[1] Accurate ionospheric specification is necessary for improving human activities such as radar detection, navigation, and Earth observation. This is of particular importance in Africa, where strong plasma density gradients exist due to the equatorial ionization anomaly. In this paper the accuracy of three-dimensional ionospheric images is assessed over a 2 week test period (2-16 December 2012). These images are produced using differential Global Positioning System (GPS) slant total electron content observations and a time-dependent tomography algorithm. The test period is selected to coincide with a period of increased GPS data availability from the African Geodetic Reference Frame (AFREF) project. A simulation approach that includes the addition of realistic errors is employed in order to provide a ground truth. Results show that the inclusion of observations from the AFREF archive significantly reduces ionospheric specification errors across the African sector, especially in regions that are poorly served by the permanent network of GPS receivers. The permanent network could be improved by adding extra sites and by reducing the number of service outages that affect the existing sites.
The near-Earth cosmic ray flux has been monitored for more than 70 years by a network of ground-based neutron monitors (NMs). With the ever-increasing importance of quantifying the radiation risk and effects of cosmic rays for, e.g., air and space-travel, it is essential to continue operating the existing NM stations, while expanding this crucial network. In this paper, we discuss a smaller and cost-effective version of the traditional NM, the mini-NM. These monitors can be deployed with ease, even to extremely remote locations, where they operate in a semi-autonomous fashion. We believe that the mini-NM, therefore, offers the opportunity to increase the sensitivity and expand the coverage of the existing NM network, making this network more suitable to near-real-time monitoring for space weather applications. In this paper, we present the technical details of the mini-NM's design and operation, and present a summary of the initial tests and science results.
Abstract. Daytime twin-peak structures, also known as biteout or diurnal double-maxima structures, are ionospheric phenomena in which the diurnal ionospheric trend shows two peaks (instead of the normal one) during the daytime. This study reports on first simultaneous observations of these structures in the Global Positioning System and ionosonde measurements from the southern African and European middle-latitude stations during a mostly quiet geomagnetic condition period of 8-13 April 2012, which indicates that their occurrence and therefore driving mechanism(s) may not be localised. It is found that the daytime twin-peak structures generally appear later in the Northern Hemisphere with a 1-3 h latency although they propagate mostly equatorward in both hemispheres. Proxies of meridional neutral winds were calculated from available manually scaled ionosonde measurements and used to explore their potential as drivers of the structures. Bite-out events were linked to downward drifts of the vertical component of equivalent neutral winds causing plasma depletions. In addition, evidence of sporadic E layers at the same time as enhancements of daytime twin-peak structures suggests that the tides had influence via the meridional wind shear in generating these structures through the dynamo electric field which resulted in upward E × B drifts.
The work presented here aims to evaluate the capabilities of Multi‐Instrument Data Analysis System (MIDAS) compared with artificial neural networks (ANNs) to reconstruct storm‐time total electron content (TEC) over the African low‐latitude and midlatitude regions. For MIDAS, the inversion was done based on the Global Positioning System (GPS) measurements from receiver stations extending from −30∘ to 36∘ in latitude and 30∘ to 44∘ in longitude while for ANNs, individual storm‐time models based on historical GPS data from receivers within the same region covered by MIDAS were used. Based on the minimum Dst index reached during the storm period, moderate (−50 nT ≥Dst> −100 nT), strong (−100 nT ≥Dst>1em−200 nT), and severe (−200 nT ≥Dst>1em−350 nT) storms were used for validation. MIDAS and ANNs results were compared with IRI‐2016 predictions and validated with real GPS TEC observations. A statistical analysis revealed that MIDAS and ANNs provide comparable results in storm‐time TEC reconstruction with average mean absolute errors of 4.81 and 4.18 TECU respectively. However, MIDAS performed better compared to ANNs in following TEC enhancements and depletions as well as short‐term features observed during the selected storm periods. In terms of latitude, it was found that on average, MIDAS performs 13% better than ANNs in the African midlatitude, while ANN model performs 24% better than MIDAS in low latitudes. Furthermore, comparisons with IRI predictions showed that both MIDAS and ANNs produce more accurate estimations of the storm‐time TEC than IRI model.
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