ERA5 is widely considered as a valid proxy of observation at region scales. Surface air temperature from the E-OBS database and 196 meteorological stations across Europe are being applied for evaluation of the fifth-generation ECMWF reanalysis ERA5 temperature data in the period of 1981–2010. In general, ERA5 captures the mean and extreme temperatures very well and ERA5 is reliable for climate investigation over Europe. High correlations ranging from 0.995 to 1.000 indicate that ERA5 could capture the annual cycle very well. However, the high mean biases and high Root Mean Square Error (RMSE) for some European sub-regions (e.g., the Alps, the Mediterranean) reveal that ERA5 underestimates temperatures. The biases can be mainly attributed to the altitude differences between ERA5 grid points and stations. Comparing ERA5 with the other two datasets, ERA5 temperature presents more extreme temperature and small outliers for regions southern of 40° latitude and less extreme temperatures in areas over the Black Sea. In Scandinavia, ERA5 temperatures are more frequently extreme than the observational ones.
Climate change has a major impact on the urban built environment, both with respect to the heating and cooling energy requirements, but also regarding the higher probability of confronting extreme events such as heatwaves. In parallel, the ongoing urbanization, the urban microclimate and the formation of the urban heat island effect, compounding the ongoing climate change, is also a considerable determinant of the building’s energy behavior and the outdoor thermal environment. To evaluate the magnitude of the complex phenomenon, the current research investigates the effect of climate change and urban heat island on heating and cooling energy needs of an urban building unit in Thessaloniki, Greece. The study comparatively evaluates different tools for the generation of future weather datasets, considering both statistical and dynamical downscaling methods, with the latter involving the use of a regional climate model. Based on the output of the regional climate model, another future weather dataset is created, considering not only the general climatic conditions, but also the microclimatic parameters of the examined case study area, under the future climate projections. The generated future weather datasets are then used as an input parameter in the dynamic energy performance simulations with EnergyPlus. For all examined weather datasets, the simulation results show a decrease of the heating energy use, an effect that is strongly counterbalanced by the rise of the cooling energy demand. The obtained simulation results also reveal the contribution of the urban warming of the ongoing climate change, demonstrating the need to perform a holistic analysis for the buildings’ energy needs under future climate conditions.
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