude in N m F 2 , of over 150 km in h m F 2 , and of over 50 km in the transition height are present in the high latitude ionospheric climatology. The 108 simulations quantify the trends and show the UT dependence and spatial variability of the ionosphere. Some aspects of these UT trends are compared successfully with observations. Many of the simulation results are predictions that can be verified as more complete observational databases become available. The UT dependence, which at times can be a factor of two modulation of the F region densities, is a key reason for the failure of statistical models at high latitudes. At lower latitudes, statistical models based mainly on local time rather than UT have been very successful. At high latitudes, this is not so and, therefore, local time and UT (longitude) must be treated as independent variables. This fact alone explains why data sets based on a fixed ground location or satellite orbital plane cannot unravel the LT and UT dependencies at high latitudes. Also, the high latitude ionosphere is not spatially uniform; morphological features on latitudinal scales of 1–2 ° are present. These structures play a key role in identifying the ionospheric climatology.
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