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.

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.