Assessment of regional climate vulnerability in Germany and the

policy science interactionJürgen P. Kropp

Potsdam Institute for Climate Impact Research (PIK) Head North-South Theme (www.pik-potsdam.de/nsp)

Team: M. Lüdeke, D. Reckien, H. Förster, T. Grothmann, L. Costa, T. Sterzel, O. Roithmeyer, A. Holsten, M. , C. Walther, V. Tekken, T. Lissner, S. Ritchie, T. Weiss, C. Pape, M. Moneo, D. Rybski, I. Niemeyer, M. Wrobel, O. Kit, M. Budde, S. Hofmann, N. Lux, S. Kriewald, J. Kossak, N. Protze , M. Böttle, P. Pradhan, J. Briganti, M. Röse, S. Fabri, R. Moreaux, M. Röse

„Negative

Emissions“

Peaking of Emission beyond 2020: > 1x Kyoto/yr

Source: after Meinshausen et al. 2009/PIK

Temperature guardrail: 2 °C - 2100, < 0.2°C/yrActual +0.8 °C, at least 0.4 °C in the “pipeline”0.2 °C we have approx. approached!

2°

2Gt/cap/yr!0.1 Gt/cap yrPoorest 3527 Gt/cap yr US

What are the difficulties?

Science and policy/decision makers have different “styles of thinking”:

• Science is interested in systematic analysis of mechanisms and functions, or in other words science seeks for the “thruth”

• Policy/decision makers are interested in concrete problem solving and do not want too much about the background

“Climate Change” is increasingly misused for labeling of anyway necessary action

Science cannot (yet) solve problems and political aims of policy makers, we can make rough suggestions.

Impact analyses are hardly comparable, cause institution use different scenarios

Height (in m)

Cities

Rivers

Admin. districts

Example: North-Rhine Westphalia

22 % (18 Mio.) of total population of Germany

26 % forests, 50 % agriculture Ca. ¼ GDP

4 PIK-Studies:NRW I Study (1998-1999) Regional climate scenarios NRW (2004-2006)NRWII Study (2008-2009) ESPON-CLIMATE case study (2008-2011)

Integrated, by usage of non-linear classifiers

Integrated Vulnerability: NRW I (1998)

Kropp et al. 2006, Climatic Change

396 communities24 indicatorssocietyeconomytourismecosystems

Insufficient, cause sectoral focus is not visible, no cause effect chain, etc.Retrieval for methods

Source: Kropp et al. 2006, Climatic Change

Source: Kropp et al. 2006, Climatic Change

Sectorale Vulnerability 1999 Stimulus: stormsExposed unit: forestry; Indicators: tree types, slope, relativeStrom frequency

Actual damage 2007 > 19 Mio m3

Regional Distribution of Functional City Types

#1: Industrial Centres (mainly Rhine-Ruhr basin)

#2: Recreation Regions

#13: Suburbs and Low Diversified Cities

#24: Rural Communities

Kropp et al. 2006, Climatic Change

North-Rhine Westphalia18 m residents, 34.000 km2, 397 communities, 25% GDP

Neuronal Network Approach, 24 input variables(Source: Kropp et al. 2006/PIK)

Deterministic and sectoral, by review of literature,

and “distillation” of relevant mechanism,in particular, what are the drivers of risk!

Inclusion of climate scenarios in sectoral approaches

Mandatory: Comparisoncf. models scenarios, e.g.CCLM/STAR for NRW z.B. Annual mean T: C-CLM is too cold! (A1B)

Source: Kropp , Holsten et al. 2009

Health Risk related to heat waves(time demand 6 man month)

Increase in number and duration of heatwaves (CCLM, scenario A1B)

Densely populated areas, in particular in the Rhine-Ruhr basin and in the large cities alog the river rhine, cause number and temperature could become very high.

Heatwaves

Example Rhine valley/ Cologne Bight:

Amount of heatwaves Duration in days

Source: Kropp , Holsten et al. 2009

Health Risks in Urban Agglomerations

Health Risk - Vulnerability

Change

Change

Vulnerability a), b)Very smallSmallMediumHighVery high

Unch.Slight changeMedium changehigh changeVery high change

Comparative analysis by an indicator-based fuzzy model

e.g. sealed surface, amount of elderly people, demographic & regional scenarios,...

will become not only for densely populated areas a problem

Source: Lissner & Kropp 2008

Storm risk

Tree types Topography

Strom frequency Soil types

corniferousdeciduous

mixed

Risk categoryNo data Very lowLowMediumHighVery high

Change of storm days %

Analysis of mechanisms, e.g. what are the

determinants of risk?time demand 3.5 man month

Source: Kropp , Klaus, Holsten 2008

Once again: climate related drivers(time demand 4 man month)

from here input for otherquestions, e.g. cooling demand for power plants….

Transpiration

Precipitation

run-off mm/yr

groundwater recoverage mm/yr

River Weser/Intschede

Climatic water balance summer

CCLM: too humid

Climatological: fire risk(time demand 4 man month)

Longer and more!

Days with high fire risk

Change in seasonality

Shift to summer, but is there really a risk?

Source: Costa, Kropp , Holsten 2008

Putting the things together

integrating climate risk, settlementdistribution, land use, etc….

Source: Costa, Kropp , Holsten 2008

A compromise: Cause effect chains are useful for the analysis of the effects of adaptation effects

Isstimulus related, butneeds time, cause “networks and interlinkages” have to be defined

damages to power grids

damages to buildings

traffic breakdown

damages to traffic infrastr.

inundation

Clearly allows to identify how an stimulus and/or impact(s)will propagate through a system or how influential adaptationcould be!

Source: Kropp & Reckien 2009

seek here for responses to risk regionalpropagation mechanisms!

… and than perform economic analyses!

Implications/ConclusionsBroadening of science/stakeholder interface: clear target definition, e.g. of what is wanted, which questions should be answered

Fuzzy definitions of tasks may lead finally to frustration on stakeholder’s side

Do not underestimate the time demand

Clearly define mechanisms jointly for vulnerability analyses

Regarding adaptationCannot finally discussed by science, decision maker’s bias is too large!

I prefer that science should solve academic questions related to adaptation (there are still enough!)

Ongoing & future activities

CI:grasp: Climate Impacts: global & regionaladaptation support platform (running, Focus developing countries, two institutions PIK/GTZ, 1.8m)

PROGRESS (fall 2009 – four years, 4(+4) partners, 11m, BMBF), Potsdam Research Cluster on Georisk Analysis, Environmental Change, and Sustainability, worldwide with specific foci, coordinator: University of Potsdam

MEDIATION: Methodology for Effective Decision-making on Impacts and Adaptation (11 Partners, beginning 2010, 3.5 years, coordinator : Alterra, 7 FRP, 3m , Focus: Europe)