Abstract
Abstract. This paper describes the developing theory and underlying processes of the microscale obstacle-resolving model MITRAS version 2. MITRAS calculates wind, temperature, humidity, and precipitation fields, as well as transport within the obstacle layer using Reynolds averaging. It explicitly resolves obstacles, including buildings and overhanging obstacles, to consider their aerodynamic and thermodynamic effects. Buildings are represented by impermeable grid cells at the building positions so that the wind speed vanishes in these grid cells. Wall functions are used to calculate appropriate turbulent fluxes. Most exchange processes at the obstacle surfaces are considered in MITRAS, including turbulent and radiative processes, in order to obtain an accurate surface temperature. MITRAS is also able to simulate the effect of wind turbines. They are parameterized using the actuator-disk concept to account for the reduction in wind speed. The turbulence generation in the wake of a wind turbine is parameterized by adding an additional part to the turbulence mechanical production term in the turbulent kinetic energy equation. Effects of trees are considered explicitly, including the wind speed reduction, turbulence production, and dissipation due to drag forces from plant foliage elements, as well as the radiation absorption and shading. The paper provides not only documentation of the model dynamics and numerical framework but also a solid foundation for future microscale model extensions.
Highlights
The urban boundary layer is considerably influenced by its surface characteristics
This closure is based on the standard E–ε model and the Kato and Launder (1993) modifications, which eliminate the excessive turbulent kinetic energy produced by the standard E–ε model in stagnation regions (López et al, 2005)
Wind turbines are represented in MITRAS by impermeable grid cells at the position of the tower and the nacelle, similar to other buildings
Summary
The urban boundary layer is considerably influenced by its surface characteristics. Within the canopy layer, atmospheric flow is disturbed by buildings and other obstacles located at the surface and all related atmospheric processes (Meng, 2015). The neighbor buildings add their own impacts on the urban meteorology, resulting in interacting flow and dispersion patterns Due to this complexity, explicit resolving of the buildings is necessary instead of only implicitly considering building effects by using surface roughness parameterizations. Explicit resolving of the buildings is necessary instead of only implicitly considering building effects by using surface roughness parameterizations This gave rise to the development of obstacle-resolving microscale meteorological models such as PALM (Maronga et al, 2015), ASMUS (Gross, 2012), ENVI-met (Bruse and Fleer, 1998; Müller et al, 2014), MISKAM (Eichhorn, 1989; Eichhorn and Kniffka, 2010), MUKLIMO (Früh et al, 2011), MITRAS (Schlünzen et al, 2003; Salim et al, 2011), and OpenFOAM (Franke et al, 2012).
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