WRF4G: WRF experiment management made simple

Fernández-Quiruelas, V.; Fernández, Jesús Fernández; Cofiño, Antonio S.; Blanco, C.; García-Díez, Markel; Magariño, María Eugenia; Fita, L.; Gutiérrez, José Manuel

doi:10.5194/gmdd-8-6551-2015

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…Although the magnitude of the UHI effect does not necessarily increase due to global warming (Lauwaet et al, 2015), it has been shown to be large enough to potentially have significant impacts. The most important ones are human health, through heat stress (Gabriel and Endlicher, 2011;Dousset et al, 2011) and energy consumption (Kikegawa et al, 2006;Kolokotroni et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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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.

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