Climate Adaptation: Risk, Uncertainty and Decision-Making

1. Climate Adaptation:Risk, Uncertainty and Decision-Making Dr. Robert Willows Environmental Forecasting Manager

2. Policy Uncertainty Policy Uncertainty Risk Analysis Forecast Models Options Appraisal Policy Analysis Uncertainty Analysis Sensitivity Analysis Tools Policy Uncertainty Uncertainty Policy Policy Uncertainty Policy Climate Change Sequestration Climate Variability Emissions Impacts Energy Supply -ve Adaptation Energy Demand Scenarios Scenarios Economic and Social Issues and Development

3. Decision/ Policy makers Science Study objectives • Help identify ‘climate-sensitive’ decisions • Help achieve better decisions • Provides guidance on the use of tools and techniques • Should provide generic guidance on climate risks • Consistent with DETR guidelines for Environmental Risk Assessment (‘Greenleaves 2’)

4. UKCIP Technical Report • Part 1 : A review of • Risk and uncertainty • Decision-making under uncertainty • Risk-based climate impact assessment • Part 2 : Framework and Guidance • Stage by Stage guidance to support the process of undertaking risk-based appraisal of climate influenced decisions Climate Adaptation: Risk, Uncertainty and Decision Making

5. Decision Making Framework Climate change issue Climate change policy Climate change research, monitoring Identify problem Establish criteria for decision-making Monitor Climate change scenarios Socio-economic scenarios Risk assessment Vulnerability assessment Data information collection Implement decision Impact assessment Options appraisal Identify options No Make decision No Adaptation strategies Climate change application Objectives met ? Climate change policy Yes Problem defined correctly ? Yes

6. HAZARD … PATHWAY… RECEPTOR Consequences C2.1 Decision Criteria C1.3 Climate C1.2 C1.1 C3.2 C3.1 C4.1 Non-Climate Risk = Hazard * Consequence

7. 1 Probability (cumulative) ? 0 Large Small Magnitude Hazard … Risk … and … Uncertainty

8. High High Risk Hazard Low Risk Low Large Small Consequence Risk … and Uncertainty

9. good Quantitative Risk Ambiguity Knowledge of Hazard Ignorance of risk Uncertainty of likelihood poor poor good Knowledge of Consequence Risk … and Uncertainty

10. High Higher priority Act sooner Past or Present risk Low Low High Rate of change of risk or future risk Risk Prioritisation –Temporally-dynamic risks

11. Climate sensitive decisions Large Climate adaptation decisions Significanceofclimate changeor climate variable(s) Climate influenced decisions Moderate Climate independent decisions None None Moderate Large Significance of non-climate factors or non-climate variable(s)

12. Perceived Actual Large importance Importance of of factors factors Climate Over-adaptation factors Under-adaptation Actual Perceived Importance importance of factors of factors None None Moderate Large Non-climate factors Perceived Mis-adaptation Perceived Actual Mal-adaptation Actual importance importance Importance importance of factors of factors of factors of factors Decision errors?

13. Adaptation strategies under Uncertainty Optimistic Precautionary‘Risk Averse’ Least Regret No-regret • The option the may produce the best adaptation outcome MaxiMax • The option associated with the most favourable of the least favourable possible outcomes MaxiMin • That option associated with the lowest lost opportunities or regret MiniMaxRegret • The best adaptation option under all possible outcomes

14. Generic options for climate risk management • Wider use of risk assessment, forecasts and options appraisal • preferably proactive technical response • Delay and buy-time • proactive technical response to reduce uncertainty • Research  e.g. modelling, technology, ‘adaptive capacity’ • Monitoring • system performance monitoring - proactive technical response • climate impact monitoring - reactive technical response • Data and information supply, and education, awareness raising • proactive and reactive • Contingency planning • low probability, high consequence events • strategic planning response

15. Generic options for climate risk management • Diversification or bet-hedging • proactive technical or policy response • Insurance - proactive, fiscal response • Defend and Manage - reactive technical measures • Change of use • proactive or reactive, planning response +/- technical measures • Retreat and Abandon • strategic planning response • Safety factors, climate headroom, buffering measures • technical and regulatory response

16. Decision Making Framework Climate change issue Climate change policy Climate change research, monitoring Identify problem Establish criteria for decision-making Monitor Climate change scenarios Socio-economic scenarios Risk assessment Vulnerability assessment Data information collection Implement decision Impact assessment Options appraisal Identify options No Make decision No Adaptation strategies Climate change application Objectives met ? Climate change policy Yes Problem defined correctly ? Yes

17. Risk screening - climate variable checklist • Helps to both identify (Table 1) and define the different characteristics (Table 2) of potentially significant or relevant climate variables • Includes preliminary assessment of sensitivity and confidence • Useful for screening of variables • Not constrained by availability of climate forecast variables (e.g. from GCM’s or RCM’s) • Encourages rigorous analysis of climate influence • Table 1 is not complete - proxy and compound variables will depend on nature of particular assessment

18. Climate variable checklist Types of variables • Examples • PrimaryCO2, sea-level, temperature, precipitation, wind, cloud cover • SynopticWeather types, pressure, storm track, lightning • CompoundHumidity, evapotranspiration, mist, fog, growth season • ProxySoil Moisture, river flow, wave climate

19. Climate variable checklist Characteristics of variables • Examples • Magnitude and DirectionIncrease, decrease, rate of change • StatisticAverage, time-integrated, variability and frequency • Averaging periodInstantaneous ... hourly …. Annual …..decadal • Joint probability events Consecutive, coincident or joint occurrence, • and variables correlation

20. Climate Global temperature Mean water level Atmospheric pressure Tides Land level Wind speed direction Surges Rainfall, freeze/thaw, wave damage, animal activity, vegetation ‘Everyday’ wave climate Extreme water level climate Extreme wave climate Beach morphology Changes to structure Flood event Water level Waves Beach state Structure Overtop Breach Flood (Climate) Influence diagrams

21. Quantitative Subjective descriptor Theoretical Information Peer Colleague Pedigree probabilistic basis or or acceptance acceptance rank Hazard Certainty descriptor model data score P > 95% ‘Highly ‘Certain’, Established, Experiment- Absolute ‘All but 4 probable’ ‘Very ‘Known’ Validated al cranks’ likely’ ‘Reliable’ model 75% < P < 95% ‘Likely’ to ‘Confident’ Process- Historical High ‘All but 3 ‘Probable’ based model, or rebels’ underpinned Observation by some theory 25% < P < 75% ‘Possible’ ‘Plausible’ Black box Calculated Medium ‘Different 2 ‘Debatable’ and schools’ Simulation models 5% < P < 25% ‘Unlikely’ to ‘Not Statistical Educated or Low ‘New field’ 1 ‘Improbable’ confident’ models expert guess ‘Uncertain’ Fuzzy ‘Doubtful’ models P < 5% ‘Impossible’ Concepts and Uneducated None ‘No 0 definitions or non- opinion’ expert guess Describing confidence …..

22. Downscaling 1 • Space: GCM  site • Time: Monthly  daily

23. SDSM - Statistical Down-Scaling Model(Rob Wilby, Kings College London) • Daily data - observed data at site • Model - site data and large-scale data from GCM • Scenario - generate ensembles of daily time series

24. 1860 climate 2000 climate 2090 climate Downscaling - Flood return period prediction

25. Scenario analysis and risk assessment Q. Can we create scenarios which reflect changes in variability as well as the mean? A. YES - but it is difficult… and scenarios remain contingent on assumptions and non-quantified uncertainties Q. Can we assign probabilities to different scenarios? A. Probably. Expert judgement can be used to assign probability to the range encompassed by any two scenarios … but uncertainty components within suite of scenarios have to be well-posed

26. Estimating “probabilities” of different futures We typically use a small number of scenarios If we make assumptions about the likelihood of different emissions futures, use many more climate models, and incorporate the effects of natural climatic variability, we can generate many more scenarios

27. Incorporating climate change into water resources management The future hydrological resource base will not be the same as the present resource base Mean climate will be different, due to climate change and natural climatic variability Variability in climate will be different. Altered frequency of successive dry years? ….but we don’t know how different….

28. Influence diagrams - water resource management management objectives demand land use change Supply-side water resources model hydrological model baseline data reliability Demand-side Climate change adaptive response

29. 000s of Ml/d Forecast demand in 2025 Use of socio-economic scenarios Water resources for the future A STRATEGY FOR ENGLAND AND WALES March 2001

30. Coping with uncertainty 1. Flexible management approaches - review situation and adjust plans if appropriate - continued monitoring 2. Improved seasonal forecasts - based on understanding of causes of seasonal climatic variability 3. Scenario analysis and risk assessment

31. Conclusions and recommendations (for decision-makers) • Emphasis on understanding impact of present-day observed climate variability • Future climate change is only one source of decision uncertainty • Assessment of climate risk should be hierarchical /tiered • Climate adaptation should be iterative • Assumptions and sources of uncertainty should be treated explicitly in risk and impact assessments in order to reach robust decisions