This paper presents the basic features of a newly developed planetary boundary layer (PBL) parameterization, and the performance assessment of a version of the University of California, Los Angeles (UCLA), Atmospheric General Circulation Model (AGCM) to which the parameterization is incorporated. The UCLA AGCM traditionally uses a framework in which a sigma-type vertical coordinate for the PBL shares a coordinate surface with the free atmosphere at the PBL top. This framework facilitates an explicit representation of processes concentrated near the PBL top, which is crucially important especially for predicting PBL clouds. In the new framework, multiple layers are introduced between the PBL top and earth's surface, allowing for predictions of the vertical profiles of potential temperature, total water mixing ratio, and horizontal winds within the PBL. The vertically integrated ''bulk'' turbulent kinetic energy (TKE) is also predicted for the PBL. The PBL-top mass entrainment is determined through an equation including the effects of TKE and the radiative and evaporative cooling processes concentrated near the PBL top. The surface fluxes are determined from an aerodynamic formula in which the velocity scale depends both on the square root of TKE and the grid-scale PBL velocity at the lowermost model layer. The turbulent fluxes within the PBL are determined through an approach that includes the effects of both large convective and small diffusive eddies. AGCM simulations with the new formulation of PBL are analyzed with a focus on the seasonal and diurnal variations. The simulated seasonal cycle of stratocumulus over the eastern oceans is realistic, as are the diurnal cycles of the PBL depth and precipitation over land. The simulated fluxes of latent heat, momentum, and shortwave radiation at the ocean surface and baroclinic activity in the middle latitudes show significant improvements over the previous versions of the AGCM based on the single-layer PBL.

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In this work is presented a statistical description of wind profile in the first 100 m of height of the Planetary Boundary Layer, taking account the measurements in the tower Colonia Eulacio Uruguay. This tower has high vertical resolution of wind velocity measurements, form 10.1 m to 101.8 m. Thermometer are installed in 3.4 m and 100.8 m, also the tower is equipped with wind vane and pyranometer. We present the diurnal cycle of mean wind, intensity of turbulence in dependence of height, also standard deviation of direction is described as a measure of turbulence in wind. Stability state is computed with vertical gradient of temperature. Before sunrise (unstable condition) is seen a decrease in mean velocity of top levels (81.8 m and 101.8 m) and increase in lower levels (10.1 m and 25.7 m). Higher dispersion in dT/dz can be seen during night time (stable condition), superadiabatic values -0.02 ◦C/m can be seen during daytime with slow dispersion. Intensity of turbulence decrease with height, for all stability conditions, is seen a increase in intensity of turbulence for unstable condition.

This work presents the results of a numerical forecast system of minimum cost for the electric power generated by wind farms in Uruguay. By keeping at minimum levels both the computational costs and the complexity of the empirical corrections of the numerical results, we obtain a benchmark for the forecast skill of more complex forecast systems, that is easily available during their calibration stages and operative functioning. The work also aims to explore the diurnal and seasonal cycle of the forecasts quality. It is found that this simple forecast system produces very good results, albeit the dependencies of the forecast skill and errors respect to the season of the year and the time of the day are distinguishable. It is also found that it is necessary to take into account the diurnal and the seasonal cycles during the calibration of the empirical corrections. The good results of this simple technique might had been possible due to the relative smooth topography of Uruguay.

This work assessed the quality of wind speed estimates in Uruguay. These estimates were obtained using the Weather Research and Forecast Model Data Assimilation System (WRF-DA) to assimilate wind speed measurements from 100 m above the ground at two wind farms. The quality of the estimates was assessed with an anemometric station placed between the wind farms. The wind speed estimates showed low systematic errors at heights of 87 and 36 m above the ground. At both levels, the standard deviation of the total errors was approximately 25% of the mean observed speed. These results suggested that the estimates obtained could be of sufficient quality to be useful in various applications. The assimilation process proved to be effective, spreading the observational gain obtained at the wind farms to lower elevations than those at which the assimilated measurements were taken. The smooth topography of Uruguay might have contributed to the relatively good quality of the obtained wind estimates, although the data of only two stations were assimilated, and the resolution of the regional atmospheric simulations employed was relatively low.