Keywords

Introduction

Urban areas are very vulnerable to climate change impacts, because of the high concentration of people, infrastructure and economic activity but also because cities tend to exacerbate climate extremes such as heat waves and flash floods. In addition, the ongoing urban expansion and the ageing of the urban population makes them particularly vulnerable. European cities are home to about 75% of the population, projected to grow to 80% in 2050. The objective of the Climate-fit.City service was to establish a service that translates the best available scientific urban climate data into relevant information for public and private end users operating in cities.

Urban areas shape their own climate, amplifying climate extremes such as excessive heat and flooding. Lauwaet et al. (2015) demonstrated that, because of the urban heat island effect, cities experience twice as many heat wave days than their rural surroundings. Moreover, towards the end of the century, the number of urban heat wave days is expected to increase by a factor of 10, from approximately 3 to 30 days per year at the end of the century under IPCC scenario RCP8.5. With respect to water, the abundance of impermeable surfaces in cities leads to inundations that are often far more intense than those occurring in rural areas (Willems et al. 2012), damaging property and infrastructure and causing economic losses arising from disrupted transportation networks.

In view of the ongoing and projected climate change, urban areas need to set up adaption processes to become less sensitive to the negative impacts of climate change. This transformation needs to be cross-sectorial as climate impacts many urban activities that are linked to each other. In this paper, we will start by describing how Climate-fit.City supports urban adaptation and its data processing methodology (Sect. “Climate-Fit.City Data”) followed by a brief presentation of the Climate-fit.City service components (Sect. “Climate-Fit.City Services”) and a brief reflexion on the use of the Climate-fit.City data and services and the impacts that it generates (Sect. “Conclusions”).

Climate-Fit.City Data

The Climate-fit.City partners want to help cities and urbanized regions manage current and future climate impacts. The diverse consortium of climate experts, thematic sectorial experts, socio-economic experts and a professional communication partner work together with city officials to gather and integrate climate data to get a clear view of specific local challenges and co-design solutions to them. The Climate-fit.City team helps cities through the process, supports stakeholder engagement and has expertise in socio-economic impact assessments and policy design including communicating of climate impacts to citizens. The Climate-fit.City modular approach offers expertise in the following urban sectors: active mobility, building energy, emergency planning, heat and health, leisure and tourism and urban planning (Fig. 13.1). We will use results created inside the H2020 Climate-fit.City project (2017–2020) to demonstrate service components.

Fig. 13.1
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Overview of Climate-fit.City cases worked out during the H2020 Climate-fit.City project

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Users of the Climate-fit.City service are on the one hand urban administrations/institutions and on the other hand territorial entities as well as private companies supporting cities by providing customized information and services to:

  • define the climate change risk by mapping and quantifying diverse impacts which increases visibility, awareness and ownership of the adaptation challenge at both the policy and citizen levels;

  • support the development and adoption of adaptation strategies and actions plans;

  • quantify socio-economic impacts of adaptation and policy support.

Climate-fit.City services are based on downscaled large-scale climate information at the city scale which is used by sectorial experts to create added value urban climate information (Fig. 13.2).

Fig. 13.2
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Data flow inside Climate-fit.City. Large-scale climate information is taken from the Copernicus Climate Change Service (C3S)

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Primary urban climate data is delivered by VITO and KU Leuven. VITO focuses with its urban climate model UrbClim (De Ridder et al. 2015) on heat stress and related meteorological variables and indicators, while KU Leuven applies its rainfall downscaling statistics methodology to focus on precipitation and flooding.

The urban boundary layer climate model UrbClim is designed to cover individual cities and their nearby surroundings at a very high spatial resolution (De Ridder et al. 2015). UrbClim consists of a land surface scheme, coupled to a three-dimensional (3D) atmospheric boundary layer module. A schematic representation of the UrbClim model is presented in Fig. 13.3. For all simulations, the model is set up with a spatial resolution of 100 m. For the historical (reference) simulations, the model is driven with meteorological data from the Copernicus Climate Change Service. Model configuration is based on Copernicus land cover data combined with local urban datasets in case end users have high-quality local data. Urban climate data (air temperature, humidity, wind speed) allows to derive urban maps for climate hazards tailored to different sector needs such as heat wave days, cooling/heating degree days, tropical nights, urban heat island intensities, temperature statistics, etc.

Fig. 13.3
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Schematic overview of the UrbClim model (left) and the generation of extreme rainfall maps and climate scenarios (right)

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Urban climate data is further post-processed in combination with 3D building and tree data into 1 m resolution human comfort indices for human heat stress assessments at the scale of the urban agglomeration, around specific urban locations (e.g. touristic sites, urban zoo, public squares), to evaluate different urban project scenario’s (e.g. greening) or to estimate the impact of heat stress on outdoor labour productivity (Lauwaet et al. 2020).

The generation of extreme rainfall maps and climate scenarios is based on a method of statistical downscaling (Willems and Vrac 2011; Willems et al. 2012) where all publicly available global and regional climate model outputs are considered and downscaled to the local scale of the city (Fig. 13.3). Local time series of measured precipitation intensity available for specific locations in Europe (i.e. cities) are perturbed according to climate change signals obtained from the climate model outputs (Hosseinzadehtalaei et al. 2017, 2018, 2020).

More details about the generation of the current and future primary urban climate data are documented in the Climate-fit.City deliverable 5.2 (available in the resource section of the project website https://www.project.climate-fit.city/). All data generated for the case study cities is freely available for download on https://www.dataplatform.climate-fit.city/.

Climate-Fit.City Services

Human activities are heavily impacted by thermal stress. During extreme heat waves, there is an uneven amplification of thermal discomfort inside the cities that leads to even higher impacts, increasing human mortality. Moreover, global climate projections consistently point towards an increase of the number, duration and intensity of heat waves (Vogel et al. 2017). Extremely hot summers such as in 2003 in Europe are likely to become fairly common towards the end of the century. Extreme heat causes direct impacts on human health due to increased mortality, discomfort and mental illnesses but also indirectly through the advance of tropical disease vectors and the deterioration of air quality. Moreover, it also reduces outdoor and indoor labour productivity, increases energy consumption for air conditioning (for human comfort but also to avoid, e.g. server and other IT infrastructure overheating), deteriorates transport infrastructure (e.g. rail buckling, road asphalt warps and melts) and impact eco-systems. Finally, it leads to lower agriculture production, makes cooling of energy production more difficult and even reduces airfreight cargo (weight limit at take-off is reduced in case of very warm air temperatures). Within Climate-fit.City, demonstrations have been worked out on the impact of heat for active mobility (focus on cycling), human health (heat–health mortality), building energy demand/indoor comfort, urban spatial planning and urban Zoo management.

Besides the heat related services, Climate-fit.City also demonstrated the use of urban pluvial flooding risk maps for climate change resilient emergency management. Finally, all services are co-designed with urban end users. An overview is given in Table 13.1.

Table 13.1 Climate-fit.City services
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Conclusions

The socio-economic impact assessment performed in the Climate-fit.City project found that diverse actual and potential added values exist in terms of public service effectiveness, economic impacts, policy impacts and raising awareness impacts (e.g. improve bike paths by accommodating climate needs, increase bike use and reduced carbon emissions, reduction of deaths attributable to heat waves and health cost reduction, support a revision of existing building and built environment policies, improve communication around heat-related issues, updating building policies and standards at national and local level, better allocate emergency flooding equipment, support zoo management in properly managing of energy investments, etc.).

Along the project, it has also been confirmed that the urban climate services represent a relevant tool that can provide scientific support, for example, through their maps, data and climate scenarios, that can lead to potential improvement of the effectiveness into a range of public services. On this regard, the climate services proved to potentially provide a relevant support for the development of evidence-based urban policies.

Urban climate data delivery is globally guaranteed by using satellite-based land cover, building, soil and vegetation data. However, the applicability of the sectorial service components depends on the availability of input data, for example, the heat–health service requires high-resolution mortality data. Actually, service demonstrations use separate online tools. Future potential improvements could be to integrate all components inside one service platform.

To conclude, we want to highlight the integrated nature of the Climate-fit.City service. All service components are using the same urban climate data which streamlines the application of multiple services and, secondly, the large variety of sectoral applications supports the involvement of many urban actors which is found to be a barrier in urban adaptation. Mostly, climate adaptation is seen as a responsibility of the energy, climate and environment departments which leads to reduced interest from other urban departments. Climate-fit.City provides an integrated perspective reaching out to other departments as health, mobility, urban planning and green infrastructure as well as emergency planning departments.