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.

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.