urban development paths Current urban research results in NSP: Climate proof urban development paths next steps: quantifying all important socially specific vulnerabilities, impacts + adaptation options extent conceptual generic model to urban form relate structural parameters of urban change with heat wave and sea level rise vulnerability flooding after local heavy rain events orography and drainage localization/growth patterns of urban areas/ slum location density and land use structure resilience under local inundation exergy maps anthrop. pressure cities->earth system sea level rise low lying & coastal location dense and redundant transport net socially specific CC impact nets strong social differentiation rapid and global urbanization urban CC vulnerabilities Synergies conceptual generic model for urban regions

Endangered urban areas under extreme precipitation: flow accumulation Research results: Estimation of frequency increase of climate-change induced extreme precipitation events Orography-derived, remote Sensing based flow accumulation model Kit et al., 2010 Climate-proofing measures: Restriction of development in identified areas of high flow accumulation Preventive extension of drainage system Hyderabad, from 17 AOGCMs (Lüdeke et al., 2010)

City Clustering Algorithm Greater London administrative Results: based on population density administrative city cluster (Rozenfeld HD, Rybski D, PNAS 2008) Results: different definitions of cities affect statistical properties of urban activity Zipf's law holds over many decades scale-invariant growth features long-range spatial correlations in growth Climate-proofing: application of these structural properties to predict the cities vulnerability, e.g. towards heat waves or coastal floods targeted preventive action

Regional Urban Growth Patterns Annual growth: fastest in China (1.5-2%) and Latin America- 1%- both independent from density Europe: cities < 2 mln will grow: Less density - more growth potential China and Europe - same number of mega-cities Expect the number in China to increase 2-3-times Cities larger then 5 mln: each region different => global economy, not demography laws Disperse city-> lower emissions per area Compact city-> lower emissions per person. Svirejeva-Hopkins, 2010. “ City Size, Density and Sectoral Structure: exploring Urban Sustainability in the Regions. EGU

Slum areas endangered by flooding Research results: automatic slum area identification (lacunarity) from remote sensing (Bird Eye) for different time slices vulnerability of urban slum areas in Hyderabad towards heavy rain fall events Climate-proofing measures: Integration of slum identification procedures into urban planning process Inclusion of secure low cost housing in urban development plans Light to dark blue: water flows under heavy rain (flow accumulation). Green to red: vulnerability of urban slum areas in Hyderabad (Kit et al. 2010)

how far is the system from thermodynamic equilibrium with environment Anthropogenic Pressure of Cities on Earth System: Thermodynamic approach* Exergy: how far is the system from thermodynamic equilibrium with environment Index of anthropogenic disturbance: Anthropogenic heat flux / Exergy New York: 0.1 Moscow: 0.5 Seoul: 0.6 Index per individual- density/level of infrastructure. Exergy 0.57 W/m2 174.24 www.cgd.ucar.edu/tss/ahf/ Svirejeva-Hopkins, et al. 2010. “Mapping the state of city systems based on remote sensing. Exergy and sustainability of urban form”. UGEC, Arizona.

Rapidly urbanizing coastal areas in developing countries Research Result: Climate Proofing: Entry points for supporting climate proof development, depending on vulnerability profile: infrastructure sectors to concentrate on emphasis on deprived areas restoration of natural protection Kok/Lüdeke/Sterzel et al., in press 6 clearly separable clusters in 17-dim indicator space => different vulnerability profiles

Weather related impacts on different socio-economic groups and socially sensitive adaptation options Climate proofing (heat and rain events): Increasing the easiness of mobility better the living situation for both groups Wallahs: investment in health infrastructure better than in energy infrastructure City managers: the opposite Improvement of water supply and drainage infrastructure reduces ALL associated problems in traffic, water, economic and health situation for City managers and Wallahs Fuzzy Cognitive Maps (survey based) of weather impacts for different social groups Here: rain for Wallahs in Delhi (Reckien et al, in prep.) Rain events: Improvement (1) (2) (3) (4) (5) (6) Wallahs 2.8 2.2 5.5 1.5 2.1 1.1 City managers 1.6 2.7 0.9 1.0 Six improvement scenarios evaluated using the social group specific FCMs for heat and rain events: (1) Improvement of water and sewage infrastructure (2) Selfhelp solutions by working in the dark, repairing houses, private power generation (3) Increase the easiness of mobility (4) Investment in energy infrastructure and provision without and (5) with “private access” (6) Extension of health infrastructure

Urban Region Generic Model City Population: P Urban assets: U Urban area: Lu Immigration Emigration Imports Exports Non/Renewable Ecosystem Agriculture Services Energy Energy Ecosys. Assets E Natural area: LE Agri. Assets: A Agri. area: LA Etc. Etc. Approach Identification of general bio-physical key processes. Defining generic functionals and coarse variables. Dynamical systems representation ; Land use changes, resource exploitation, demographic growth and assets production. Objectives Developing insights into: Critical transitions along different climate scenario and socio-economic development paths. Shifts towards sustainable steady regimes. Resilience of desirable regimes. A. Garcia Cantu et al. (In preparation)