Applying urban climate model in prediction mode\u2014evaluation of MUKLIMO_3 model performance for Austrian cities based on the summer period of 2019

Brigitta Hollósi,Astrid Kainz,Maja Žuvela-Aloise,Wolfgang Schöner,Sandro Oswald

doi:10.1007/s00704-021-03580-6

Brigitta Hollósi, Astrid Kainz + Show 3 more

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https://doi.org/10.1007/s00704-021-03580-6

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Abstract

Extreme heat events are natural hazards affecting many regions of the world. This study uses an example of the six largest cities in Austria to demonstrate the potential of urban climate model simulations applied in prediction mode providing detailed information on thermal conditions. For this purpose, the urban climate model MUKLIMO_3 of the German Meteorological Service (DWD) coupled with the hydrostatic numerical weather prediction model, ALARO, is used to simulate the development of the urban heat island (UHI) in Austrian cities for the summer period of 2019 with a horizontal resolution of 100 m. In addition to the evaluation of UHI predicting skills, other relevant variables, such as humidity and wind characteristics on hourly basis, are also analysed in this paper. Model evaluation confirmed that the MUKLIMO_3 microscale model had the capacity to simulate the main thermal spatiotemporal patterns in urban areas; however, a strong dependence on the input data from the mesoscale model was found. Our results showed large benefit in prediction of maximum air temperatures in urban areas, while the relative humidity predictions of MUKLIMO_3 appear to be much less plausible and show large variety of model prediction skills. Urban climate model simulations using real atmospheric conditions can facilitate better quantification and understanding of day-to-day intra-urban variations in microclimate as well as provide a basis for evaluation of the microclimate prediction skills of mesoscale numerical models with urban extensions.

Highlights

In recent years, much attention has been focused on urbaninduced and urban-modified weather and climate
The hourly outputs of high-resolution MUKLIMO_3 3D fields on near-surface level (2 m) were compared with air temperature and humidity measured at 2 m height and wind speed and direction measured at 10 m height at the semiautomatic weather stations, TAWES (GCOS Austrian Inventory Report 2017), of the cities
The hourly forecasts (0600 + 0001 to 0600 + 0024 UTC) of the numerical weather prediction (NWP) model ALARO were considered in the analysis in order to evaluate the benefit of UCM application and to determine model dependences

Summary

Introduction

Much attention has been focused on urbaninduced and urban-modified weather and climate. In order to increase the resilience of cities to current and future extreme heat events and to reduce the negative impacts on public health and urban systems, comprehensive urban planning and risk management strategies have to be developed. Following this approach, WHO and WMO have strengthened their cooperation and co-published the guideline “Heatwaves and Health: Guidance on Warning-System Development” that outlines the main aspects of heat warning system developments and presents a comprehensive analysis on definitions and methodologies and communication of warnings and planning strategies for managing heat events (WMO and WHO 2015). After the 2003 heat wave, most European countries began to develop and implement early warning systems (Lowe et al 2011; Casanueva et al 2019)

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