Advantages of using a fast urban boundary layer model as compared to a full mesoscale model to simulate the urban heat island of Barcelona

Abstract

Abstract. As most of the population lives in urban environments, the simulation of the urban climate has become a key problem in the framework of the climate change impact assessment. However, the high computational power required by high-resolution (sub-kilometre) fully coupled land–atmosphere simulations using urban canopy parameterisations is a severe limitation. Here we present a study on the performance of UrbClim, an urban boundary layer model designed to be several orders of magnitude faster than a full-fledged mesoscale model. The simulations are evaluated with station data and land surface temperature observations from satellites, focusing on the urban heat island (UHI). To explore the advantages of using a simple model like UrbClim, the results are compared with a simulation carried out with a state-of-the-art mesoscale model, the Weather Research and Forecasting Model, which includes an urban canopy model. This comparison is performed with driving data from ERA-Interim reanalysis (70 km). In addition, the effect of using driving data from a higher-resolution forecast model (15 km) is explored in the case of UrbClim. The results show that the performance of reproducing the average UHI in the simple model is generally comparable to the one in the mesoscale model when driven with reanalysis data (70 km). However, the simple model needs higher-resolution data from the forecast model (15 km) to correctly reproduce the variability of the UHI at a daily scale, which is related to the wind speed. This lack of accuracy in reproducing the wind speed, especially the sea-breeze daily cycle, which is strong in Barcelona, also causes a warm bias in the reanalysis driven UrbClim run. We conclude that medium-complexity models as UrbClim are a suitable tool to simulate the urban climate, but that they are sensitive to the ability of the input data to represent the local wind regime. UrbClim is a well suited model for impact and adaptation studies at city scale without high computing requirements, but does not replace the need for mesoscale atmospheric models when the focus is on the two-way interactions between the city and the atmosphere.

Spatial Variability of Heat-Related Mortality in Barcelona from 1992–2015: A Case Crossover Study Design

“…The UrbClim model was designed to simulate temperature and heat-stress at the city scale with a minimum amount of computation power [21]. This model is composed of a simple urban physics, coupled with a 3-D atmospheric boundary layer module.…”

“…UrbClim combines information about the urban structure (vegetation, soil sealing, typology, land use and land cover) through a simplified physics approach relevant at urban scales, and generates local climate data at very high spatial resolution of 100 m. The location and time were considered when climate data were extracted from the UrbClim model in order to merge with the georeferenced mortality dataset. The model has been previously validated in several validation campaigns, among which one has focused on the agglomeration of Barcelona [16,21,22]. Using the UrbClim model, daily urban climate data have been composed for all summer periods (1 June-30 September) of the years 1992-2015 ( Figure 1a).…”

“…There are a few limitations we faced in modelling the risk that merit discussion. Previous validation exercises have shown that UrbClim, coupled to reanalysis data, can sometimes show a little warm bias in the modeled air temperatures Therefore, it is important to recognize the specific limitations both in the analysis and the interpretation of results obtained by using model data [21,39]. The sociodemographic variables were derived from data available at a fixed point in time (the year 2012 until 2016).…”

A new method for fine-scale assessments of the average urban Heat island over large areas and the effectiveness of nature-based solutions

“…These simulations have been performed with the urban boundary layer climate model UrbClim , designed to cover agglomeration-scale domains at a high spatial resolution, taken as 250 m for this study. The model has been successfully validated regarding its calculated air temperatures and urban-rural temperature differences for a large number of cities throughout Europe , García-Díez et al 2016). These simulations have been performed in the framework of the European FP7 project RAMSES (www.ramses.eu).…”

“…Observational studies revealed that green areas are usually cooler than their surrounding built-up areas, with instantaneous air temperature differences of 1°C up to 7°C (Bowler et al 2010, Jamei et al 2016). Similar to parks, water features have the potential to alleviate high urban temperatures through enhanced evaporation and reduced sensible heat fluxes (Nishimura et al 1998, Coutts et al 2012).…”