Use for Adaptation Selected Examples

There are numerous epidemiological studies published which impressively show worldwide the health impact of extreme thermal conditions such as heat waves. Figure 2.5 shows as an example a detail of the daily mortality rate time series from south-west Germany that includes the hot summer 2003 (Schar and Jendritzky 2004). During this summer about 55,000 extra deaths attributable to heat occurred in Europe, and from these about 35,000 alone in August (Brucker 2005; Kosatsky 2005). Neither the NMSs nor the public health systems were sufficiently prepared.

11.4.02

20.7.02

28.10.02 Date

16.5.03

24.8.03

Fig. 2.5 Daily total mortality rates (MR) in SW - Germany. Smoothed line, i.e. expected value (EW_tot) based on Gauss-Filter. Evident: MR peak in June 2002 (short heat wave), episode in spring 2003 (related to an influenza epidemic), peaks in July and the August heat wave effect (Schär and Jendritzky 2004)

11.4.02

20.7.02

28.10.02 Date

16.5.03

24.8.03

Fig. 2.5 Daily total mortality rates (MR) in SW - Germany. Smoothed line, i.e. expected value (EW_tot) based on Gauss-Filter. Evident: MR peak in June 2002 (short heat wave), episode in spring 2003 (related to an influenza epidemic), peaks in July and the August heat wave effect (Schär and Jendritzky 2004)

When considering the impact of the hot summer 2003 numerous questions arise, such as:

1. There is no general accepted definition of a heat wave. A conceptually adequate definition must be based on the physiological response, see Eq. (2.1).

2. There is no consensus on the definition of the mortality baseline. In Fig. 2.5 a time series filtering approach is used rather than just calculating monthly mean values.

3. There is no idea about the actual heat exposure of the population in different floors of different buildings in urban areas when applying meteorological data from usually rural measuring sites. It can be assumed that the urban heat island effect (UHI) has intensified the regional heat load. But how many?

Based on a climate change simulation with HIRAM (Beniston 2004) the distribution of the maximum temperatures of the summer 2003 (Fig. 2.6) indicates that - if the prediction were correct - this extreme summer is expected to be a fairly normal regular occurrence by the end of this century in Central Europe! This is basically compatible with the change of the annual mean of Perceived Temperature PT in a future climate (2041-2050) in central Europe compared to the control run (19711980), which here is taken as the "actual" climate, based on the MPI time-slice experiment with ECHAM4 in T106 resolution, assuming the "business-as-usual" scenario IS92a (Fig. 2.7a, b). The need for adaptation is evident. Short-term (I) and long-term (II) adaptation measures are crucial.

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