They are invisible and often unrecognized. Nevertheless, heat waves pose a serious threat to human health, especially for children and the elderly. While heat waves gain relatively little public attention, they are one of the most severe natural disasters worldwide and cause casualties and illnesses. Heat waves affect particularly regions where high temperatures occur infrequently, so the population is consequently not well prepared for the heat. For example, the heat wave in 2003 in Europe is statistically related to about 40,000 deaths (García-Herrera et al. 2010). (For comparison: Around 54,000 people died in traffic accidents in the same year in Europe.) Heat waves, however, only seldom cause deaths directly (e.g. through heatstroke), but they worsen already existing health issues, such as illnesses of the respiratory or the cardiovascular system. With the global climate change, grave heat waves will occur more frequently and intensely. Hence, both the Intergovernmental Panel on Climate Change (IPPC http://www.ippc.ch/) and the Sustainable Developments Goals (SDGs) point out the need for public authorities to target the ongoing global climate change and for the population to adapt to the changing situation
Fig. 1 - How to combat heat stress in Seoul? Identify sites with high heat-stress risk, vulnerability or hazard, and implement site-specific measures.
But how can we adapt to heat stress? To answer this question, decision-makers need not only to know about effective adaptation measures, but also where exactly heat stress occurs. Particularly cities are affected by heat waves, because they are home for the majority of all people – more than half of the world population is living in cities. In many countries, such as Germany or Korea, the fraction of the urban population is even more than 80%. Moreover, in cities an urban heat island establishes, thereby additionally increasing the air temperature. Cities such as Berlin and Seoul are, during cloudless nights with low wind speed, up to 7 to 10℃ warmer than their rural surroundings. The lower fraction of vegetation and the higher area of sealed surfaces in cities cause the urban heat island effect. Thus, the cooling evapotranspiration decreases and the heat of the day is stored in the buildings and released during the night. This can have serious implications during heat waves. When the temperature is up to 10℃ higher than average, the cities remain too hot to find the needed recovery during the night-time, while in the rural surroundings a good sleep is possible. Moreover, also poor sleep quality has been associated with the worsening of several illnesses.
I already identified cites as particularly heat-prone areas. But even within cities urban planners need to know where exactly, e.g. in which districts or neighborhoods, the heat-stress risk is high (see Ren et al. 2011). Identifying those areas is not an easy task since cities are a complex mosaic of different pieces. Within a small distance, we can find different urban structures such as vegetation, buildings, and parking lots. Moreover, the population is spatially differentiated in cities. In some areas there are more families with vulnerable children, in other districts more elderly people. Consequently, the heat-stress risk is spatially varying, such as the number of emergency interventions and hospitalization as well as heat-related mortality. All of these pieces form a mosaic showing the heat stress risk in a city.
In a recent study (preview: Jänicke et al. 2017), I considered all these components and their spatial variability for the city of Seoul. For describing the spatial patterns of buildings and green spaces, I used air temperature simulated by urban climate models. The heat-stress risk is represented by heat-related mortality. And for describing the spatial pattern of heat-stress vulnerability, I used an index called the heat vulnerability index, which summarizes different factors like age and socioeconomic status. With these data, I can now identify the areas in the city that are particularly affected by heat stress. I can also detect the cause of the heat-stress risk and find out if it is either the extremely air temperature or the vulnerable population.
At the Korean Weather Service (National Institute of Meteorological Science) my colleagues and I already implemented a high-resolution heat-wave forecasting system for the city of Seoul. The system provides high-resolution maps of expected air temperature and heat-stress risk at 25 m resolution, and provides guidance for forecasters when issuing heat-stress warnings. Moreover, the maps highlight the districts with the highest air temperature due to the urban heat island. In these districts countermeasures to reduce the urban heat island would be beneficial. These countermeasures include increasing the vegetation amount with parks, façade, or roof greening. Also, reflective roofs which decrease the heat storage and therefore the heat stress in buildings are helpful. Water pounds have also been found to reduce the urban heat island. In districts with high heat-stress vulnerability measures can focus on the vulnerable population by providing cool shelters, increasing awareness of the topic and special care for the elderly. Institutions such as retirement homes or daycare centers with particularly vulnerable inhabitants can be provided with heat-stress warnings.
This new knowledge about the location of heat stress within the urban mosaic is important to protect cities better against heat waves in the future. Given the ongoing urbanization and climate change, such knowledge is needed to foster the implementation of adaptation measures and thus to contribute to achieving the SDGs.
García-Herrera R, Díaz J, Trigo RM, Luterbacher J, Fischer EM (2010) A review of the European summer heat wave of 2003. Crit Rev Environ Sci Technol 40:267–306. doi.org/10.1080/10643380802238137
Jänicke B, Holtmann A, Kang M, Kim KR, Scherer D (2017) Towards high-resolution heat-stress maps for Seoul, Korea: Hazard, risk, and vulnerability. 21st Int Congr Biometeorol Ext Abstr S1.3:29–33.
Ren C, Ng EY, Katzschner L (2011) Urban climatic map studies: a review. Int J Climatol 31:2213–2233.