Mesoscale convective systems (MCSs) are frequently observed over southern West Africa (SWA) throughout most of the year. These MCS events are the dominant rain-bearing systems, contributing over 50 % of annual rainfall over SWA. However, it has not yet been identified what variations in typical large-scale environments of the seasonal cycle of the West African monsoon may favour MCS occurrence in this region. Here, nine distinct synoptic states are identified and are further associated with being a synoptic-circulation type of either a dry, transition, or monsoon season using self-organizing maps (SOMs) with inputs from reanalysis data. We identified a pronounced annual cycle of MCS numbers with frequency peaks in April and October that can be associated with the start of rainfall during the major rainy season and the maximum rainfall for the minor rainy season across SWA, respectively. Comparing daily MCS frequencies, MCSs are most likely to develop during transition conditions featuring a northward-displaced moisture anomaly (2.8 MCSs per day), which can be linked to strengthened low-level westerlies. Considering that these transition conditions occur predominantly during the pre- and post-monsoon period, these patterns may in some cases be representative of monsoon onset conditions or a delayed monsoon retreat. On the other hand, under monsoon conditions, we observe weakened low-level south-westerlies during MCS days, which reduce moisture content over the Sahel but introduce more moisture over the coast. Finally, we find a majority of MCS-day synoptic states exhibiting positive zonal wind shear anomalies. Seasons with the strongest zonal wind shear anomalies are associated with the strongest low-level temperature anomalies to the north of SWA, highlighting that a warmer Sahel can promote MCS-favourable conditions in SWA. Overall, the SOM-identified synoptic states converge towards high-moisture and high-shear conditions on MCS days in SWA, where the frequency at which these conditions occur depends on the synoptic state.

A simple analytical approach has been developed to determine the series resistance, R_s, of a solar cell. The method adopted here depends only on the knowledge of the open-circuit voltage, V_oc, and the current and voltage at the maximum power point, I_sc and V_mp respectively. This approach, based on a knowledge of these operating output parameters of the cell, provides a theoretical framework for an existing computer simulated approach which has been widely used in industries.

We analyze long-term extreme events in daily precipitation for the period of 1950–2005 and future projections from 2006 to 2100 based on representative concentration pathways (RCP8.5) over West Africa, including twelve major cities of the subregion. The study uses two datasets from the Coordinated Regional Downscaling Experiments (CORDEX) and NASA Earth eXchange Global Daily Downscaled Projections (NEX–GDDP), for their potential to simulate extreme rainfall characteristics over West Africa. CORDEX datasets are dynamically downscaled from 9 General Circulation Model (GCM) and the NEX-GDDP is statistically downscaled from 21 GCM simulations from CMIP5. The ensemble members of each dataset were used for the analysis and evaluated with eight observations. The projected changes in the rainfall indices were analyzed at four Global Warming Levels (GWLs) under the RCP8.5 climate-forcing scenario. The projections from the CORDEX and NEX-GDDP ensembles were compared. Self-Organizing Map (SOM) analysis was used to classify the projected changes from the simulations into twelve groups, based on their characteristics. Both CORDEX and NEX-GDDP models perform well in simulating the frequency and intensities of daily rainfall characteristics for important parts of the domain. However, substantial differences exist between the models and their relative performance varies with the indices. In all cases, NEX-GDDP outperforms CORDEX in stimulating the extreme indices. On the projections, CORDEX showed a wider spread than the NEX–GDDP for RTOT and vice versa for R97.5pTOT for all the GWLs.

Transparent conducting oxide material, ZnO nanoparticles has been synthesized using inexpensive and eco-friendly synthesis procedures with less or environmental pollutants and no liquid waste products. The effect of the temperatures on the structural properties for the synthesized ZnO nanocrystals has been investigated. In this study, we report an easy, low-cost, re-producible method for synthesizing ZnO nanoparticles by means of the liquid phase method. The ZnO nanocrystals were synthesized using the wet chemical route and the effect of temperature variation on the structural properties of investigated synthesized using powder x-ray diffractogram (XRD). The temperatures for the synthesis were varied from 120 °C to 200 °C in steps of 20 °C. The results show that, during the first stage of the synthesis of ZnO (at 120 °C), the XRD diffraction pattern confirms the cubic structure of zinc peroxide and the XRD pattern of the samples obtained at temperatures of 140 °C, 160 °C, 180 °C and 200 °C were confirmed to be hexagonal (wurtzite) crystal structure of ZnO. The XRD diffraction patterns of the 140 °C and 160 °C samples show some impurity phases which were associated with the zinc acetate by-product which is a colloid complex of water and methyl succinate and were removed by evaporation as temperatures were increased to 180 °C and 200 °C respectively. As temperature increases, the peak of the diffractograms of the sample becomes sharper and narrow indicating a decrease in width. A shift in peak positions to higher angles was observed and the positional parameter, bond angle, β, average crystallite size, APF, number of unit cells and density generally increase with temperature. However, the lattice parameters ‘a’ and ‘c’, bond lengths b and b1, bond angle, α, dislocation density, strain and unit cell volume were found to generally decrease with temperature.

Clouds play a crucial role in Earth’s climate system by modulating radiation fluxes via reflection and scattering, and thus the slightest variation in their spatial coverage significantly alters the climate response. Until now, due to the sparse distribution of advanced observation stations, large uncertainties in cloud climatology remain for many regions. Therefore, this paper estimates total cloud cover (TCC) by using sunshine duration measured in different tropical climates in Ghana. We used regression tests for each climate zone, coupled with bias correction by cumulative distribution function (CDF) matching, to develop the estimated TCC dataset from nonlinear empirical equations. It was found that the estimated percentage TCC, 20.8–84.7 ± 3.5%, compared well with station-observed TCC, 21.9–84.4 ± 3.5%, with root mean square errors of 1.08–9.13 ± 1.8% and correlation coefficients of 0.87–0.99 ± 0.03. Overall, spatiotemporal characteristics were preserved, establishing that denser clouds tended to prevail mostly over the southern half of the forest-type climate during the June–September period. Moreover, the model and the observations show a non-normality, indicating a prevalence of above-average TCC over the study area. The results are useful for weather prediction and application in meteorology.

Stratospheric Aerosol Injection (SAI), a proposed climate intervention, aims to reduce the amount of solar radiation reaching the Earth’s surface by increasing the reflectivity of the atmosphere, thereby offsetting the warming effect of greenhouse gases. During the Harmattan season (December–February) in West Africa (WA), a natural meteorological phenomenon injects dust and sand particles into the atmosphere, leading to a cooling effect. In this study, we investigate the influence of SAI on West African surface temperature, dust, and other meteorological variables using the Whole Atmosphere Community Climate Model under the Shared Socioeconomic Pathway 2-4.5 scenario and the Assessing Responses and Impacts of Solar Climate Intervention on the Earth system with SAI (ARISE-SAI) dataset. Our findings indicate that SAI intervention significantly impacts the projected surface temperatures, specific humidity, and wind speed changes during the Harmattan season. Compared to a future without SAI, the intervention shows a significant net cooling effect over most parts of WA during the mid-future period (2050–2069). Also, SAI intervention significantly decreases moisture content over southern and northern WA in the near-future (2035–2054), mainly due to the net cooling effects over WA, when compared to a future without SAI. This feature is enhanced in the mid-future period. The cooling effects of SAI are likely to reduce the air’s capacity to hold moisture, leading to lower specific humidity levels relative to a future without SAI. It could also have negative implications, such as increased aridity compared to a future without SAI in the northern and central regions of WA. These findings also highlight the potential for SAI to improve air quality in certain areas but also underscore the need for careful consideration of implementation strategies and possible trade-offs. The changes from SAI observed are specific to the ARISE simulation and may differ from other SAI simulations.