Wind machines have been increasingly used for frost damage mitigation in the agricultural community. During radiative frost nights, wind machines are used to erode near-surface thermal inversion by air mixing. The underlying mixing processes remain poorly understood. A full picture of warming effects caused by air mixing requires measurements with wide coverage and high resolution. Our study aimed to quantify the magnitude and area of warming by air mixing and identify the characteristic mixing processes downwind and upwind. We installed 9 km of fiber optic cables in a 6.75 ha orchard block, creating two horizontal planes and three vertical profiles. Quasi-3D temperature responses with spatial sampling and temporal resolution of 25 cm and 10 s, respectively, were obtained before and during machine operation. We found a 50% reduction of the local inversion strength (8 K) over 0.42 ha at 1 m and 0.46 ha at 2 m height. The warming area for a 30% reduction extends to 2.81 and 2.52 ha, respectively. As the propeller rotates 360°, the weak background wind substantially impacts the air mixing processes downwind and upwind. When jets blow along with background wind, the warming plumes arrive earlier than the jet due to horizontal advection from earlier warmed sections. The warming plumes consequently accumulate downwind and penetrate deep into the canopy. In contrast, in upwind direction, wind drag resistance causes warming plumes arrive later than the jet. Quadrant analysis reveals that flux transport during the machine operation is dominated by sweeping and ejection motions. Intermittent downdrafts of warm air and updrafts of cool air result in efficient vertical heat exchange. This feature makes wind machines highly effective in raising canopy airspace temperature to mitigate frost damage.

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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 Ls that represents the size of the smallest eddies near the grass structures. We show that Ls 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.@en

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 Ls that represents the size of the smallest eddies near the grass structures. We show that Ls 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.@en

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 Ls that represents the size of the smallest eddies near the grass structures. We show that Ls 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.@en

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 Ls that represents the size of the smallest eddies near the grass structures. We show that Ls 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.@en

To mitigate spring frost damage, fruit farmers use wind machines to mix warm overlying air down to the vegetation. Up to this point, studies on wind machine efficiency have focused on air temperatures. The temperature of different plant organs during operation remains unknown, while critical for the actual degree of frost damage. With Distributed Temperature Sensing we measured vertical in-canopy air temperature profiles in a pear orchard in the Netherlands and thermistors were installed to determine the plant tissue temperatures. We found that to optimize wind machine operation, it is important to consider two effects of a wind machine: (1) mixing of stratified air above and into the canopy layer and (2) erosion of the leaf boundary layer to facilitate plant–air heat exchange. We show how foliage reduces plume penetration to the ground with distance to the wind machine. Due to this blocking at least 15 rotations (∼ 75 min) are needed for optimal mixing. Leaf temperatures lag behind air temperatures, due to strong radiative cooling. We found that over the rotation cycle of a wind machine the temperature difference between leaf and air is variable as convective warming repeatedly dominates over radiative cooling. This is different for flowers and shoots due to different heat capacities. Thin flower petals store little heat and are almost in direct equilibrium with air temperature changes. Shoots, with their higher heat capacity and lower surface/volume ratio, store more heat during the day that is slowly released at night. This discrepancy between plant and air temperature should be considered for frost damage prediction.@en

We have identified certain fundamental limitations of a mixing-length parametrization used in a popular turbulent kinetic energy-based subgrid-scale model. Replacing this parametrization with a more physically realistic one significantly improves the overall quality of the large-eddy simulation (LES) of stable boundary layers. For the range of grid sizes considered here (specifically, 1 m–12.5 m), the revision dramatically reduces the grid-size sensitivity of the simulations. Most importantly, the revised scheme allows us to reliably estimate the first- and second-order statistics of a well-known LES intercomparison case, even with a coarse grid size of O(10 m).

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