Aspects of atmospheric turbulence related to scintillometry Atmospheric turbulence is the main vertical transport mechanism in the atmospheric boundary layer. The surface fluxes related to this turbulent transport are the sensible () and latent heat fluxes (). The area-averaged values of and are of interest to evaluate mesoscale numerical weather models and in water budget studies. Natural landscapes are often heterogeneous, i.e. and differ among fields. The fluxes can be obtained with a scintillometer system, which consists of an electromagnetic beam transmitter at one end of a propagation path and a receiver at the other end. The intensity of the electromagnetic signal at the receiver varies due to fluctuations in the refractive index of air () caused by turbulence along the path. From the magnitude of these fluctuations the structure parameter of temperature () and of humidity () can be derived. Finally, and are used to determine path-averaged and via Monin-Obukhov similarity theory (MOST). The advantage of scintillometry is that the obtained fluxes are path-averaged, which makes scintillometry a more suitable method for obtaining area-averaged fluxes over natural landscapes than traditional point measurements. However, the disadvantage is that the fluxes are not directly measured. Therefore in this thesis four questions are answered related to the applicability of MOST and to the behaviour of structure parameters over heterogeneous surfaces. The latter is important because MOST assumes homogeneous surface conditions. For our studies we used meteorological data measured at three sites (Cabauw; the Netherlands, CASES-99 experiment; Leon; Kansas; USA, LITFASS-2009 and LITFASS-2010 experiments; Lindenberg; Germany) under unstable conditions (day-time). MOST is restricted to the part of the atmosphere close to the surface: the atmospheric surface layer (ASL). The depth of the ASL is not constant during the day, and is relatively shallow during the morning. At those moments, the scintillometer observation level can be located outside the ASL, which can question the validity of MOST. Therefore, we proposed and compared two variations in MOST (MOST using local fluxes and MOST using surface fluxes). We found that during the afternoon when both concepts have to be valid, the values of are comparable. During the morning, the data do not unequivocally support one of the two concepts: MOSTl shows the correct temporal behaviour in, but underestimates by a factor of ten. The universal function that links the surface fluxes with the structure parameter in MOST needs to be determined empirically. In literature a great variety of these function can be found. Therefore, we investigate to what extent the expression for this function depends on the specific regression approaches, stability range and observation level. First, we found that applying various regression approaches has an impact on the expression. This means that studies always should specify their regression approach, when presenting new functions. We advise to use an orthogonal distance regression method, applied to the logarithmic transformation of both dimensionless groups, and weighted such that unreliable data points have a smaller influence on the fit. Second, we found that the observation height and the stability range have an impact on the coefficients too. This implies that variations found in literature may result from variations in the height and stability ranges among the datasets. Furthermore, application of a given expression on a dataset measured at a different height or within a different stability range has to be done with care. In order to investigate whether variations in and along a scintillometer path or aircraft flight leg are within the range of local variability, or could be attributed to surface heterogeneity, we analysed the amount of local variability in the structure parameters at different heights and under different stability regimes. We found that the variability is determined by stability and by the size of the averaging window over which the structure parameters are calculated. If instability increases, differences in structure parameters between upward motions and downward motions increase. If the averaging window size increases, the variance of the logarithmic structure parameters decreases. A rough estimation of this decrease is made by fitting a simple linear regression between this variances and the averaging window size. From this we found that for various stability classes both the offset and slope (in absolute sense) decrease with increasing instability. The offset and slope can be used to quantify the local variability, which in turn can give an indication if variations in the structure parameters along a scintillometer or flight path might be attributed to surface heterogeneity. Finally, our last study is an elaboration of the study of Beyrich et al. (2012). They compared obtained with the unmanned meteorological mini aerial vehicle (M2AV) with obtained with the large-aperture scintillometer (LAS) for five flights on one single day during LITFASS-2009 experiment. We investigated if the systematically larger values of the M2AV as observed by them, can be found for other days, and if these differences could be reduced or explained through a more elaborate processing of the data of both instruments. We concluded that the difference can be found for other days during LITFASS-2009 and LITFASS-2010 as well. obtained from the M2AV data is larger, which is not improved by the more elaborate data analysis. Moreover, an exact synchronization of the LAS data with the time intervals of the M2AV data does not eliminate the discrepancy between both datasets. All in all, this thesis defines better the borders of MOST and shows the behaviour of the structure parameters in the atmospheric surface layer. Beyrich F, Bange J, Hartogensis OK, Raasch S, Braam M, van Dinther D, Gräf D, van Kesteren B, van den Kroonenberg AC, Maronga B, Martin S, Moene AF (2012) Towards a validation of scintillometer measurements: The LITFASS-2009 experiment. Boundary-Layer Meteorol 144:83-112