The Long-Term Evolution of the Atmosphere of Venus: Processes and Feedback Mechanisms

Space Science Reviews - The BepiColombo Environment Radiation Monitor (BERM) on board the European Space Agency’s Mercury Planetary Orbiter (MPO), is designed to measure the radiation...     

Thermal neutrons’ response to the GLEs

Thermal neutrons’ flux near the Earth’s crust is very sensitive regarding different processes and phenomena both in the near-Earth space and in the Earth’s crust by reason of the dual nature of the thermal neutron flux. Its first source is associated with high-energy particles of cosmic rays penetrating into the Earth’s atmosphere and interacting with its elements. The second source originates from the radioactive gases contained in the Earth’s crust. So the contributions of these two sources are specified by the Earth’s crust conditions and its movements, on one hand and variations of high-energy particles flux near the Earth.     

Equatorial vertical E × B drift velocities inferred from ionosonde measurements over Ouagadougou and the IRI-2007 vertical ion drift model

F-region vertical plasma drift velocities were deduced from the hourly hmF2 values acquired from ionogram data over a near dip equatorial station Ouagadougou (12.4°N, 358.5°E, dip angle 5.9°N) in Africa. Our results are compared against the global empirical model of Scherliess and Fejer (1999) incorporated in the IRI model (IRI-2007) for 1600 to 0800 LT from 1 year of data during sunspot maximum year of 1989 (yearly average solar flux intensity, F10.7 = 192) corresponding to the peak phase of solar cycle 22, under magnetically quiet conditions. The drifts are entirely downward between 2000 and 0500 LT bin for both techniques and the root mean square error (RMSE) between the modeled and the ionosonde vertical plasma drifts during these periods is 3.80, 4.37, and 4.74 m/s for June solstice, December solstice and equinox, respectively. Ouagadougou average vertical drifts show evening prereversal enhancement (PRE) velocity peaks (V_ZP) of about 16, 14, and 17 m/s in June solstice, December solstice, and equinox, respectively, at 1900–2000 LT; whereas global empirical model average drifts indicate V_ZP of approximately 33 m/s (June solstice), 29 m/s (December solstice), and 50 m/s (equinox) at 1800 LT. We find very weak and positive correlation (+0.10376) between modeled V_ZP versus F10.7, while ionosonde V_ZP against F10.7 gives worst and opposite correlation (−0.05799). The results also show that modeled V_ZP–Ap indicates good and positive correlation (+0.64289), but ionosonde V_ZP–Ap exhibits poor and negative correlation (−0.22477).     

Performance evaluation of some rain rate conversion models for microwave propagation studies

An important characteristic of rainfall levels at a particular place is the statistical distribution of rainfall rate. In this paper, 5-min integration time rainfall data for the Northcentral region of Nigeria was obtained from the Tropospheric Data Acquisition Network (TRODAN), Anyigba, Nigeria. Also, 1-min integration time rainfall was measured at Minna, Nigeria. In order to obtain the optimal rain rate model suitable for this region, two globally recognised rain rate models were critically evaluated and compared with the 1-min measurements. These are the ITU-R P.837-7 and Lavergnat-Gole (L-G) models. The results obtained showed that the ITU-R P.837-7 and L-G models respectively underestimated the measured rain rate by 7.3 mm/h and 9 mm/h at time percentage exceedance of 0.1%, while they underestimated the measured rain rate by 23.4 mm/h and 13 mm/h respectively at 0.01%. At 0.001%, the measured rain rate was overestimated by the ITU-R P.837-7 and L-G models by 27.4 mm/h and 3 mm/h respectively. Further performance evaluation of the predefined models was carried out using different error metrics such as sum of absolute error (SAE), mean absolute error (MAE), root mean square error (RMSE), standard deviation (STDEV) and Spearman’s rank correlation. The results obtained adjudged the Lavergnat-Gole model as the best rain rate prediction model for this region.