Validating the results of urban climate models with temperature data from personal weather stations

What is it about?

In this work, we used a numerical urban climate model to simulate the air temperature within the western German city of Bochum. A numerical urban climate model uses information about the urban structure such as buildings, trees and surfaces combined with meteorological data like wind speed, air temperature and humidity to calculate the thermal conditions in a city on a very detailed level. As models are always are simplification of the real world, it is important to check the results with measurement data. Air temperature data from private weather stations anyone can install in their garden or on the balcony was used to validate our model results. The validation reveals that the applied model can accurately model the air temperature within a city. Furthermore, the air temperature data from personal weather stations proved valuable for the validation as there are many stations available in cities.

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Photo by Markus Spiske on Unsplash

Photo by Markus Spiske on Unsplash

Why is it important?

Due to climate change, heat events have become more frequent and intense. This leads to heat stress especially in cities and can negatively impact human health. The most vulnerable groups are the ederly, children and people with pre-existing conditions. Adapting our cities to a changed climate, for example with more green spaces, can reduce the risks of heat stress. To efficiently plan where to apply adaptation measures, city planners require detailed information on risks areas and the potential of adaptation measures to reduce heat stress. Urban climate modelling can fulfill this tasks. However, model results should always be validated. Weather stations operated by national weather services are often not within cities. On the other hand, many private weather stations are present in cities. This work is important as it combines two efficient tools in urban climatology: modelling and crowdsourcing. Both tools are freely available and can generate validated information on the thermal conditions within cities and therefore on risks areas when it comes to heat stress.

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