Atmospheric shallow convection (SC) is characterised by cumulus clouds that extend between a few hundred meters and a few kilometres. These clouds are more than passive tracers of the air flow in which they are embedded. They play an active role in atmospheric dynamics and the climate system by redistributing moisture, temperature, and momentum in the troposphere.
We focus on two recent field campaigns. 1. EUREC4A took place between January and February 2020 over the North Atlantic trade wind region, which provides perfect conditions for shallow cumuli. This campaign measured clouds and the wind flows on mesoscales. 2. CMTRACE took place in September 2021 around Cabauw, The Netherlands. During CMTRACE, a collocated wind lidar and cloud radar allowed, for the first time, to measure winds from the surface up to 2 km, with a frequency of about 1 minute (∼500 m).
Our results show that CMT crucially influences wind speed and direction throughout the lower troposphere, it also controls cloud organisation and mesoscale circulations. Observations reveal an excessively pronounced diurnal cycle of the winds in the IFS, with too strong winds at night and too weak winds during the day. The role of shallow convection parameterisation (SCP) in kilometre-scale models is explored using the HARMONIE-AROME model. Experiments with inactive SCP produce stronger mesoscale circulations, altering cloud cover and wind profiles.
Finally, the thesis examines novel momentum flux observations from the CMTRACE campaign. These data confirm errors in IFS momentum flux parameterisation, particularly under active convection.
The findings outlined in this thesis hold important implications for advancing our understanding of CMT and its role in atmospheric dynamics

The weather significantly influences daily life, which is predominantly due to short-term weather phenomena occurring in the atmospheric boundary layer (ABL). The HARMONIE-AROME (HARMONIE) model, used by the Royal Netherlands Meteorological Institute (KNMI), simulates the ABL by discretizing the atmosphere into a three-dimensional grid. Processes occurring at scales significantly larger than these grid can be resolved by the model, but processes occurring at scales smaller than the grid (subgrid) are parameterized by theoretical frameworks. At the current horizontal grid resolution of the HARMONIE model, both shallow convection and smaller-scaled diffuse turbulent transport are parameterized by the Eddy-Diffusivity (ED) and the Mass-Flux (MF) scheme, respectively, coupled in the EDMF-framework. In which the MF is described separately for the dry and the moist (cloudy) updraft.
Increasing the model’s resolution promises an increase in atmospheric representation, yet introduces challenges in the so-called Grey zone of turbulence, where the scale of the turbulent motions are in the same order of magnitude as grid size, making
them neither fully resolved nor fully subgrid.
This study aims to investigate the scale-adaptivity of the HARMONIE EDMF-scheme in the Grey zone of turbulence, for the shallow cumulus boundary layer. To this end, high-resolution Large Eddy Simulation (LES) results of two shallow-cumulus cases are coarse-grained to quantify the partitioning of resolved and unresolved turbulence. It is reviewed how well these partitionings scale against the resolution, normalized with height of the dry (h) and the cloudy boundary layer (h+hc), to investigate the potential of scale-adaptivity of the EDMF-scheme with this height. Additionally, the HARMONIE model is run for one of these cases at three EDMF settings: without scale adaptations, with a scale-adaptive scheme based on both h and hc, and with an additional vertical velocity threshold.
In the dry boundary layer, the partitionings of turbulences showed to scale well with the height of the dry boundary layer h, but also implied additional large scaled turbulent transport not carried by strong updrafts. The scaling down of the dry MF in the HARMONIE run showed significant reduction, with increased resolved transport. However, the unresolved partitioning to the total flux still was higher than expected by LES results, which may be explained by these large scaled turbulent transport not accounted for with the mass-flux. In the cloud layer, scaling the resolved and unresolved partitioning of the total turbulence with the height of the cloud h + hc showed not as effective, and indicated that it may not sufficiently represent the strength of convection in the cloud layer. This is supported by the
HARMONIE run, that showed too much decrease of the moist updraft. The addition of the vertical velocity threshold showed a too strong decrease of mass-flux, both in the dry and in the mixed layer. An additional figure from LES results suggest that this threshold was set too low and scale-adaptivity of this threshold may be needed.

Clouds play a crucial role in Earth’s systems, influencing the radiation budget and the hydrological cycle. However, their dynamics are poorly represented in climate models, leading to uncertainties in predicting global temperature changes. To better understand cloud dynamics and improve model parametrizations, the large-scale field campaign EUREC4A focused on studying cloud organization and its potential impact on climate feedback in the North Atlantic trade-wind region, where shallow marine cumulus clouds are prevalent. Within the EUREC4A framework, this study focuses on cloud fields and organization in the HARMONIE weather model to assess the impact of shallow convective parametrizations on its outputs. By comparing three experiments denominated as ’HARMONIE noHGTQS’, HARMONIE noHGTQS noSHAL’ and ’HARMONIE noHGTQS noUVmix’ one can identify discrepancies and determine what the impact of the various shallow convective parametrizations are. Several cloud organization metrics have been computed for the HARMONIE experiments as well as GOES-16 satellite snapshots. The results show that none of the experiments precisely capture the observed diurnal patterns successfully. There exist disparities in cloud cover, cloud quantity, cloud sizes, and the organization index. Removing shallow convective parametrization partly improves the representation of clouds. It exhibits a stronger correlation with the observed cloud cover data from ceilometer measurements and demonstrates a higher capability to replicate the amount of
cloud entities seen in observations in comparison to the other experiments. Furthermore, disabling shallow convection leads to instability and deeper clouds. On the other hand momentum mixing alone has a small impact on clouds, yet it alters wind patterns, resulting in reduced speeds, and little production of precipitation. Overall the model struggles to reproduce detailed cloud patterns such as sugar, mainly due to its coarse resolution. However, it does exhibit a
degree of day-to-day variability in cloud patterns. To gain a deeper understanding on the role of parametrized shallow convection, further investigation into model configurations, momentum mixing dynamics, and hybrid approaches are proposed.

The exchange of energy and mass between the ocean and atmosphere plays a crucial role in shaping oceanic and atmospheric circulation patterns. However, accurately representing these air-sea fluxes remains a challenge for current weather and climate models. Improving the accuracy of bulk flux pa- rameterizations is crucial to improve the quality of weather forecasts and climate predictions, as these parameterizations play a fundamental role in estimating the air-sea fluxes. This study aims to evaluate the performance of the ECUME and ECUME6 parameterizations in simulating air-sea fluxes by utilizing in situ observations obtained from R/V Ron Brown and R/V Meteor, and conducting a comparison with the COARE3.6 parameterization.

To evaluate the ECUME and ECUME6 parameterizations, surface flux diagnostics are established, which illustrate how air-sea fluxes vary with changes in the respective atmospheric variables. By comparing the surface flux diagnostics of the in situ observations with those of the parameterizations, sources of error are identified. The analysis reveals that both ECUME and ECUME6 tend to overestimate the heat fluxes in comparison to EC observations and the COARE3.6 parameterization, with ECUME6 exhibiting a larger overestimation. The degree of overestimation becomes more pronounced as wind speeds increase. Concerning the momentum flux, the parameterizations exhibit an underestimation, with the discrepancy becoming more significant at elevated wind speeds.

By employing an offline model for ECUME and COARE3.6, the iteratively obtained parameters are compared. This analysis demonstrates that the air-sea fluxes derived from the parameterizations strongly depend on the determined neutral transfer coefficients. Addressing these sources of error and refining the parameterization methodology can improve the accuracy of the parameterizations and enhance their applicability for estimating air-sea exchange between the Earth’s surface and the atmosphere.

In the tropics, the character of the trade-winds is decisive for setting convergence and the large-scale circulation. Nevertheless, the vertical transport of momentum by shallow convection (SCMT) and yet its impact on trade- winds has not been investigated in depth yet. With this study, we aim to contribute in understanding the isolated effect SCMT has on the large scale circulations, setting the strength of the circulation and favouring zones of deep convection. Six climate models participated by each conducting three aquaplanet simulations, referring to a simplified climate model in which the entire planet’s surface is covered by ocean, useful for studying fundamental atmosphere-ocean dynamics in the absence of complex land surface interactions. In three distinctive simulations, the models either turn off or exaggerate their SCMT scheme, alternatively by altering an approximate convective momentum scheme. We hypothesized that given the typical tropical wind profile, north-easterly flow at the surface and south-westerly flow aloft, the depth of mixing is determinative for the long-term reaction in setting the circulation. By deeper types if mixing, the scheme will likely bring opposite winds to the surface, affecting both the magnitude and direction of the trade-winds. A first analysis reveals that certain confine the mixing of surface friction to the sub-cloud layer, showing a clear cut-off of induced tendency between the mixed layer and the cloud layer. It is those models that favour a local response only in the shallow overturning circulation, opposite to the models that actively mix momentum between the mix-layer and cloud-layer and show adjustments in the deep overturning circulation. Further building earlier work showing that the horizontal advection of moist static energy (MSE) in the sub-tropics drives tropical convection, we analyzed to what extent enhanced SCMT leads to a change in atmospheric cooling rates by di- or convergence of MSE. Apparent differences by enhanced SCMT are observed in the in cooling rates by advection of MSE between the models that show strong responses in the deep overturning versus the models that do not.

One of the areas of major importance when it comes to weather prediction are clouds, due to their significant impact on the climate and because they are major source of the spread in climate sensitivity in climate models. This paper will focus on the main numerical weather prediction model, HARMONIE, used by the Royal Netherlands Meteorological Institute, with the objective to determine whether this model is able to accurately simulate the meso-scale organization and structures of subtropical low marine clouds.
This is done by comparing various HARMONIE simulation outputs with the observed variables obtained from the Barbados Cloud Observatory. To determine how the different processes within HARMONIE are affecting the simulation outputs, several experimental runs are analyzed. Based on the results it can be
seen that HARMONIE cycle 43 does produce a higher amount of low cloud cover compared to HARMONIE cycle 40. This is expected as HARMONIE cycle 43 does contain the additional height variance which was added in order for the model to produce more low clouds. However, it is overestimating the total low
cloud cover, in contrast to the underestimation by HARMONIE cycle 40. It can be seen that when the additional height variance is removed the simulation of the low cloud cover is significantly improved and is comparable to the observational low cloud cover. Furthermore, when the additional height variance and
shallow convection are both removed the amount of low cloud cover produced by HARMONIE cycle 43 also closely resembles the observed low cloud cover amount. When it comes to cloud fraction in the atmosphere, all of the experimental runs are not able to produce clouds that are present above 3000 m. This result was also obtained from simulation outputs of HARMONIE cycle 40. Besides this, also the specific humidity and potential temperature from the simulation outputs of HARMONIE cycle 43 are not accurately modelled.
All of the experiments seem to have a dry BIAS near the surface and a cold BIAS throughout the whole entirety of the atmosphere. Based on these findings it can be concluded that HARMONIE cycle 43 is able to produce meso-scale subtropical marine clouds, however it does not do this accurately but is overestimating
at all times. Moreover, it can be seen that the additional height variance has significant impact on the cloud production and it is recommended it be removed as the simulation outputs more accurately describe the observational data when it is not present. Furthermore there is no major improvement between cycle 40 and 43 in the cloud formation above 3000m. Both cycles are not able to produce any clouds in the simulation outputs. Based on this new understanding of what is the major source affecting the cloud production in HARMONIE, it is possible to further look into them with the aim to improve the overall weather prediction
of HARMONIE.

Shallow cumulus clouds interact with their environment and redistribute heat, moisture, and momentum (wind speed and direction) in the atmosphere. The same convective plume that forms the cloud is for a large extent responsible for this transport. Modeling the effect of shallow cumulus clouds is challenging because these clouds are smaller than can be directly simulated by models. Weather and climate models therefore rely on empirical functions to represent the effect of sub-grid processes such as the turbulent and convective transport. The transport of moisture and heat through cumulus convection has received a lot of attention from the atmospheric science community. Momentum transport has been studied far less, even though a few studies indicate that momentum transport may have a large influence on local weather as well as the large-scale circulation.

By combining satellite observations and model reanalysis winds, a global data set with higher temporal and spatial resolution ocean surface wind fields can be generated. These superior surface wind fields can have various applications, such as wind forcing of ocean models. The Royal Netherlands Meteorological Institute (KNMI) is responsible for the delivery of two different global data sets of combined surface winds, referred to as IFREMER and ERA5*. IFREMER’s approach focuses on satellite scatterometer observations which are complemented with model reanalysis winds (ERA5). On the other hand, ERA5* is based on ERA5 model reanalysis and corrected with scatterometer observations. The aim of this research is to evaluate global IFREMER and ERA5* surface winds in terms of spatial and temporal characteristics.

In order to validate the surface winds of IFREMER and ERA5*, a reference system of true winds is required. For this, quality-controlled wind observations from an independent Chinese scatterometer Haiyang-2B have been used. This comparison study has been carried out for the year 2019 focusing on zonal wind, meridional wind and wind speed. IFREMER and ERA5* wind fields have been collocated in time and space to HY-2B wind observations using a 6-hour and 1-hour window respectively. This methodology was applied to overcome differences between the data sets in grid definition, wind representation, spatial resolution and temporal resolution.

On a global scale, IFREMER shows larger average and standard deviation of wind differences with respect to HY-2B than ERA5*, specifically in coastal regions and at higher latitudes. The results of this research suggest that the ERA5* wind product generates more accurate surface ocean winds than IFREMER, except for in the tropics, assuming that HY-2B winds represent the true value. Moreover,
at higher wind speeds both global wind products underestimate HY-2B wind, whereby IFREMER already deviates at lower winds than ERA5*. The IFREMER winds showed suspicious satellite tracks and temporal wind inaccuracies, most likely as a result of its 6-hourly resolution. It is recommended that a follow-up investigation is carried out with validation of buoy data in the tropics to investigate the underlying causes of the observed local wind bias.

Climate on Earth is changing rapidly. In order to take the right measures it is important to know with which magnitude and rate the warming of the climate continues in the future. However, climate models currently predict different scenarios. The differing in response of shallow cumulus clouds to a warming climate explains the largest part of the spread of climate sensitivity in these models. It is known that clustered clouds have a different climate feedback than randomly distributed clouds and that we can expect more clustered cloud fields in a warmer climate. It is however unknown how these clouds respond and what the exact difference in climate feedback is. Future research must provide us with more insights and eventually a better understanding of the response of shallow cumulus clouds to warming. However, in order to investigate this an objective measure of the degree of cloud organization is necessary, something that is currently lacking. In this thesis a dimensionless combined organization measure is introduced that can be applied to a large range of cloud field organizations on different field sizes. This is a combined measure, as it makes use of the existing organization index I_org and the size of clouds and clear sky areas in the cloud field. A different approach on calculating I_org was introduced taking into account the sizes of the clouds, resulting in an useful and more realistic values from this parameter. The results of the combined organization measure were compared to a visual inspection of 557 cloud fields with dimensions of 10x10 degree, which showed promising results. Sub-fields of 5x5 degree and 2.5x2.5 degree were also analysed, which showed that the combined organization measure could often be applied on smaller scales as well but yielded some problems when areas contained either no or little clouds or some very large ones. It was concluded that the newly developed method is an improvement of the already existing method, providing scientists with a better and more reliable index to quantify the degree of cloud organization.

In this study we are specifically interested in the role of convective momentum transport in a commercial fine-scale LES model that is used for wind predictions in the wind-energy sector. With this model, forced with the ECMWF IFS, a year-long of daily forecasts are run over Cabauw, the Netherlands, at a resolution of 40m in the horizontal and a resolution in the vertical of 8m that decreases with height to 80m. At this location atmospheric conditions range from stable to convective boundary layers, from clear sky to overcast days. The number of days with cumulus convection are surprisingly large: 144 out of 365 days.

Focusing on daytime hours, we separate days with and without cumulus convection, and with small and large cloudiness. For these different categories we show how the normalised momentum flux, and what this implies for drag in the lowest kilometre of the atmosphere. Here we are mindful of differences in background winds between the categories. A similar exercise is performed by separating cumulus days on surface buoyancy flux and cloud depth; four groups of increasing convection have been obtained.

It is found that in the presence of cumulus convection, the momentum transport is less linear than on overcast days. Clear-sky days show more drag in the lower half of the mixed layer compared to the cumulus case. Near cloud base, the drag is similar to that of cumulus days.

Separating cumulus days on convection we found that with decreasing buoyancy flux, the normalised momentum transport behaves less linear: in general cumulus days with the largest convection showed linear behaviour in the sub-cloud layer, cumulus days with the lowest convection showed a profile that tends to increase the wind speed near the surface and shows drag near cloud base.

Finally, using sensitivity experiments in which we remove the latent heating effect on buoyancy, we that the presence of moist convection specifically, change momentum mixing near and above cloud base, but not in the sub-cloud layer underneath.