Regional climate model assessment of the urban land-surface forcing over central Europe

Abstract

Abstract. For the purpose of qualifying and quantifying the climate impact of cities and urban surfaces in general on climate of central Europe, the surface parameterization in regional climate model RegCM4 has been extended with the Single-layer Urban Canopy Model (SLUCM). A set of experiments was performed over the period of 2005-2009 for central Europe, either without considering urban surfaces or with the SLUCM treatment. Results show a statistically significant impact of urbanized surfaces on temperature (up to 1.5 K increase in summer) as well as on the boundary layer height (increases up to 50 m). Urbanization further influences surface wind with a winter decrease up to −0.6 m s −1 , though both increases and decreases were detected in summer depending on the location relative to the cities and daytime (changes up to 0.3 m s −1 ). Urban surfaces significantly reduce the humidity over the surface. This impacts the simulated summer precipitation rate, showing a decrease over cities of up to −2 mm day −1 . Significant temperature increases are simulated over higher altitudes as well, not only within the urban canopy layer. With the urban parameterization, the climate model better describes the diurnal temperature variation, reducing the cold afternoon and evening bias of RegCM4.Sensitivity experiments were carried out to quantify the response of the meteorological conditions to changes in the parameters specific to the urban environment, such as street width, building height, albedo of the roofs and anthropogenic heat release. The results proved to be rather robust and the choice of the key SLUCM parameters impacts them only slightly (mainly temperature, boundary layer height and wind velocity).Statistically significant impacts are modelled not only over large urbanized areas, but the influence of the cities is also evident over rural areas without major urban surfaces. It is shown that this is the result of the combined effect of the distant influence of the cities and the influence of the minor local urban surface coverage.

On the long-term impact of emissions from central European cities on regional air quality

“…It indicates a negative model bias, which is highest in spring (around −1 to −2 K over large areas) and lowest in summer (0 to −1.5 K). This is attributable to overestimated cloudiness in RegCM, as already concluded by Huszar et al (2014), who used the same model and set-up. Over mountainous areas like the Alps, southeastern Carpathians, biases reach values from −5 to 5 K, however, this is most probably related to coarse model representation of specific terrain features (valleys, ridges etc.)…”

“…In this study, the BATS scheme is activated. The single layer urban canopy model coupled to RegCM4.2 introduced by Huszar et al (2014) was not applied assuming that the urban-meteorological influence on the emissions impact will be minor and furthermore, to meet the computational demand of long climate simulations.…”

“…These were built according to the administrative borders of the particular city in combination with the subgrid urban landsurface data used in Huszar et al (2014), originally extracted from the Corine2006 database (EEA, 2012). The selection of certain cities, in general, comprises cities considered to be large within the particular region.…”

“…Previously, Huszar et al (2014) presented the impact of urban landsurface forcing on climate. Here, we link it to this study and look at a further aspect of the urban impact on environment: we aim to provide a chemistry transport model-based estimate of the long-term impact of emissions from cities in central Europe on the regional air quality.…”

Analysis of the Temporal and Spatial Distribution of Haze and its Influencing Factors in Shanghai

“…Simulations of winter weather conditions and air quality for central and southeastern Europe by [23] demonstrated that climate change will be followed by deteriorated air quality, not only due to potentially increased O 3 concentrations, but also as a result of an expected growth in SO 2 concentration levels, with relatively low changes in PM 10 concentrations. Methods for tackling these negative trends include restructuring of urban space and amelioration of the tropospheric climate of the city.…”