THE NORTH-RHINE WESTPHALIA STUDY 1. Introduction in Spite Of

SEMIQUANTITATIVE ASSESSMENT OF REGIONAL CLIMATE VULNERABILITY: THE NORTH-RHINE WESTPHALIA STUDY J. P. KROPP1, A. BLOCK1, F. REUSSWIG1, K. ZICKFELD1, and H. J. SCHELLNHUBER1,2 1Potsdam Institute for Climate Impact Research P.O. Box 60 12 03, 14412 Potsdam, Germany E-mail: [email protected] 2Tyndall Centre for Climate Change Research University of East Anglia, Norwich, NR4 TTJ, UK Abstract. Climate change will bring about a sea change in environmental conditions worldwide during the 21th century. In particular, most of the extreme events and natural disaster regimes prevailing today will be transformed, thus exposing innumerable natural and socio-economic systems to novel risks that will be difficult to cope with. This crucial component of vulnerability to anthropogenic interference with the climate system is analyzed using powerful pattern recognition methods from statistical physics. The analysis is of intermediate character, with respect to spatial scale and complexity level respectively, and therefore allows a rapid regional assessment for any area of interest. The approach is based on a comprehensive inventory of all those ecological and socioeconomic assets in a region that are significantly sensitive to extreme weather (and climate) events. Advanced cluster analysis techniques are then employed to derive from the inventory a set of thematic maps that succinctly summarize – and visualize – the differential vulnerabilities characteristic of the area in question. This information can prepare decision makers and the general public for the climate change hazards to be faced and facilitates a precautionary climate change risk management. The semiquantitative methodology described and applied here can be easily extended to other aspects of climate change assessment. 1. Introduction In spite of the many new observations provided by the Third Assessment Report (TAR) of the Intergovernmental Panel on Climate Change (IPCC), it has become clear that climate change science has still a very long way to go. In particular, the TAR was not really able to present any formal analysis of differential geographical vulnerability to anthropogenic global warming and the concomitant transformation of environmental conditions at large. Vulnerability defined by the IPCC as the degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change. It is a function of the climate-related stimuli to which a system is exposed, its sensitivity and its adaptive capacity (Cutter, 1996; McCarthy et al., 2001). Although the precise definition of vulnerability is still a matter of debate between distinct schools (for a detailed discussion, see Füssel and Klein (2005) and the references therein) climate policy makers would actually be highly interested in learning from the scientific community which regions (or even sub-regions) Climatic Change (2006) 76: 265–290 DOI: 10.1007/s10584-005-9037-7 c Springer 2006 266 SEMIQUANTITATIVE ASSESSMENT OF REGIONAL CLIMATE VULNERABILITY of our planet are most likely to be endangered by climate change – in order to activate coping capabilities and to negotiate for compensation measures as soon as possible. As a matter of fact, the entire issue of sustainable development outside the industrialized countries will crucially depend on such information. Why is this body of evidence not yet available? There are three major obstacles to be overcome: first, adaptation research has not yet reached a stage that allows the numerical derivation of coping capacities from basic socio-economic indicators like GDP or certain infrastructural data (Klein et al., 1999; Smit et al., 2000). Second, the available collection of climate impact studies is – geographically and topically – highly fragmented. Moreover, there exists no harmonized calibration with respect to common scenarios for social driving forces (Nakicénovic and Swart, 2000) and for the resulting transformations of atmospheric concentrations (Covey et al., 2003). Third, it is quite difficult to identify – and to establish – the “right” degree of formal complexity for a vulnerability analysis based on expert judgment (see the classic study by Morgan and Keith, 1995). Several attempts to generate differential vulnerability maps were made during the recent TAR process, but not released for publication due to their premature character. There are, on the other hand, elaborate studies that try to account for all possible costs and benefits of climate change including all conceivable mitigation and adaptation measures. Most results of this approach are published in the so- called “integrated assessment” literature (cf. Parson, 1995; Schneider, 1997; IPCC, 1997; Rotmans and Dowlatabadi, 1998; Schellnhuber, 1998; Tóth and Hizsnyik, 1998; Lorenzoni et al., 2000; Aggrawal and Mall, 2002). But even if these attempts succeeded in reflecting reality appropriately (by accounting also for non-market values, extreme weather events or large-scale geophysical discontinuities (Smith et al., 2001)) it would be unfeasible to carry out this type of analysis in comparative depth for all regions, or even sub-regions, of the world. Therefore, it seems reasonable to settle for an intermediate level of complexity (see, e.g., Tóth and Hizsnyik, 1998). A semi-quantitative approach to vulnerability assessment (i) should be apt to consider the crucial vulnerability inventory of a given geographical region, (ii) should be applicable to any region of the world, in principle, and (iii) should allow for quick (and moderately “dirty”) integration of rough numerical indicators of adaptive capacity. In this paper, we demonstrate this approach by presenting a model case study for the German state of North-Rhine Westphalia (NRW) (see Figure 1), which illustrates the application of modern data- processing methods for deriving a geographically explicit vulnerability classification on the community level. This classification is well-defined and rigorous, yet transforms away most of the complex details contained in the empirical information input. As a consequence, the resulting vulnerability ranking of subregions is quite robust with respect to imprecisions and uncertainties associated with the data-base. Our approach also differs from the majority of previous vulnerability studies by focusing on extreme weather events rather than on smooth modifications of J. KROPP ET AL. 267 Figure 1. North-Rhine Westphalia (NRW) and its location in Europe (red inset). NRW is the study region and the most populous state of Germany (≈18 Mio. residents in 2004, 34,070 km2). The red squares denote the district capitals. NRW comprises 396 communities with rural, rangy, peri-urban, or urban characteristics. The latter type of community mainly located in the Ruhr basin (Duisburg- Essen-Dortmund axis). mean values of crucial climate parameters. Researchers have emphasized time and again the importance of “singular” phenomena for evaluating the real risks associated with anthropogenic climate change (Nordhaus, 1994; Schneider, 1996; Smith et al., 2001), but little progress has been made so far to incorporate these singularities in cost-benefit or proper vulnerability analysis (cf., for example, Subak et al., 2000; Azar and Schneider, 2002). This is deplorable because global warming is likely to modify the probability distributions for extreme events (storms, heavy precipitation, droughts, etc.) considerably (Trenberth, 1999), and may even bring 268 SEMIQUANTITATIVE ASSESSMENT OF REGIONAL CLIMATE VULNERABILITY about abrupt regional or global changes in the present mode of operation of the ecosphere machinery (Schellnhuber, 1999). The pace of climate change and the increased intensity of extreme weather events push us to the limits of adaptive capacity for the future. Although it is rather difficult to determine local vulnerability, there exists sufficient evidence that a variety of assets located in densely populated areas could be affected most seriously (MunichRe, 2003). It is, of course, a formidable scientific task to estimate the possible damages that might arise for ecological and socio-economic systems by irregular events accompanying climate change in these areas (for a review see, for instance, Kunkel et al., 1999). The associated impacts are generally unevenly distributed among social structures and economic sectors (Kasperson et al., 1996). The values at stake do not only refer to markets assets, but also to ecosystem functions, human well-being, and sociopolitical stability. The standard items to be considered sensitive to climate functions are agricultural yields, traffic capacities, human settlements, energy production systems, etc. (Renn, 1992). Evidently, a long-term forecast of individual meteorological hazards in unfeasible. A systematic investigation of the sensitivity of a given exposure unit with respect to a statistical ensemble of singular events can be performed, however. In a similarly averaging way, the adaptive capacities of the exposure units can be assessed quite satisfactorily. In the following, we will use a neural networks approach (Kohonen, 2001) for establishing a climate vulnerability typology for North-Rhine Westphalia (NRW) (Figure 1), which provides an integrated ranking of the communities of this state. 2. Analyzing Climate Vulnerability by Indicators of Varying Complexity As a basis for this vulnerability assessment we carried out a systematic stocktaking of all conceivable types of damage caused by extreme weather events (see Table I) such as heat waves, cold spells,

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