Abstract. Measurements of equatorial thermospheric winds, temperatures, and 630 nm relative intensities were obtained using an imaging Fabry–Perot interferometer (FPI), which was recently deployed at Bahir Dar University in Ethiopia (11.6° N, 37.4° E, 3.7° N magnetic). The results obtained in this study cover 6 months (53 nights of useable data) between November 2015 and April 2016. The monthly-averaged values, which include local winter and equinox seasons, show the magnitude of the maximum monthly-averaged zonal wind is typically within the range of 70 to 90 ms−1 and is eastward between 19:00 and 21:00 LT. Compared to prior studies of the equatorial thermospheric wind for this local time period, the magnitude is considerably weaker as compared to the maximum zonal wind speed observed in the Peruvian sector but comparable to Brazilian FPI results. During the early evening, the meridional wind speeds are 30 to 50 ms−1 poleward during the winter months and 10 to 25 ms−1 equatorward in the equinox months. The direction of the poleward wind during the winter months is believed to be mainly caused by the existence of the interhemispheric wind flow from the summer to winter hemispheres. An equatorial wind surge is observed later in the evening and is shifted to later local times during the winter months and to earlier local times during the equinox months. Significant night-to-night variations are also observed in the maximum speed of both zonal and meridional winds. The temperature observations show the midnight temperature maximum (MTM) to be generally present between 00:30 and 02:00 LT. The amplitude of the MTM was  ∼  110 K in January 2016 with values smaller than this in the other months. The local time difference between the appearance of the MTM and a pre-midnight equatorial wind was generally 60 to 180 min. A meridional wind reversal was also observed after the appearance of the MTM (after 02:00 LT). Climatological models, HWM14 and MSIS-00, were compared to the observations and the HWM14 model generally predicted the zonal wind observations well with the exception of higher model values by 25 ms−1 in the winter months. The HWM14 model meridional wind showed generally good agreement with the observations. Finally, the MSIS-00 model overestimated the temperature by 50 to 75 K during the early evening hours of local winter months. Otherwise, the agreement was generally good, although, in line with prior studies, the model failed to reproduce the MTM peak for any of the 6 months compared with the FPI data.

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[1] NeQuick 2 ionospheric empirical model depends on global ionospheric coefficients that are estimated from unevenly distributed ionosonde measurements. In regions, like Africa, where very few observational data were available until recently, the model estimated the ionospheric peak parameters by interpolation. When one wants to employ the model to specify the ionosphere where very few data have been used for model development, the performances of the model need careful validation. This study investigates the performances of NeQuick 2 in the East African region by assisting the model with measurements from a single Global Positioning System (GPS) receiver, which has been deployed recently. This can be done by first calculating an effective ionization level that drives NeQuick 2 to compute slant total electron content (sTEC) which fits, in the least square sense, with the measurements taken from a single GPS receiver. We then quantify the performances of NeQuick 2 in reproducing the measured TEC by running the model at four other locations, where GPS stations are available, using the same effective ionization level that we calculated from a single GPS station as a driver of the model. Finally, the performances of the model before and after data ingestion have been investigated by comparing the model results with the experimental sTEC and vertical TEC (vTEC) obtained from the four test stations. Three months data during low solar activity conditions have been used for this study. We have shown that the capability of NeQuick 2, in describing the East African region of the ionosphere, can be improved substantially by data ingestion. We found that the model after ingestion reproduces the experimental TEC better as far as about 620 km away from the reference station than that before adaptation. The statistical comparisons of the performances of the model in reproducing sTEC before and after ingestion are also discussed in this study.Citation: Nigussie, M., S. M. Radicella, B. Damtie, B. Nava, E. Yizengaw, and L. Ciraolo (2012), TEC ingestion into NeQuick 2 to model the East African equatorial ionosphere, Radio Sci., 47, RS5002,

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