The ability of general circulation models (GCMs) to correctly simulate precipitation is usually assessed by comparing simulated mean precipitation with observed climatologies. However, to what extent the skill in simulating average precipitation indicates how well the models represent temporal changes is unclear. A direct assessment of the latter is hampered by the fact that freely evolving climate simulations for past periods are not set up to reproduce the specific evolution of internal atmospheric variability. Therefore, model-to-real-world comparisons of time series of daily, monthly, or annual precipitation are not meaningful. Here, for the first time, the authors quantify GCM skill in simulating precipitation variability using simulations in which the temporal evolution of the large-scale atmospheric state closely matches that of the real world. This is achieved by nudging the atmospheric states in the ECHAM5 GCM, but crucially not the precipitation field itself, toward the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). Global correlation maps between observed and simulated seasonal precipitation allow areas in which simulated future precipitation changes are likely to be meaningful to be identified. In many areas, correlations higher than 0.8 are found.This means also that in these regions the simulated precipitation is a very good predictor for the true precipitation, and thus a statistical correction of the simulated precipitation, which can include a downscaling component, can provide useful estimates for local-scale precipitation. The authors show that a simple scaling of the simulated precipitation performs well in a cross validation and thus appears to be a promising alternative to standard statistical downscaling approaches.

Although trees are numerous in urban areas, their dynamic effects on the wind flow are usually approximated or neglected altogether in many wind engineering studies, especially those based on numerical modeling. This study investigates the effect of the inclusion of trees in numerical simulations of wind flow in urban area. Three approaches are used to include the dynamic effect of trees: the basic approach (tree effects are neglected), the implicit approach (tree effects are included in the surface parameterizations), and the explicit approach (trees are represented by porous media). Several test cases have been adopted in order to cover a wide range of urban complexities, wind directions, foliage densities, and tree planting configurations. The results show that there are significant effects of trees when the explicit approach is used compared to the basic and the implicit approaches. Thus tree effects need to be considered using an explicit approach to simulate wind flow in urban area. Also, many parameters such as wind direction, foliage density, and urban configuration are believed to influence the intensity of trees effects. This study emphasizes the importance to explicitly consider the effects of trees in numerical model investigations for the wind flow in urban areas

Urban areas have well‐documented effects on climate, such as the urban heat island (UHI) effect, reduction of wind speeds, enhanced turbulence and boundary layer heights, and changes in cloud cover and precipitation. The aim of this study is to quantify the impact of the urban area of London on local and regional climate. This is achieved through the coupling of the non‐hydrostatic mesoscale model METRAS with the sophisticated urban canopy scheme BEP. The model is configured for case studies of the London region, for typical UHI conditions, and the model results are evaluated using data from meteorological monitoring sites. This study develops a methodology to quantify the regional impact of urbanisation from numerical model results. The urban area, in its current form, is found to affect near surface temperature, the diurnal temperature range, the UHI, and the near surface wind speed and direction. For the selected cases, peak UHI intensities of up to 2.5 K are found during night time hours, with the timing and magnitude of the peak showing good agreement with previous experimental studies for London. The timing of the UHI peak intensity for the current urban land cover for London shows a good agreement with the results of measurements. A significant reduction in wind speed over the urban area was also simulated during both daytime and night time, due to the higher roughness of the city compared to the rural domain. The effect is shown to have a regional character, with both urban and surrounding rural areas demonstrating a significant impact. Thus, the UHI can not only be understood when focussing on local data, but the interaction with the surrounding needs to be considered.

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.

This is the review of CFD (Computational Fluid Dynamics) guidelines for dispersion modeling in the USA, Japan and Germany. Most parts of this review are based on the short report of the special meeting on CFD Guidelines held at the International Symposium on Computational Wind Engineering (CWE2014), University of Hamburg, June 2014. The objective of this meeting was to introduce and discuss the action program to make worldwide guidelines of CFD gas-dispersion modeling. The following six gas-dispersion guidelines including Verification and Validation (V&V) schemes are introduced by each author; (1) US CFD guidelines; (2) COST/ES1006; (3) German VDI (Verein Deutscher Ingenieure) guidelines; (4) Atomic Energy Society of Japan; (5) Japan Society of Atmospheric Environment; (6) Architectural Institute of Japan. All guidelines were summarized in the same format table shown in the main chapters in order to compare them with each other. In addition to the summary of guidelines, the overview of V&V schemes and many guidelines of CFD modeling in the USA are explained.