/pdf/patterns-of-f2-layer-variability-30tf20qssu.pdf

Patterns of F2-layer variability

[1] The ionosphere's total electron content (TEC) is a parameter widely used in studies of the near-Earth plasma environment. The scientific use of TEC appeared early in the artificial satellite era, and among its many contributions were fundamental insights into how the ionosphere responds to geomagnetic storms. While many excellent reviews of solar-terrestrial disturbances exist in the literature, none have concentrated on the TEC parameter per se. With new TEC data sets increasingly available from the Global Positioning System (GPS), a comprehensive summary of pre-GPS storm studies is needed to set the base for progress in the GPS era. This review summarizes past case studies, describes statistical occurrence pattern, and identifies responsible mechanisms validated via modeling. It presents a new set of results of TEC disturbance patterns during 180 geomagnetic storms to describe seasonal and solar cycle effects. It concludes with a set of open questions that require additional study.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2005RG000193

Storms in the ionosphere: Patterns and processes for total electron content

The sources of ionospheric forcing are from above (solar and magnetospheric forces), internal (chemistry, local neutral dynamics), and from below (lower atmosphere). In this work we review the observed ion-neutral coupling effects at equatorial and low latitudes during large meteorological events called sudden stratospheric warming (SSW). Research in this direction has been accelerated in recent years mainly due to: (1) extensive observing campaigns, and (2) solar minimum conditions. The former has been instrumental to catch the events before, during, and after the peak SSW temperatures. The latter has permitted a reduced forcing contribution from above and internal. The main ionospheric effects are clearly observed in the zonal electric fields (or vertical E×B drifts), total electron content, and peak electron densities. We include results from different ground- and satellite-based observations, covering different longitudes and years. We also present and discuss the modeling efforts that support most of the observations. Given that SSW can be forecast with a few days in advanced, there is potential for using the connection with the ionosphere for forecasting the occurrence and evolution of electrodynamic perturbations at low latitudes, and sometimes mid latitudes, during arctic winter warmings.

/pdf/equatorial-and-low-latitude-ionospheric-effects-during-4u1lki5jyu.pdf

Equatorial and low latitude ionospheric effects during sudden stratospheric warming events

/pdf/modelling-f2-layer-seasonal-trends-and-day-to-day-gvdj9f2py4.pdf

Modelling F2-layer seasonal trends and day-to-day variability driven by coupling with the lower atmosphere

F-region links with the lower atmosphere?

. A physical model of the coupled thermosphere and ionosphere has been used to determine the accuracy of model predictions of the ionospheric response to geomagnetic activity, and assess our understanding of the physical processes. The physical model is driven by empirical descriptions of the high-latitude electric field and auroral precipitation, as measures of the strength of the magnetospheric sources of energy and momentum to the upper atmosphere. Both sources are keyed to the time-dependent TIROS/NOAA auroral power index. The output of the model is the departure of the ionospheric F region from the normal climatological mean. A 50-day interval towards the end of 1997 has been simulated with the model for two cases. The first simulation uses only the electric fields and auroral forcing from the empirical models, and the second has an additional source of random electric field variability. In both cases, output from the physical model is compared with F-region data from ionosonde stations. Quantitative model/data comparisons have been performed to move beyond the conventional "visual" scientific assessment, in order to determine the value of the predictions for operational use. For this study, the ionosphere at two ionosonde stations has been studied in depth, one each from the northern and southern mid-latitudes. The model clearly captures the seasonal dependence in the ionospheric response to geomagnetic activity at mid-latitude, reproducing the tendency for decreased ion density in the summer hemisphere and increased densities in winter. In contrast to the "visual" success of the model, the detailed quantitative comparisons, which are necessary for space weather applications, are less impressive. The accuracy, or value, of the model has been quantified by evaluating the daily standard deviation, the root-mean-square error, and the correlation coefficient between the data and model predictions. The modeled quiet-time variability, or standard deviation, and the increases during geomagnetic activity, agree well with the data in winter, but is low in summer. The RMS error of the physical model is about the same as the IRI empirical model during quiet times. During the storm events the RMS error of the model improves on IRI, but there are occasionally false-alarms. Using unsmoothed data over the full interval, the correlation coefficients between the model and data are low, between 0.3 and 0.4. Isolating the storm intervals increases the correlation to between 0.43 and 0.56, and by smoothing the data the values increases up to 0.65. The study illustrates the substantial difference between scientific success and a demonstration of value for space weather applications. Key words: Ionosphere (ionospheric disturbances; mid-latitude ionosphere; modeling and forecasting)

/pdf/quantitative-modeling-of-the-ionospheric-response-to-2cstr9ho14.pdf

P. Wilkinson

Papers

Quantitative modeling of the ionospheric response to geomagnetic activity