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Wim C. de Rooy and Kees Kok

Abstract

In this paper a combined physical–statistical approach for the downscaling of model wind speed is assessed. The key factor in this approach is the decomposition of the total error (model − observation) into a small-scale representation mismatch (RM) and a large-scale model error (ME). The RM is caused by the difference between the grid-box mean conditions of the model and the locally valid conditions. For wind speed, the RM is primarily determined by the difference in roughness between the model and the location. In the first step of the combined approach, the physical method (based on surface layer theory) adjusts the model output for the roughness characteristics at several observation sites. For these local wind estimates the RM is strongly reduced but the ME remains. To reduce this ME, the local wind estimates, together with the corresponding observations, are used in one pool to derive one linear regression equation. With local roughness length information derived from land-use maps, this regression equation can then be applied to model output to produce high-resolution wind speed fields. Using a 3-yr dataset, the combined approach is validated at six independent stations in the Netherlands (with different RMs). In this way, it is shown that for observation-free locations the combined approach results in a significant improvement in skill compared to the standard model output as well as the physical method only. The method can be optimized for special conditions, such as high wind speed cases.

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Wim C. de Rooy and A. Pier Siebesma

Abstract

For a wide range of shallow cumulus convection cases, large-eddy simulation (LES) model results have been used to investigate lateral mixing as expressed by the fractional entrainment and fractional detrainment rates. It appears that the fractional entrainment rates show much less variation from hour to hour and case to case than the fractional detrainment rates. Therefore, in the parameterization proposed here, the fractional entrainment rates are assumed to be described as a fixed function of height, roughly following the LES results. Based on the LES results a new, more flexible parameterization for the detrainment process is developed that contains two important dependencies. First, based on cloud ensemble principles it can be understood that deeper cloud layers call for smaller detrainment rates. All current mass flux schemes ignore this cloud-height dependence, which evidently leads to large discrepancies with observed mass flux profiles. The new detrainment formulation deals with this dependence by considering the mass flux profile in a nondimensionalized way. Second, both relative humidity of the environmental air and the buoyancy excess of the updraft influence the detrainment rates and, therefore, the mass flux profiles. This influence can be taken into account by borrowing a parameter from the buoyancy-sorting concept and using it in a bulk sense. LES results show that with this bulk parameter, the effect of environmental conditions on the fractional detrainment rate can be accurately described. A simple, practical but flexible parameterization for the fractional detrainment rate is derived and evaluated in a single-column model (SCM) for three different shallow cumulus cases, which shows the clear potential of this parameterization. The proposed parameterization is an attractive and more robust alternative for existing, more complex, buoyancy-sorting-based mixing schemes, and can be easily incorporated in current mass flux schemes.

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Wim C. de Rooy and A. A. M. Holtslag

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A scheme is proposed that relates surface flux densities of sensible heat, latent heat, and momentum to routine weather data. The scheme contains parameterizations concerning the radiation components and the surface energy flux densities. The parameterizations are developed and examined using observations from 1987 of a grass-covered surface at Cabauw in the Netherlands. It is shown that improvements in the parameterizations are achieved by incorporating an albedo dependence on solar elevation, a longwave downward radiation with a correction for the amount of high clouds, and a soil heat flux with a soil temperature approximated by a 24-h-mean 2-m temperature. In addition, the Penman–Monteith concept for the latent heat flux is utilized with a simple one-parameter surface resistance, which depends on atmospheric moisture deficit in particular. Special attention is paid to the treatment of surface inhomogeneities. A distinction is made between stable conditions, when measurements in the lower 10 m appear to be in equilibrium with the local surface, and unstable conditions, when measurements seem to be influenced by deviating upstream surface conditions. A constant roughness length for heat above grassland of 1 mm is applied. Finally, the scheme as a whole is evaluated and compared with a previous approach by A. P. van Ulden and A. A. M. Holtslag. It appears that in particular the sensible heat flux is improved with the new scheme. This can be ascribed mostly to the replacement of the modified Priestley–Taylor by the Penman–Monteith formulation and by a better representation of the surface temperature.

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