The geomagnetic data obtained from Amber Network station in Cameroon have been used for this study. The variability of H component of geomagnetic field has been examined by using geomagnetic field data of X and Y components recorded at AMBER magnetometer station hosted by the Department of Physics of University of Yaoundé (3.87˚N, 11.52˚E). The day-today variability of the horizontal intensity of the geomagnetic field was examined and shows that the scattering of H component of magnetic field variation is more on disturbed than that on quiet condition. The signatures H of geomagnetic Sq and Sd variations in intensities in the geomagnetic element, has been studied. This study shows that the daytime variations in intensities of geomagnetic elements H, Sq(H) and Sd(H) respectively are generally greater than night-time ones. This paper interests answering the two questions: 1) how can geomagnetic variations be used to study the equatorial ionosphere electrodynamics and electrojet equatorial over Africa in general and Cameroon in particular? 2) How can geomagnetic variations be used to monitor and predict space weather events in Cameroon? This paper presents and interprets the results of H component of geomagnetic field variations during magnetic storms and on quiet days.

This paper presents the earth's magnetic field variations on quiet

This study aims at discussing longitudinal effects on the variability of the vertical E × B drift velocity at low latitudes, specifically over African sector. To this effect, observations from ground-based magnetometers and the Ion Velocity Meter experiment onboard C/NOFS satellite are analyzed in conjunction with equatorial electric field and neutral wind model estimates under geomagnetically quiet conditions in the years 2012-2013. Notwithstanding the limitation in data over Africa, the combination of ground-based and in-situ observations confirmed the existence of longitudinal differences in the E × B between the Atlantic, Western and Eastern African sectors. This was well reproduced by the equatorial electric field model (EEFM) which showed that during noon, the peak of the equatorial electric field (EEF) was the lowest in the Atlantic sector, with an increasing trend towards the Eastern longitude. The Horizontal Wind Model 14 (HWM14) showed that the eastward zonal (poleward meridional) wind velocity was the lowest (highest) in the Eastern sector. Furthermore, the zonal (meridional) wind increased (decreased) from the Eastern to the Atlantic sector. These results highlight the contribution of the neutral wind velocity in driving the longitudinal difference in the vertical How to cite this paper: Honoré, M.E.,

Extreme rainfall events are a serious threat to the well-being of Cameroon's society. The reliability of studies on extreme events such as floods depends on the quality of the data and their distribution in time and space. Although these topics are still incomplete in many countries. This present work focuses on the action of extreme rainfall variability and changes on ground traffic in Cameroon using the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) estimation data in the simulation of precipitation at the intra-seasonal scale. For this, the performance verification of the CFSv2 model was first made on the basis of two mathematical techniques such as the Generalized Relative Operating Characteristics (GROC) score and the Ranked Probability Skill Score (RPSS). Then, based on this calculation of the different performance scores, the analysis and interpretations of the model outputs, the study is carried out on the extreme events (floods) of the first three (03) weeks of August 2021 to understand the impact of extreme rainfall over road transport in Cameroon. The results suggest that the CFSv2 model is the best performance for rainfall simulation at this intra-seasonal scale with CHIRPS satellite estimation data for the first three weeks of August 2021 in Cameroon and is adequate to improve the prevention of accidents and road transport infrastructure caused by extreme events (flooding) to heavy rainfall in Cameroon.