Land cover controls the land-atmosphere exchange of water and energy through the partitioning of solar energy into latent and sensible heat. Observations over all land cover types at the regional scale are required to study these turbulent flux dynamics over a landscape. Here, we aim to study how the control of daily and midday latent and sensible heat fluxes over different land cover types is distributed along three axes: energy availability, water availability and exchange efficiency. To this end, observations from 19 eddy covariance flux tower sites in the Netherlands, covering six different land cover types located within the same climatic zone, were used in a regression analysis to explain the observed dynamics and find the principle drivers. The resulting relative position of these sites along the three axes suggests that land cover partly explains the variance of daily and midday turbulent fluxes. We found that evaporation dynamics from grassland, peatland swamp and cropland sites could mostly be explained by energy availability. Forest evaporation can mainly be explained by water availability, urban evaporation by water availability and exchange efficiency, and open water evaporation can almost entirely be explained by exchange efficiency. We found that the sensible heat flux is less sensitive to land cover type. This demonstrates that the land-atmosphere interface plays an active role in the shedding of sensible heat. Our results contribute to a better understanding of the dynamics of evaporation over different land cover types and may help to optimize, and potentially simplify, models to predict evaporation.

This study investigates how wind shear and momentum fluxes in the surface- and boundary layer vary across wind and cloud regimes. We use a 9-year-long data set from the Cabauw observatory complemented by (8.2 × 8.2 (Formula presented.)) daily Large Eddy Simulation (LES) hindcasts. An automated algorithm classifies observed and simulated days into different cloud regimes: (a) clear-sky days, (b) days with shallow convective clouds rooted in the surface layer, with two ranges of cloud cover, and (c) non-convective cloud days. Categorized days in observations and LES do not always match, particularly the number of non-convective cloud days are underestimated in the LES, which likes to develop convection. However, the climatology and diurnal cycle of winds for each regime are very similar in LES and observations, strengthening our confidence in LES’ skill to reproduce certain clouds for certain atmospheric states. Along-wind momentum flux profiles are similar across all regimes, but large cloud cover (convective and non-convective) days have larger total momentum flux distributed over a deeper layer, with up to 30% of the surface flux still present near cloud base. The clear-sky and especially shallow cumulus regime with low cloud cover have notably larger crosswind momentum fluxes in the boundary layer. Surface-layer wind shear at daytime is smallest in the shallow cumulus regimes, having deeper boundary layers and a steady increase in surface layer wind speed during daytime. Compared to clear-sky days at a similar stability, convective cloud regimes have smaller surface-layer wind shear and larger surface friction than estimated by Monin-Obukhov Similarity Theory.

The reduction in visibility that accompanies fog events presents a hazard to human safety and navigation. However, accurate fog prediction remains elusive, with numerical methods often unable to capture the conditions of fog formation, and observational methods having high false-alarm rates in order to obtain high hit rates of prediction. In this work, 5 years of observations from the Cabauw Experimental Site for Atmospheric Research are used to further investigate how false alarms may be reduced using the statistical method for diagnosing radiation-fog events from observations developed by Menut et al. (Boundary-Layer Meteorol 150:277–297, 2014). The method is assessed for forecast lead times of 1–6 h and implementing four optimization schemes to tune the prediction for different needs, compromising between confidence and risk. Prediction scores improve significantly with decreased lead time, with the possibility of achieving a hit rate of over 90% and a false-alarm rate of just 13%. In total, a further 31 combinations of predictive variables beyond the original combination are explored (including mostly, e.g., variables related to moisture and static stability of the boundary layer). Little change to the prediction scores indicates any appropriate combination of variables that measure saturation, turbulence, and near-surface cooling can be used. The remaining false-alarm periods are manually assessed, identifying the lack of spatio–temporal information (such as the temporal evolution of the local conditions and the advective history of the airmass) as the ultimate limiting factor in the methodology’s predictive capabilities. Future observational studies are recommended that investigate the near-surface evolution of fog and the role of non-local heterogeneity on fog formation.

A conceptual model is used in combination with observational analysis to understand regime transitions of near-surface temperature inversions at night as well as in Arctic conditions. The model combines a surface energy budget with a bulk parameterization for turbulent heat transport. Energy fluxes or feedbacks due to soil and radiative heat transfer are accounted for by a "lumped parameter closure," which represents the "coupling strength" of the system. Observations from Cabauw, Netherlands, and Dome C, Antarctica, are analyzed. As expected, inversions are weak for strong winds, whereas large inversions are found under weak-wind conditions. However, a sharp transition is found between those regimes, as it occurs within a narrow wind range. This results in a typical S-shaped dependency. The conceptual model explains why this characteristic must be a robust feature. Differences between the Cabauw and Dome C cases are explained from differences in coupling strength (being weaker in the Antarctic). For comparison, a realistic column model is run. As findings are similar to the simple model and the observational analysis, it suggests generality of the results. Theoretical analysis reveals that, in the transition zone near the critical wind speed, the response time of the system to perturbations becomes large. As resilience to perturbations becomes weaker, it may explain why, within this wind regime, an increase of scatter is found. Finally, the so-called heat flux duality paradox is analyzed. It is explained why numerical simulations with prescribed surface fluxes show a dynamical response different from more realistic surface-coupled systems.

Geostrophic wind speed data, derived from pressure observations, are used in combination with tower measurements to investigate the nocturnal stable boundary layer at Cabauw, the Netherlands. Since the geostrophic wind speed is not directly influenced by local nocturnal stability, it may be regarded as an external forcing parameter of the nocturnal stable boundary layer. This is in contrast to local parameters such as in situ wind speed, the Monin-Obukhov stability parameter (z/L), or the local Richardson number. To characterize the stable boundary layer, ensemble averages of clear-sky nights with similar geostrophic wind speeds are formed. In this manner, the mean dynamical behavior of near-surface turbulent characteristics and composite profiles of wind and temperature are systematically investigated. The classification is found to result in a gradual ordering of the diagnosed variables in terms of the geostrophic wind speed. In an ensemble sense the transition from the weakly stable to very stable boundary layer is more gradual than expected. Interestingly, for very weak geostrophic winds, turbulent activity is found to be negligibly small while the resulting boundary cooling stays finite. Realistic numerical simulations for those cases should therefore have a comprehensive description of other thermodynamic processes such as soil heat conduction and radiative transfer.

The performance of an atmospheric single-column model (SCM) is studied systematically for stably-stratified conditions. To this end, 11 years (2005–2015) of daily SCM simulations were compared to observations from the Cabauw observatory, The Netherlands. Each individual clear-sky night was classified in terms of the ambient geostrophic wind speed with a (Formula presented.) bin-width. Nights with overcast conditions were filtered out by selecting only those nights with an average net radiation of less than (Formula presented.). A similar procedure was applied to the observational dataset. A comparison of observed and modelled ensemble-averaged profiles of wind speed and potential temperature and time series of turbulent fluxes showed that the model represents the dynamics of the nocturnal boundary layer (NBL) at Cabauw very well for a broad range of mechanical forcing conditions. No obvious difference in model performance was found between near-neutral and strongly-stratified conditions. Furthermore, observed NBL regime transitions are represented in a natural way. The reference model version performs much better than a model version that applies excessive vertical mixing as is done in several (global) operational models. Model sensitivity runs showed that for weak-wind conditions the inversion strength depends much more on details of the land-atmosphere coupling than on the turbulent mixing. The presented results indicate that in principle the physical parametrizations of large-scale atmospheric models are sufficiently equipped for modelling stably-stratified conditions for a wide range of forcing conditions.