During the West African monsoon season, nocturnal low-level stratiform clouds frequently form over southern West Africa with a cloud base of only few hundred metres above ground . From synoptic observations and various satellite products derived a climatology of low-level clouds over southern West Africa for the monsoon seasons from 2006 to 2011. The affected area covers approximately 800 000 km2. Low-level clouds frequently form shortly after sunset along the coast and upstream of the Mampong Range in Ghana and the Oshogbo Hills in Nigeria and spread during the night . As these clouds persist into the late morning or early afternoon, they reduce surface solar radiation and could strongly affect the regional heat and moisture budgets and, thus, the West African climate .

The mechanisms controlling the formation and maintenance of the low-level clouds were investigated by , using observations at Nangatchori (Benin, 9.70∘ N, 1.68∘ E; 434 m above mean sea level, m.s.l.) and by , who simulated the 2006 monsoon season and analysed atmospheric conditions averaged for clear and cloudy nights. Based on these few studies, current theories relating to low-level cloud formation suggest that these clouds evolve in connection with a nocturnal south-westerly low-level jet (LLJ), which forms regularly in this region and is linked to the Saharan heat low e.g.. The jet axis is several hundred metres above ground, i.e. generally around the same level as the low-level clouds. In the simulations of , the LLJ is on average several m s-1 stronger during cloudy nights than during clear nights. They propose that the relevance of different processes to low-level cloud formation varies depending on the region. While shear-generated turbulent vertical mixing of moisture underneath the LLJ is a main process close to the coast, orographically induced lifting upstream of higher terrain is more important farther inland. In both regions, horizontal cold air advection is strong in and underneath the LLJ layer, and radiative cooling at the cloud top helps to maintain the low-level clouds once they have formed. proposed that vertical mixing of moisture due to shear-generated turbulence underneath the LLJ is the major process for cloud formation far inland at Nangatchori. However, no answers were given to the questions why many nights with an LLJ remain clear and why the LLJ does not form during some nights with low-level clouds.

The existing studies suggest that a lot of effort is still needed to identify controls of the development of the low-level clouds and to improve the understanding of the involved physical processes. In particular, there is a large demand for high-quality observations in this region for process studies and model validation. To meet this demand, a field campaign was conducted in the 2016 monsoon season in southern West Africa within the framework of the Dynamics-aerosol-chemistry-cloud interactions in West Africa (DACCIWA) project . In the regions favourable for low-level clouds , three supersites were installed at Kumasi (Ghana), Savè (Benin) and Ile-Ife (Nigeria).

In preparation for this field campaign, we performed high-resolution simulations with the Consortium for Small-Scale Modeling (COSMO) model for the area around the supersite at Savè (8.00∘ N, 2.43∘ E; 166 m m.s.l.), i.e. about 200 km inland from the Guinea Coast (Fig. ). At this supersite, various remote sensing and in situ systems, including the KITcube mobile observation platform , were operated during the field campaign. This study aims at identifying possible controls of the development of the nocturnal low-level clouds in the simulation. These results were then used to optimise the measurement strategy for the field campaign. Contrary to , who simulated a large part of southern West Africa for the whole monsoon season of 2006, we performed a case study for a smaller domain around the supersite at Savè with a significantly higher horizontal and vertical resolution. This set-up was chosen to resolve the vertical structure of the nocturnal boundary layer and the LLJ as well as small-scale processes possibly relevant to the low-level clouds.

The paper is structured as follows: the next section covers the model set-up, followed by a description of the simulated evolution of low-level clouds in Sect. . In Sect. , we analyse the atmospheric conditions and processes relevant to low-level clouds for different phases of the night. Section  presents a discussion and Sect.  provides a summary and conclusions.

For this study, we use the COSMO model, version 5.1, which is a fully compressible non-hydrostatic regional weather forecast model used for operational weather forecasting as well as for scientific applications down to high resolutions. The model run was performed with a horizontal grid spacing of around 500 m (0.005∘) and a hybrid system with 80 layers up to 22 km with 33 layers below 1.8 km. COSMO model simulations with similar high horizontal resolution have been performed by to study deep moist convection and by to investigate the cloud-topped boundary layer. For comparison, used a horizontal grid spacing of 3 km and 70 vertical layers, of which 20 were below 1.8 km. The horizontal differencing in the COSMO model is done on a latitude–longitude grid using an Arakawa C-grid and a generalised terrain-following height coordinate is implemented in vertical direction. For turbulent diffusion, we use a 3-D turbulence parameterisation based on the extended Smagorinsky model according to and also applied by and . In this parameterisation, turbulence diffusion coefficients depend on horizontal and vertical grid size, stability and turbulent kinetic energy, which is retrieved from a prognostic equation. Due to the high horizontal resolution, the model is convection resolving and therefore convection parameterisation is turned off in this simulation. At lower horizontal resolutions, sub-grid-scale clouds are considered in the radiation scheme after , by applying either a relative humidity criterion or a statistical criterion. However, the consideration of sub-grid-scale clouds is highly uncertain at such high horizontal resolution as chosen in this study and it is not clear whether the criteria are applicable or not . We performed sensitivity tests for the region in West Africa and found that the consideration of sub-grid-scale clouds in the radiation scheme delays the transition from stratiform clouds to convective clouds by several hours, while the impact on the qualitative characteristics of the nocturnal low-level clouds is small. For the simulation analysed in this study, we decided to consider only grid-scale clouds in the radiation scheme, which is called every 15 min. Whether this choice leads to more realistic results or not, could be investigated in upcoming studies using observations from the DACCIWA field campaign. Using an online trajectory module implemented in COSMO , trajectories are started hourly at 7.5∘ N between 1.5 and 2.5∘ E at various levels below 2000 m m.s.l. in order to obtain information on the origin of air parcels, which are involved in the evolution of the low-level clouds.

For initialisation and boundary conditions of the atmospheric part of the model, a convection-resolving simulation with 2.8 km horizontal grid spacing performed with the COSMO model for the northern half of Africa for the whole year of 2006 is used. An advantage of using this simulation is that the lower boundary, particularly the soil moisture, is tuned and long spin-up times are unnecessary. As the 2.8 km simulation is initialised on 1 January 2006 and the model domain is very large (about 2500 × 1800 grid points); the simulated atmospheric conditions on a specific day do not necessarily agree with the observations. However, the overall characteristics of the simulated data are realistic and precipitation statistics match well with Tropical Rainfall Measuring Mission (TRMM) data .

We examine the 2.8 km simulation for periods during the monsoon season when the conditions in the area of interest are characterised by conditions assumed to be favourable for the evolution of low-level clouds . This means we are looking for periods with a south-westerly monsoon flow, a strong nocturnal LLJ and high relative humidity at low levels, which are free of disturbances by large-scale events such as mesoscale convective systems and free of precipitation. Of these periods, we choose a night at the beginning of August for analysis. The simulation is initialised at 12:00 UTC and runs for 30 h with the boundary conditions being updated every hour. For the analysis, we use 15 min model output on z levels and times are given in UTC, the local standard time in Benin being UTC plus 1 h. The model domain ranges from 6.5 to 9∘ N and 1 to 3.5∘ E and contains 501 × 511 grid points (Fig. ). To prevent boundary effects, the analysis is confined to a smaller area with about 100 km distance to the upstream (southern and western) boundaries. In the area used for the analysis, the terrain gradually increases from south to north, with Savè being about 100 km south-west, i.e. upstream, of the Oshogbo Hills, which rise up to 500 m m.s.l. To assess the impact of different terrain heights on the low-level clouds, we investigate two areas of 40 km × 40 km in detail: the SAVE area, which is centred on the location of the supersite at Savè, is characterised by a mean terrain height of 156 m m.s.l., and the HILLS area is directly upstream of the peaks of the Oshogbo Hills with a mean terrain height of 322 m m.s.l.

To obtain information about the spatial distribution and temporal evolution of low-level clouds, we accumulate the liquid water content up to 1200 m m.s.l., i.e. up to the top of the domain-averaged low-level clouds, (Fig. a, b) and average profiles of the liquid water content for both areas SAVE (Fig. c) and HILLS (Fig. d). Throughout the night, the horizontal and vertical extent as well as the liquid water content of the low-level clouds vary, allowing us to distinguish different phases. In the following, we use the term density to distinguish between clouds with low and high liquid water content.

Before about 22:00 UTC, the analysed area is free of low-level clouds (phase 0). First low-level clouds form after around 22:00 UTC in HILLS and after midnight in SAVE (phase 1, Fig. c, d). During this phase, the low-level clouds are denser and more extended over the higher terrain in the north-eastern part of the analysed area (Fig. a). In the other parts of the area, clouds remain rather patchy and less dense. After 03:00 UTC, dense low-level clouds spread towards the south-west, thus, increasing the liquid water content in SAVE (phase 2, Fig. b, c). After around 05:00 UTC, the dense clouds withdraw somewhat to the north-east, causing the averaged liquid water content in SAVE to decrease (Fig. c). During this phase, the clouds in HILLS have a higher density and a larger vertical extent than during phase 1 (Fig. d). Considering the different terrain heights, cloud-base heights above sea level are remarkably similar in both areas (Fig. c, d). With the onset of surface heating, the cloud base rises after 08:00 UTC and convective clouds form.

The differences in the temporal and spatial evolution of clouds in SAVE and HILLS suggest that different processes are relevant in the two areas. To understand the evolution of low-level clouds, we analyse in detail the atmospheric conditions and the processes such as advection, which affect these conditions during the different phases. For this purpose, we calculate tendencies of potential temperature and moisture from the 15 min model output and average them for the SAVE (Fig. ) and HILLS areas (not shown). When using the term moisture, we are referring to specific humidity. To study contributions to the tendencies by advection, we determine horizontal and vertical advection for each grid point and each level and average over the area. Note that parts of the contributions by advection result from inclined isentropes and isohumes over the smoothly sloping terrain. As contributions of sub-grid-scale mixing, divergence of net radiation or phase changes to the tendencies cannot be quantified in the simulation due to unavailable output, residuals result. The residuals are determined by simply subtracting the advection terms from the tendencies (Fig. d, h). Although the residuals are influenced by subtracting the instantaneous advection terms from the tendencies calculated from the 15 min output, the magnitude and sign of the residuals provide some qualitative information: for example, the residual for the heat budget is found to be very large near the surface during phase 0 when a nocturnal inversion evolves due to surface cooling (negative sensible surface heat flux) and in the morning when the convective boundary layer forms due to heating of the surface (positive sensible surface heat flux). During phases 1 and 2, the budgets are dominated by the contributions of the advection terms.

The processes relevant to cloud formation take place on different scales: the increase of relative humidity due to horizontal cold air advection from the coast is related to the monsoon flow and the LLJ, i.e. to large-scale processes. Clouds are triggered by orographically induced lifting, gravity waves and horizontal convergence upstream of existing clouds, which occur on a scale of a few hundred to a few tenths of kilometres. In addition, turbulent sub-grid-scale mixing is important for the upward shift of the LLJ in cloudy areas. The capability of models to resolve any of these processes, of course, depends on the model-grid spacing. This has to be kept in mind when comparing these results to other studies.

The characteristics of the LLJ as well as the temporal evolution and spatial distribution of the low-level clouds are in general agreement with previous studies: the strength and height of the LLJ are comparable to the LLJ characteristics during cloudy nights reported by and , considering that the LLJ and cloud base in our simulation are roughly constant in height above sea level. The low-level clouds in the present simulation first form directly upstream of the Oshogbo Hills due to orographically induced lifting and then spread to the south-west, i.e. to the upstream side. The feature is also visible in satellite images , which supports our hypothesis that enhanced upward motion upstream of existing dense clouds triggers new clouds. We find that this process is most relevant to the evolution of dense extended low-level clouds in SAVE. According to our knowledge, this process has not been reported in any region before. In the simulations of , clouds form upstream of the Oshogbo Hills due to orographically induced lifting and intensify during the night. However, no clear extent to the south-west upstream side can be distinguished. This could be related to the coarser-grid spacing of the model or to different parameterisations. On the one hand, the modification of the horizontal wind field due to the grid-scale clouds is related to model-grid spacing. On the other hand, the upward shift of the layer with maximum static stability and, hence, of the LLJ is at least partly caused by sub-grid-scale turbulent mixing, which depends on the parameterisation in the model. The analysis of the sensitivity of this trigger mechanism to different turbulence parameterisations and grid spacing is beyond the scope of this study, but could be addressed in future studies.

Besides the formation of low-level clouds over land upstream of orography, it is found in simulations and satellite observations that low-level clouds form early along the Guinea Coast and then spread inland. The model-domain size and location in this study do not allow for the study of cloud formation along the coast in detail. Nevertheless, we hypothesise that conditions at the coast and upstream of orography are generally earlier favourable for cloud formation than in other areas over land. In the course of the night, conditions become more favourable in the other areas as well – likely due to horizontal cold air advection and radiative cooling – leading to an extent of low-level clouds from the coast to the north as well as to the south-west upstream of orography.

In this simulation, gravity waves in the LLJ layer generate clouds. To exclude that the gravity waves are caused by numerical effects and enter the domain through the boundaries, we performed another model run with a doubled domain size. The southern boundary for this run is located over the Gulf of Guinea. It is evident that the gravity waves are generated over land within the domain and do not enter through the domain borders and travel through the domain. The gravity waves evolve under stable stratification and significant vertical wind shear; i.e. under conditions in which gravity waves are common features e.g.. Besides vertical wind shear, some of the gravity waves seem to be linked to orographic features, although obstacle heights upstream of SAVE are on the order of 50 m only.

The front, which exists along the coast of southern West Africa and moves inland in the evening, is a regular feature in the 2.8 km simulation. As far as we know, it has not been reported before in this region, which is maybe due to a lack of observations or to lacking analysis of high-resolution simulations. On the other hand, the formation of a sea breeze in this region was documented by satellite images e.g. and investigated using observations in Cotonou and at several stations along the coast of Nigeria . The south-westerly monsoon flow during the wet season often prevents a reversal to offshore flow along the coast of southern West Africa in the evening and may make the sea breeze indistinguishable from the large-scale flow as known from other regions overview by. For this reason, we use the term “front” rather than “sea-breeze front” to describe the boundary between the cool maritime and the warm continental air masses, which evolves along the coast during the day. The temporal characteristics of the front, i.e. its stationarity during the day and its inland penetration in the late afternoon and evening, are highly similar to a study by . They investigated a sea-breeze front on the coast of Mauretania, which is stationary during the day and moves several hundred kilometres inland in the evening, and state that the stationarity results from the balance between horizontal advection of cool maritime air and turbulent mixing in the convective boundary layer. When turbulence decays in the evening, the sea-breeze front moves inland. Other authors report cool sea-breeze surges in northern and south-eastern Australia , which penetrate up to 500 km inland at nights with moderate onshore flow.

A high-resolution COSMO simulation was performed for southern West Africa during the monsoon season in order to identify possible controls of the development of nocturnal low-level clouds. The analysis was made in preparation for the DACCIWA field campaign and focuses on the area around the city of Savè (SAVE area), the location of one of the three supersites. The conditions during the case study are typical of nights with an undisturbed south-westerly monsoon flow prevailing in the area of interest.

Based on the simulation data, we hypothesise that several processes are relevant to cloud formation; some of these are illustrated in Fig. . A sudden increase of relative humidity occurs in the first half of the night. This is related to a front, which forms along the Guinea Coast during the day between the cool maritime and the warm continental air masses and moves inland in the late afternoon and evening. Subsequent cooling mainly due to horizontal advection with the LLJ and vertical advection results in the formation of clouds. Vertical cold air advection is related to orographically induced lifting (process 1 in Fig. ) as well as to gravity waves that form in the stably stratified atmosphere around the level of the LLJ (process 2 in Fig. ). In areas covered by clouds, the height of the LLJ maximum shifts to the top of the clouds, resulting in low-level horizontal convergence and upward motion upstream of the clouds. This triggers new clouds upstream of the existing ones, when saturation is reached (process 3 in Fig. ). Latent heat release due to condensation and radiative cooling at the cloud top likely contribute to cloud evolution as well, but are not the main mechanisms according to the heat and moisture budgets.

The simulation reveals some interesting processes contributing to the evolution of low-level clouds over southern West Africa, which have not been reported before. The results contributed to an optimised measurement strategy for the DACCIWA field campaign, as they emphasise the importance of measuring advection of heat and moisture, turbulence profiles, vertical motion in the LLJ layer to detect gravity waves and profiles of horizontal wind speed with high temporal and vertical resolution to resolve the structure and evolution of the LLJ. For example, wind profiles were measured using radiosondes, sodars and a wind profiler. Research aircrafts were flying inland from the coast detecting horizontal gradients in, e.g., temperature and moisture. A combination of vertical stare and scanning mode was chosen for a Doppler lidar system to allow for detection of inhomogeneities in wind and backscatter in an area of up to 20 km × 20 km, which could provide evidence for the front, as well as for vertical velocity, which can be used as an indicator for gravity waves and to derive turbulence profiles. The observations will now be used to verify and test the hypotheses for cloud formation gained from this study.

Of course, it is difficult to draw any general conclusions with respect to the representativeness of the processes from this case study. Nevertheless, we think that the processes most likely are also effective in other regions and during other periods, as we chose a night with conditions typical of the monsoon season, and two of the relevant processes – gravity waves and triggering of new clouds upstream of existing clouds – are rather independent of local orography. Nevertheless, the sensitivity of cloud formation to factors such as orography, geographic location, variations of the LLJ and humidity distribution, model-grid spacing, model-domain size, turbulence parameterisation and aerosol–cloud interactions, which are believed to have a noticeable impact on cloud formation , was not considered and could be investigated in the framework of the DACCIWA project.

The datasets are available upon request to the corresponding author.