Using daily (monthly) rainfall data from 167 (254) stations across West Africa with at least 80% data availability for the 31‐year period 1980–2010 and the gridded African Rainfall Climatology Version 2 (ARC2) for the period 1983–2010, linear trends in yearly and monthly rainfall totals were investigated. Measures of the Expert Team on Climate Change Detection and Indices (ETCCDI) and two rainy season onset and retreat definitions were employed to assess the corresponding trends in frequency and intensity of daily rainfall and changes to monsoon season length. A rotated Empirical Orthogonal Function analysis yielded two homogeneous rainfall regions, the Sahel and Guinea Coast, in terms of interannual to decadal rainfall variability, and this led to analysis of station data and Standardised Precipitation Index for the two regions. Results show that the majority of stations in the Sahel between the West Coast and 15°E shows a statistically significant positive rainfall trend for annual totals. The August–October period exhibits the largest rainfall recovery in the Sahel and the date of the retreat of the rainy season significantly moved later into the year by 2 days decade⁻¹. The recovery is reflected both in more rainy days associated with longer wet spell duration and more extreme rainfall events. Trends along the Guinea Coast are weak and non‐significant except for extreme rainfall related indices. This missing significance is partly related to the hiatus in rainfall increase in the 1990s, but also to the larger interannual rainfall variability. However, the tendency towards a more intense second rainy season suggests a later withdrawal of rains from the West African subcontinent. ARC2 trends are broadly consistent where ground calibration was undertaken, but are dubious for Nigeria and Ghana, and especially for the Guinea, Jos and Cameroon Line highlands due to missing gauge data.

Synoptic observations and various satellite products have been utilized for computing climatologies of low‐level stratus over southern West Africa for the wet monsoon seasons July–September of 2006–2011. Previous studies found inconsistencies between satellite cloud products; climate models often fail to reproduce the extensive stratus decks. Therefore, a better observational reference and an understanding of its limitations are urgently needed to better validate models. Most detailed information of the spatiotemporal characteristics of low‐level clouds was obtained from two Meteosat Second Generation (MSG) satellite‐based data sets. However, CALIPSO and CloudSat cross sections of cloud occurrence frequency suggest that both MSG products underestimate the low‐level cloudiness over Nigeria due to shielding by abundant upper level and midlevel clouds and reveal that the stratus is lower over the continent than over the ocean. The Terra Multiangle Imaging Spectroradiometer product appears to overestimate the morning extent of low‐level clouds. The climatology presented here shows that the zone of abundant low‐level stratiform clouds is at its diurnal minimum south of 6–7°N around sunset (~1800 UTC). Thereafter, it starts to spread inland and reaches its maximum northward extent of 10–11°N between 0900 and 1000 UTC. The maximum affected area is approximately 800,000 km². After about 1000 UTC, the northern boundary gets fragmented due to the breakup of stratus decks into fair‐weather cumuli. The stratus is most frequent around Cape Palmas, over Ivory Coast, and at the windward sides of the Mampong Range (Ghana) and Oshogbo Hills (Nigeria).

Convective cold pool events in (semi) arid areas have significant impacts on their environment. They reach horizontal extents of up to several hundred kilometers and the associated turbulence and shear can cause dust emissions and threaten aviation safety. Furthermore, cold pools play a major role in the organization of deep convection and in horizontal moisture transport. They have even been proposed to have impacts on larger-scale monsoon dynamics. Cold pools are not well represented in models using a convective parameterization. To test and improve these models, it is necessary to reliably detect cold pool occurrence from standard observational data. Former studies, however, focused on single cases or short time periods. Here, an objective and automated method for the generation of multiyear climatologies of cold-pool events is presented. The algorithm combines standard surface observations with satellite microwave data. Representativeness of stations and influence of their spatial density are addressed by comparison to a satellite-only climatology. Applying this algorithm to data from automatic weather stations and manned synoptic stations in and south of the Atlas Mountains in Morocco and Algeria reveals the frequent occurrence of cold pool events in this region. On the order of six cold-pool events per month are detected from May to September when the Saharan heat low is in its northernmost position. The events tend to cluster into several-days-long convectively active periods, often with strong events on consecutive days. The algorithm is flexible enough to be applied in comparable regions around the world.

An energy budget model is developed to predict water temperature of typical mosquito larval developmental habitats. It assumes a homogeneous mixed water column driven by empirically derived fluxes. The model shows good agreement at both hourly and daily time scales with 10-min temporal resolution observed water temperatures, monitored between June and November 2013 within a peri-urban area of Kumasi, Ghana. There was a close match between larvae development times calculated using either the model-derived or observed water temperatures. The water temperature scheme represents a significant improvement over assuming the water temperature to be equal to air temperature. The energy budget model requires observed minimum and maximum temperatures, information that is generally available from weather stations. Our results show that hourly variations in water temperature are important for the simulation of aquatic-stage development times. By contrast, we found that larval development is insensitive to sub-hourly variations. Modelling suggests that in addition to water temperature, accurate estimation of degree-day development time is very important to correctly predict the larvae development times. The results highlight the potential of the model to predict water temperature of temporary bodies of surface water. Our study represents an important contribution towards the improvement of weatherdriven dynamical disease models, including those designed for malaria early forecasting systems.