Weather and climate models require knowledge about the surface temperature and surface heat flux to make predictions for climatology, farming, wind power prediction, etc. Most current models make use of Monin-Obukhov Similarity Theory (MOST). This theory expresses multiple turbulent fluxes in terms of their mean gradients with height. MOST results in an accurate universal form for the non-dimensional wind, temperature and humidity profiles from just above the surface and up to the top of the Atmospheric Surface Layer. The description of the near-surface temperature profile above a rough surface is, however, non-robust and ill-defined in the lowest layer of the atmosphere, the Roughness Sublayer. This thesis presents a new flux-gradient framework based on surface geometry. We apply it to the near-surface temperature profile of high-resolution experimental data from fibre optic measurements over a grass surface. The framework was developed to universally compare 3 different types of models at the surface: a Direct Numerical Simulation in a smooth pipe validated model; a constant surface gradient over grass model and a tall canopy model. Where the temperature is scaled with the already in use turbulent heat flux scale, the new length scale scales the height based on a finite surface gradient which is observed in experimental data. The experimental data can in this framework collapse onto one universal profile with the use of a reference temperature taken at the top of the grass. The framework thus extends MOST with a universal non-dimensional temperature profile in the roughness sublayer.

Litter decomposition in soils is a microbial process linked to soil respiration, affected by soil composition as well as environmental factors such as temperature and moisture. For alpine areas in particular, these stand to vary significantly with climate change. To characterize the impacts of these projected changes on the carbon fluxes and carbon cycling in the environment, this study uses turf transplants along an altitudinal gradient in Western Norway. Warming is simulated for alpine and subalpine soils. Because the soils differ in composition, this enables the quantification of the influence of soil composition on soil litter decomposition and respiration. Decomposition is quantified using the standard Tea Bag Index (TBI) where the mass loss of buried rooibos and green tea bags over an extended period is used to model the labile and recalcitrant fraction of litter in the soil. Respiration CO2 fluxes are quantified from concentration measurements in an infrared gas analyzer (IRGA, LI-84A, LICOR) across a prescribed period and bare soil area. Results from this study show that simultaneous optimal soil moisture and temperature conditions maximize soil respiration and litter decomposition rates. These optimal ranges are 15-35% for soil moisture and the maximum measured 22 oC for temperature. However, the impacts of the conditions individually are more complex: soil moisture is positively correlated with soil respiration, while the correlation with temperature is inconclusive. Decomposition rates and stabilization factors for the Liahovden, the alpine site, consistently exceed those for Joasete, the sub-alpine site, which contains less soil organic matter (SOM) and carbon. With warming, Joasete exhibits opposing behavior to that of Liahovden: reduced decomposition rates and litter stabilization. These findings suggest that the availability of nutrients due to soil moisture and the soil composition itself are the most important factors determining the carbon emissions and cycling in the soil. Nevertheless, under coupled optimal conditions (warmer climate with soil moisture at approximately 35%), there is a clear maximum in flux. The complexity of the interrelations of soil moisture and temperature for different soil types supports further research on the topic, with more replicates and soil moisture content variation plot by plot.

This study aims to look into the effect of small-scale surface heterogeneity on the mixing properties within the stable boundary layer (SBL) and the impact of different configurations of the heterogeneity on this mixing. The motivation for this research is to better understand the turbulent mixing phenomena in the SBL and to be able to represent the mixing more accurate in weather prediction models. In the current models, this mixing is highly uncertain or even missing. It is likely that this mixing is driven by thermal memories that are spatially distributed over the land-surface in the form of surface heterogeneity. These surface heterogeneities (e.g. ditches or roads) effectively store heat during the day and then turn into heat sources, driving turbulent mixing, during the night. A simulation with surface heat sources in an idealized SBL is setup and four case studies are performed. The simulations show that the heat sources clearly influence the mixing in the SBL. A buoyancy plume is formed above a heat source. The plumes of two heat sources are attracted towards each other. At smaller distances the plumes even merge and form a single plume. In the three-dimensional simulations, the distance between the heat sources has an influence on their effect on the SBL. At small distances, the kinetic energy in the system decreases with increasing distances between two heat sources. At larger distances this decrease appears to level off. Apparently, the bending and merging of the plumes allows turbulent length scales to increase, causing the effect of the buoyancy sources to be larger. To verify these simulation results, a field experiment is conducted. An infrared camera pointing at a vertical high-emissivity cloth was able to capture the two-dimensional (vertical and horizontal) air temperature pattern above heat sources. The merging effect between two plumes is also observed in this field experiment. At small distances a single merged heat plume was visible above two heat sources and at larger distances two separated heat plumes are formed.

This thesis contributes to the scientific underpinning of the battle against fruit frost. Fruit frost is the freezing damage to blossoms when in the growing season the night temperature drops below 0±C. This results in damaged or undeveloped fruits, and a yield loss for the fruit farmer. Several techniques against fruit frost have been developed, including sprinkling and wind machines, often in combination with meteorological models, for example, to predict air temperature. However, the contribution of heat exchange with the soil to moderate orchard temperatures is often not included. In this thesis, this heat transfer is investigated, as an increase of heat transfer from the soil to the orchard during the night is a potential remedy against fruit frost. The research is based on measurements for soil temperature, soil heat flux, and soil moisture from two locations (1. Haarweg (Gelderland), The Netherlands 2. Bushland (Texas), The U.S.A.). First, a numerical model is developed to calculate the temperature and soil heat flux profiles for a soil layer. The results are compared to the results of an already developed analytical model. Second, the thermal parameters, that are of influence on the heat transfer, are analyzed by assessing a) their robustness in relation to the model and b) their relation to soil moisture. Because a numerical model is more flexible for shorter periods of data compared to an analytical model (because of underlying assumptions), it can be used to relate the parameters to (daily) varying soil moisture. Third, the numerical model for heat transfer is extended to the vegetation layer, and, again, the results are compared to analytical results. The model is created by assuming homogeneity in both separate layers and by discretizing the governing heat equation over the domain. The results show that the model reproduces temperature and soil heat flux in the soil layer with similar accuracy as the analytical, harmonic model. One thermal parameter, the diffusivity, is robust and does not show a clear dependency on soil moisture. The model is however sensitive to deviations in the other parameter, the heat conductivity. The model shows a clear relation between conductivity and soil moisture, and from this, a site-specific quantitative relation is determined. This relation however is only valid in the investigated region of moisture variation and we recommend future research to cover data in a broader range of soil moisture. Overall, we conclude that the model successfully reproduced the temperature and soil heat flux throughout the full vegetation-soil continuum.

Climate models have difficulties in predicting the frequency and intensity of future droughts on regional scales, possibly caused by inadequate representation of land surface hydrological processes. Vegetation is controlling the Earth's water and energy balance by transporting water from the subsurface to the atmosphere, through its roots. The water storage capacity in the vegetation's rootzone is a key parameter in predicting evaporation fluxes in land surface models because its size determines how long into the dry season vegetation is able to evaporate. Ecosystems design the size of their rootzone water storage reservoir to optimally function and to overcome dry periods, based on climatic conditions. Whereas climate is the major driver of root development, the rootzone storage capacity in the HTESSEL land surface scheme is only dependent on soil type and modelled soil depth. Moreover, the model describes root parameters by tables based on scarce observations of individual plants that do not represent ecosystem scales. This research aims to analyse the effect of the climate-based mass balance method for estimating the maximum water storage capacity in the vegetation's rootzone on the representation of water and energy fluxes in the HTESSEL land surface model. Maximum rootzone water storage capacities are estimated for 15 river catchments in Australia based on catchment-scale water balances. These estimates are implemented in the current surface parameterisation of the HTESSEL land surface model and offline simulations are performed. The current model performance and the model performance with adapted rootzone water storage capacities are evaluated regarding simulation of water and energy fluxes. According to this study, the storage capacity in the vegetation’s rootzone represented in HTESSEL is larger than the mass-balance derived estimates. The model strongly overestimates evaporation fluxes and thereby underestimates river discharge, with larger relative simulation errors in the dry season than in the wet season. The climate-based mass balance total rootzone water storage capacities have small effects on the representation of water and energy fluxes by the model, but contribute to a consistent improvement in predicting these fluxes. Nash Sutcliffe Efficiencies of the modelled river flows improve on average from 0.44 in the base model to 0.51 in the model with mass balance rootzone water storage capacities. The results indicate that the inadequate rootzone representation is a source of modelling error. However, it is expected that other hydrological process are also inadequately represented by the model, as the modelling simulation errors remain large when implementing mass balance rootzone water storage capacities. Moreover, it was found that internal vegetation dependent model parameters strongly influence the simulated fluxes and could therefore be another source of model bias. This study shows that investigating uncertainties in the representation of the rootzone in the HTESSEL land surface model is paramount. More research on the representation of hydrological processes in land surface models could lead to significant improvements in climate model predictions.

The non-linear relation between Evapotranspiration (ET) and the atmospheric moisture demand in terms of vapor pressure deficit (VPD) has been widely reported. Observations point towards a diverse range of potential drivers; however, without uncovering why the identified factors are found to control diurnal ET-VPD hysteresis. Modelling efforts have laid a theoretical foundation to unravel the compound effect of surface and atmospheric states on this hysteresis. However, so far these models have been unable to realistically incorporate the non-linear feedbacks between atmosphere and surface, and lack a vegetation representation that reflects the underlying biological mechanisms. To unravel in what manner the characteristics of ET-VPD hysteresis are controlled, multi-scale observations spanning biology, meteorology, and hydrology from the CloudRoots campaign are combined with modelling in a novel manner. For the first time a proof-of-concept is delivered for reproducing ET-VPD hysteresis with a model that incorporates both surface-atmosphere feedbacks as well as a mechanistic vegetation component. Observations are used for parameter initialization and evaluation to ensure that the modelled hysteresis curve and underlying processes represent a realistic case. Next, this calibrated model is used for a sensitivity analysis. The results show that both the early morning state of the surface and the state of the atmosphere influence the characteristics of the hysteresis loop with respect to its width, height, and initial slope. Via control of the stomatal aperture, soil moisture stress and the vegetation’s capacity to assimilate CO2 for photosynthesis affect the height and width of the curve. The height of the hysteresis loop is significantly affected by entrainment of warm dry air, while its width is minorly impacted. The characteristic fingerprint of entrainment is distinctly different to that of soil moisture stress and the capacity for CO2 uptake. The sensitivity analysis applied to our observationally inspired case, appears to facilitate quantification of the strongest model responses to changing external forcings and parameters. Therefore, the presented approach offers a promising tool, allowing further research into the controlling mechanisms of ET-VPD hysteresis.

Wind machines are used to prevent or mitigate the adverse effects of night frost in spring. These frost events occur during clear-sky, low-wind nights in which a thermal inversion builds up from the surface. The machines work by mixing and transporting warm air from aloft downward which consequently erodes the thermal inversion. Various studies have been conducted regarding this frost protection method, which have resulted in empirical regression models that relate affected area and temperature enhancement (i.e. the performance) with inversion strength. In this study, we assessed heightdependent temperature responses and the sensitivity of wind machine performance to various physical processes. Both of which have not been studied thoroughly in earlier works. In this regard, a large field experiment was conducted and experimental analysis was augmented with sensitivity studies using turbulent resolving Large Eddy Simulations (LES). Experimental observations showed that the temperature response strongly depends on the radial distance to the fan and the height above the surface. In agreement with previous studies, the wind machine was able to achieve rotation-averaged temperature increases of up to 50% of the inversion strength (≈3 K) in an area of 3-5 ha at 1 m height. Furthermore, it was observed that low-speed ambient winds (<1 m/s) can cause strong upwind-downwind asymmetries in the protected area, the downwind area being larger. The LES model, inspired by the field experiment, showed similar spatial temperature responses as compared to observations. Sensitivity studies using a simpli_ed case showed that the a_ected area strongly increased for slower axial rotation times (ranging from 3 to 6 min) while the temperature enhancement stayed relatively constant. Furthermore, variation of the horizontal tilt angle showed that, in our model, temperature enhancement was maximized between 8º and 16º. Presumably, those angles, corresponding to near horizontal ow, are very effective in generating strong shear layers which in turn generate Kelvin-Helmholtz like instabilities. These processes increase mixing and vertical transport of heat. Finally, analysis on the ambient wind showed that, in agreement with observations, strong upwind-downwind asymmetries in the affected area exist.

A brief study to understand the physical driving forces concerning ice growth. These forces are mathematically described in a basic prediction model. Further complexity to the model is added through adopting various assumptions about the physical factors involved.

Near-surface wind speed is typically only measured by point observations. The so-called Actively Heated Fiber-Optic (AHFO) technique, however, has the potential to provide high-resolution distributed observations, allowing for better understanding of different processes. However, before it can be widely used, its performance needs to be tested in a range of settings. Therefore, in this work, experimental results on this novel observational wind-probing technique are presented. We utilized a controlled wind-tunnel setup to assess both the accuracy and the precision of AHFO as well as its potential for outdoor atmospheric operation. The technique allows for wind speed characterization with a spatial resolution of 0.3 m on a 1 s time scale. The flow in the wind tunnel is varied in a controlled manner, such that the mean wind, ranges between 1 and 17 m/s. Comparison of the AHFO measurements with observations from a sonic anemometer shows a high overall correlation, ranging from 0.94-0.99. Also, both precision and accuracy are greater than 95 %. As such, it is concluded that the AHFO has potential to be employed as an outdoor observational technique in addition to existing techniques. In particular, it allows for characterization of spatial varying fields of mean wind in complex terrain, such as in canopy flows or in sloping terrain. In the future the technique could be combined with regular Distributed Temperature Sensing (DTS) for turbulent heat flux estimation in micrometeorological/hydrological applications.

Nocturnal weather can have significant impact on society. Dangerous conditions can occur after clear sky nights with weak winds. The lack of turbulent mixing during these nights can cause the near-surface temperature to rapidly decrease. A single short-lived turbulent event can renew turbulent mixing and hamper/stop the formation of fog or severe frost, averting dangerous conditions for e.g. Short-lived turbulence has been studied using single tower observations, but the spatial scale of this phenomenon is not yet known. The goal of this study is to fill that gap and estimate the spatial scale of short-lived turbulent structures in the nocturnal boundary layer.

Short-lived turbulent structures are studied using wind speed and near-surface temperature observations from existing observational networks in the Netherlands. Nights with short-lived turbulence are selected using an automated filter and manual selection. Visual analysis is first used to identify that the turbulent structures span multiple stations of the network. If so, the correlation between pairs of stations is quantified as a function of their spatial separation. Next, an exponentially decaying fit is applied to this data. The e-folding distance of this fit serves as the estimation of the spatial scale of the turbulent structure.

A dense network is found by using the observational masts at and around Schiphol Airport. Visual analysis shows that this network is sufficiently dense for the turbulent structures to span multiple stations. Using the aforementioned methodology, the scales of the short-lived turbulent structures are estimated to range between 1.5 km and 24 km, with a median of 9 km. The spatial scale of short-lived turbulent structures is therefore estimates at 9 km.
This study should be considered to be a first-order estimate. In fact, one of the weaknesses of the method used is that it only takes the distance between stations into account (without incorporating directional effects). As such, it assumes the turbulent event to be spatially isotropic. At present, limitations by the network do not allow for a clear assessment of the spatial structure of the events.
To accurately study both the dynamics and the spatial coherence of short-lived turbulent structures, a dense and uniformly distributed network is recommended. Ideally, such set-up would consist of a nested fine-scale network within a courser network which needs to span a distance of 25 km minimum to capture turbulent events such as the ones studied here.

In addition to turbulent events, regional temperature variations are found. Near-surface temperature differences up to 9 degrees over a distance of 40 km are observed during nighttime. The daytime temperature at these stations is nearly identical, stressing the differences in atmospheric physics during day and night. These local variations may result from different local (soil) conditions, local turbulence and clouds. Artificial turbulence, caused by large airplanes taking off, is observed close to the airport’s runways, increasing the local near-surface temperature up to 4 degrees. It will be interesting to also study the impact of artificial turbulence on the near-surface temperature as a follow up of the current work.