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A viscous sublayer was introduced into a PBL model in order to specify the lower boundary condition for temperature. The simulated results have been compared against available observations. However, for such a comparison, some of the variables and parameters that are necessary are not known but can be deduced from observed data. In this way, surface temperature and thermal diffusivity of the soil, representative for the fourday period studied here, have been estimated from measured data. An optimized relation for the thickness of the viscous sublayer d was found that includes the diurnal variation of the properties of the air flow. Including this approach in the model, simulated temperatures in the ground at different levels as well as temperature in the atmosphere agree very well with the observations. The applicability for a wider range of wind speeds was demonstrated by calculating daily maximum temperatures Tmax. An analysis of long-term observations for the summer season at different operational weather stations consistently show a distinct maximum of Tmax for a 10-m wind between 2-3 m/s, which can be explained by the interaction between the molecular transport of heat within the viscous sublayer of thickness d and the turbulent heat flux. [ABSTRACT FROM AUTHOR]

A one-dimensional boundary layer model was combined with a routine to calculate surface temperatures on road bridges. Forced by reanalysis data for the year 2016, simulations were performed for two bridges 80 and 130m in height, respectively. The results for each hour of the year were compared with on-site observations. In addition to the annual variation in general, temperature extremes captured by the model were quite reasonable. Although hourly wind speeds above the bridge were calculated less perfectly, the few cases of simulated and observed maximum mean winds were in good agreement. [ABSTRACT FROM AUTHOR]

A one-dimensional boundary layer model was used to study the effects of uncertain input data on 2-m temperature and 10-m wind. Based on a very large number of numerical results, it can be demonstrated, that even a small degree of ambiguity can have significant implications, especially for temperature. In 50 % of all 6,0 simulations for flat terrain and randomly chosen sets of input data within narrow limits, temperature uncertainty was more than 2 K, and in 14 % of all cases more than 4 K, with a maximum of 9 K. Effect on wind speed is much smaller and depends mostly on surface roughness length. For a forest scenario, the results for temperature of 18,000 simulations are in the same order, with 25 % of the ensemble show temperature uncertainties of more than 2 K, and 6 % of more than 4 K, while wind speed above a forest is much more affected than for the bare soil case. In addition, the contribution of uncertainties of individual input data was estimated. [ABSTRACT FROM AUTHOR]