Agricultural businesses in Ghana heavily depend on rain-fed farming, but they are facing increasing challenges due to climate change and population growth. Accurate weather forecasts providing useful information on the onset of the rainy season are therefore of utmost importance. Unfortunately, the country still lacks reliable weather information and precise forecasts. This study aims to enhance and expand weather forecasting research in Ghana by running the regional Weather Research and Forecasting (WRF) model over Ghana and verifying its performance in forecasting the local onset of West Africa’s annual rainy season. Three experimental setups were conducted. The first experimental setup tested four different planetary boundary layer (PBL) schemes. Results showed that the schemes performed differently across the various agro-ecological zones of Ghana, highlighting the influence of spatial context on the model’s performance and the choice of PBL scheme. Further analysis within a smaller domain in the Forest zone revealed promising insights into accurately capturing categorized precipitation. In the third and final experiment, the WRF model was compared to the ECMWF’s operational forecast, demonstrating WRF’s capability of detecting local variations in rainfall, including heavier precipitation amounts, which the ECMWF model was not capable of detecting. This comparison underscored the added value of the WRF model over global models. Whether the WRF model can serve as an accurate weather prediction model to forecast the local onset of the rainy season in Ghana depends not only on its performance but also on the chosen definition of the onset. However, the results highlighted its qualities and robustness for multiple definitions, indicating a high potential for this purpose.

In the atmospheric boundary layer, when surface heat flux is small and mean wind shear is strong, horizontal convective rolls that are elongated along the wind shear are formed. This study attempts to explain the asymmetry of rolls in terms of turbulence using large-eddy simulations. A pressure gradient in the north-south y direction is applied, which results in an east-west geostrophic wind. It is shown that the turbulent kinetic energy components in the x and y directions are not equal when rolls develop. In addition, a countergradient regime is present for vertical momentum flux in the y direction in convective boundary layer with rolls. In the countergradient regime, the wind variance in the y direction is destroyed, contrary to being produced in the x direction. The presence of a countergradient regime for v'w' but not u'w' suggests that the eddy viscosity in the x and y directions would be rather different, and even become negative for v'w'. Thus, the existing parameterization scheme in global atmospheric models may need to be modified. However, the design of an improved parameterization scheme is non-trivial as the countergradient regime is non-stationary when stability decreases, while it does not exist in neutral or stable boundary layers with rolls.

Oceans play a vital role in the regulation of Earth's intricate climate system. The majority of gas and energy exchanges occurring at the ocean-atmosphere interface are driven by small-scale, O(1 km), coupled processes. Despite its importance, too few observations have been able to capture the ocean-atmosphere coupling at scales smaller than O(10 km). This has led to poor parameterisation in climate models. In an effort to enhance our understanding of the ocean-atmosphere coupling, this study aims to test and improve upon two separate Marine Atmospheric Boundary Layer (MABL) characterisation methodologies (called algorithm 2A and algorithm 2B) put forward by Young et al., (2000). Algorithms 2A and 2B relate processed Synthetic Aperture Radar (SAR) image properties to a specific atmospheric state through use of surface-layer similarity theory and a combination of surface-layer and mixed-layer similarity theory respectively. Results of both methods indicate significant inherent limitations. Algorithm 2A's utility is curbed by uncertainty introduced during the estimation of Convective Boundary Layer depth Zi and spectral power-law extrapolation. Algorithm 2B suffers from uncertainty introduced by the dimensionless energy dissipation rate psi. As a result of these (and other) uncertainties, the estimated atmospheric instability can be off by a factor 2 or more. Further analyses suggest shortcomings in the applicability of the Geophysical Model Function (GMF). It is hypothesised that both employed GMFs underestimate the horizontal wind-field variance at scales relevant to turbulent convection, which subsequently manifests itself as (part of) the observed average 50% overestimation of absolute Obukhov length and subsequent 33% underestimation of the atmospheric instability. Additional research is required to support and quantify the GMF-induced underestimation hypothesis. Inspired by algorithm 2B, a third method (algorithm 2C) is developed which circumvents major uncertainties inherent to both algorithm 2A and 2B. However, due to limitations of its own, algorithm 2C is incapable of replacing algorithms 2A or 2B for a large range of atmospheric instabilities. If improved upon and successfully employed, spaceborne characterisation of the MABL could benefit climate studies by providing a wealth of continuous and global atmospheric-state measurements on scales previously unavailable.

In the context of climate modelling, convective clouds in tropical regions play a major role in determining the climate sensitivity. The vertical transport of mass and energy associated with this type of clouds is often represented with so called mass-flux parameterization schemes. In this work the aim is to evaluate the relationship between mass-flux and large scale environmental conditions using observations in a tropical region, over a period of 13 wet seasons. A uniquely comprehensive data set from the C-band polarimetric radar (CPOL) in Darwin, Australia, is used to estimate vertical velocity inside precipitating convective clouds. Ultimately, mass-flux is derived over a domain size similar to that of a general circulation model (GCM) grid box. Five parameters (RH_500, CAPE, CIN, ­Omega_500 and Chi_crit) are selected to describe environmental conditions and with these, the magnitude and shape of mass-flux is analysed. Chi_crit appears to be the most valid parameter to represent both the shape and magnitude of mass-flux. All other selected parameters strongly influence only one of the two aspects of the profile. Additionally, fractional entrainment is retrieved from mass-flux profiles and partitioned into two terms: one dependent on area fraction and the other on vertical velocity. Under all environmental conditions, the layer between 4.5 and 7 km experiences detrainment. It can be inferred that a stable layer, known as the freezing level, is present at 4.5 km. Below the freezing level, the vertical velocity and the mass-flux shape are most relevant to determine entrainment rates leading to the conclusion that the vertical velocity should not be disregarded when parameterizing convection.

Wind is an important indicator of circulation related processes in the atmosphere. Accurate wind in- formation is used as an input for weather and circulation models. Wind data with a high temporal and spatial resolution are useful for research on the microphysics of the atmosphere, which is the area of application for the three-beam Transportable Atmospheric Radar (TARA) located at Cabauw Ex- perimental Site for Atmospheric Research (CESAR) in the Netherlands. Although some comparisons were performed using radiosondes, no thorough quality assessment of the wind estimation results has been done so far. During this research, the quality assessment is performed for the estimation of the wind speed and direction during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) campaign, which took place in October and November 2014. This research shows that the wind estimation is working well during precipitation and a TARA-based criteria for the data selection to guarantee the quality of the wind retrievals is identified in the form of the coefficient of variation for the mean Doppler velocities.
The quality assessment of the results of the TARA wind estimation is done by comparing the wind retrievals to the measurements of the meteorological tower at a height of 200 m above the surface at minute resolution. For the assessment to be performed, an effective way of removing clear air measurements is needed, which is done for the whole ACCEPT-campaign using a rough selection of time steps including rain. This approach showed that the wind estimation is working well during precipitation and shows that an improved data selection is needed.
Several approaches towards improving the data selection for the wind estimation of TARA are per- formed. The most successful is the use of the coefficient of variation, which is defined as the standard deviation divided by the mean. This coefficient is calculated for the mean Doppler velocities, which are the input for the wind estimation algorithm. Comparing the results of the coefficient of variation method to the one based on rain selection shows that both return good results. This leads to the conclusion that the coefficient of variation is useful to improve the data selection.