Abstract

Abstract. In recent years, the PALM 6.0 modelling system has been rapidly developing its capability to simulate physical processes within urban environments. Some examples in this regard are energy-balance solvers for building and land surfaces, a radiative transfer model to account for multiple reflections and shading, a plant-canopy model to consider the effects of plants on flow (thermo)dynamics, and a chemistry transport model to enable simulation of air quality. This study provides a thorough evaluation of modelled meteorological, air chemistry, and ground and wall-surface quantities against dedicated in situ measurements taken in an urban environment in Dejvice, Prague, the Czech Republic. Measurements included monitoring of air quality and meteorology in street canyons, surface temperature scanning with infrared cameras, and monitoring of wall heat fluxes. Large-eddy simulations (LES) using the PALM model driven by boundary conditions obtained from a mesoscale model were performed for multiple days within two summer and three winter episodes characterized by different atmospheric conditions. For the simulated episodes, the resulting temperature, wind speed, and chemical compound concentrations within street canyons show a realistic representation of the observed state, except that the LES did not adequately capture night-time cooling near the surface for certain meteorological conditions. In some situations, insufficient turbulent mixing was modelled, resulting in higher near-surface concentrations. At most of the evaluation points, the simulated surface temperature reproduces the observed surface temperature reasonably well for both absolute and daily amplitude values. However, especially for the winter episodes and for modern buildings with multilayer walls, the heat transfer through walls is not well captured in some cases, leading to discrepancies between the modelled and observed wall-surface temperature. Furthermore, the study corroborates model dependency on the accuracy of the input data. In particular, the temperatures of surfaces affected by nearby trees strongly depend on the spatial distribution of the leaf area density, land surface temperatures at grass surfaces strongly depend on the initial soil moisture, wall-surface temperatures depend on the correct setting of wall material parameters, and concentrations depend on detailed information on spatial distribution of emissions, all of which are often unavailable at sufficient accuracy. The study also points out some current model limitations, particularly the implications of representing topography and complex heterogeneous facades on a discrete Cartesian grid, and glass facades that are not fully represented in terms of radiative processes. Our findings are able to validate the representation of physical processes in PALM while also pointing out specific shortcomings. This will help to build a baseline for future developments of the model and improvements of simulations of physical processes in an urban environment.

Highlights

  • A majority of the world’s population live in large cities (55 % as of 2018), and this percentage is expected to grow (UN, 2019)

  • PALM Largeeddy simulations (LES) simulations driven by mesoscale Weather Research and Forecasting model (WRF) and CAMx simulations were performed for a real urban environment in Dejvice, Prague, the Czech Republic

  • The PALM model properly adjusts to the temporally evolving WRF and CAMx conditions and simulates the temporal evolution and daily amplitude of street canyon quantities in most cases, with some noticeable exceptions such as insufficient night-time cooling under some conditions

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Summary

Introduction

A majority of the world’s population live in large cities (55 % as of 2018), and this percentage is expected to grow (UN, 2019). The high level of attention currently being paid to the impact of climate change on urban areas is amply justified and is supported by many important studies and reports of global standing (IPCC, 2014a, b). This intensifying urbanization has heightened the awareness that control of the microclimate in the urban environment, which can reduce heat stress and prompt other general environmental improvements, is crucial for the well-being of city inhabitants (Mutani and Fiermonte, 2017). Researchers have responded to, or anticipated, such concern and the requirement for modelling of urban climate processes, and several small-grid-scale models and frameworks for numerical climate modelling have recently been developed (Geleticet al., 2018)

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