Wind machines are increasingly used to mitigate spring frost damage in agricultural sectors. Complementing quasi-3D temperature measurements to quantify the warming effects of wind machines (Dai et al., 2023), this study develops a numerical model to quantify warming effects on air and plant tissues and resolve the dynamic interplay between turbulent rotating plumes and canopy structure. We implement an integrated model in a large-eddy simulation and validate the model against field observations. Simulation results show remarkable agreement with the air mixing and warming effects observed during wind machine operation in Dai et al. (2023). Simulation results reveal significant air and leaf warming near the wind machine due to direct jet-mixing. Beyond 20 m from the machine (3–4 rotor diameters), while wind velocities drop rapidly, the warming is sustained and gradually decreases over distance. This sustained warming, without direct jet mixing, likely results from the advection of jet-entrained warm air. The warming extends 150 m upstream and 550 m downstream, influenced by the background wind. This difference is attributed to the interaction between the machine-induced jet and the background wind, forming convergence patterns when jets oppose the wind and extended warming plumes in wave-like patterns when jets align with the wind. Cross-stream warming symmetrically extends about 250 m. Within these warming regions, leaf temperatures closely follow air temperatures due to strong turbulent heat exchanges. Outside the warming zone, radiative cooling prevails, bringing the leaf–air temperature difference back to approximately 1 degree. These findings collectively give new insights into interactions between the induced warming plumes and air flows within the canopy and provide a useful tool to optimize operational wind machine deployment. This integrated model uniquely provides a full, multi-process representation of outdoor reality with respect to wind machine operation in orchards.

In this study, we present an extension to the Monin–Obukov similarity theory (MOST) for the roughness sublayer (RSL) over short vegetation. We test our theory using temperature measurements from fiber optic cables in an array-shaped set-up. This provides a high vertical measurement resolution that enables us to measure the sharp temperature gradients near the surface. It is well-known that MOST is invalid in the RSL as the flow is distorted by roughness elements. However, to derive the surface temperature, it is common practice to extrapolate the logarithmic profiles down to the surface through the RSL. Instead of logarithmic behaviour defined by MOST near the surface, our observations show near-linear temperature profiles. This log-to-linear transition is described over an aerodynamically smooth surface by the Van Driest equation in classical turbulence literature. Here we propose that the Van Driest equation can also be used to describe this transition over a rough surface, by replacing the viscous length scale with a surface length scale L_s that represents the size of the smallest eddies near the grass structures. We show that L_s scales with the geometry of the vegetation and that the model shows the potential to be scaled up to tall canopies. The adapted Van Driest model outperforms the roughness length concept in describing the temperature profiles near the surface and predicting the surface temperature.

In this work we study the dynamics of the surface-based temperature inversion over the Antarctic Plateau during the polar winter. Using 6 years of observations from the French–Italian Antarctic station Concordia at Dome C, we investigate sudden regime transitions in the strength of the near-surface temperature inversion. Here we define “near-surface” as being within the domain of the 45-m measuring tower. In particular, we consider the strongly nonlinear relation between the 10-m inversion strength (T _10m – T _s ) and the 10-m wind speed. To this end, all individual events for which the 10-m inversion strength increases or decreases continuously by more than 15 K in time are considered. Composite time series and vertical profiles of wind and temperature reveal specific characteristics of the transition from weak to very strong inversions and vice versa. In contrast to midlatitudes, the largest variations in temperature are not found at the surface but at a height of 10 m. A similar analysis was performed on results from an atmospheric single-column model (SCM). Overall, the SCM results reproduce the observed characteristics of the transitions in the near-surface inversion remarkably well. Using model output, the underlying mechanisms of the regime transitions are identified. The nonlinear relation between inversion strength and wind speed at a given level is explained by variations in the geostrophic wind speed, changes in the depth of the turbulent layer and the vertical divergence of turbulent fluxes. Moreover, the transitions between different boundary layer regimes cannot be explained without considering the contribution of subsidence heating.

We present a proof-of-concept for the adaptive mesh refinement method applied to atmospheric boundary-layer simulations. Such a method may form an attractive alternative to static grids for studies on atmospheric flows that have a high degree of scale separation in space and/or time. Examples include the diurnal cycle and a convective boundary layer capped by a strong inversion. For such cases, large-eddy simulations using regular grids often have to rely on a subgrid-scale closure for the most challenging regions in the spatial and/or temporal domain. Here we analyze a flow configuration that describes the growth and subsequent decay of a convective boundary layer using direct numerical simulation (DNS). We validate the obtained results and benchmark the performance of the adaptive solver against two runs using fixed regular grids. It appears that the adaptive-mesh algorithm is able to coarsen and refine the grid dynamically whilst maintaining an accurate solution. In particular, during the initial growth of the convective boundary layer a high resolution is required compared to the subsequent stage of decaying turbulence. More specifically, the number of grid cells varies by two orders of magnitude over the course of the simulation. For this specific DNS case, the adaptive solver was not yet more efficient than the more traditional solver that is dedicated to these types of flows. However, the overall analysis shows that the method has a clear potential for numerical investigations of the most challenging atmospheric cases.

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.

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.

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.

Investigation of meteorological measurements along a 45 m tower at Dome C on the high East Antarctic Plateau revealed two distinct stable boundary layer (SBL) regimes at this location. The first regime is characterized by strong winds and continuous turbulence. It results in full vertical coupling of temperature, wind magnitude and wind direction in the SBL. The second regime is characterized by weak winds, associated with weak turbulent activity and very strong temperature inversions reaching up to 25 K in the lowest 10 m. Vertical temperature profiles are generally exponentially shaped (convex) in the first regime and ‘convex–concave–convex’ in the second. The transition between the two regimes is particularly abrupt when looking at the near-surface temperature inversion and it can be identified by a 10 m wind-speed threshold. With winds under this threshold, the turbulent heat supply toward the surface becomes significantly lower than the net surface radiative cooling. The threshold value (including its range of uncertainty) appears to agree with recent theoretical predictions from the so-called ‘minimum wind speed for sustainable turbulence’ (MWST) theory. For the quasi-steady, clear-sky winter cases, the relation between the near-surface inversion amplitude and the wind speed takes a characteristic ‘S’ shape. Closer analysis suggests that this relation corresponds to a ‘critical transition’ between a steady turbulent and a steady ‘radiative’ regime, with a dynamically unstable branch in the transition zone. These fascinating characteristics of the Antarctic boundary layer challenge present and future numerical models to represent this region in a physically correct manner.