Uncertainty from above and encounters in the middle

Workshop - Climate Change and Uncertainty from Above and Below 27-28 January, 2016

Conference Room 2, India International Centre, New Delhi

Suraje DessaiUniversity of Leeds

Centre for Climate Change Economics and Policy

ClimatechangeuncertaintyfromAboveandBelow

Climateadaptation

policy

Worlddevelopment

Globalgreenhousegases

Globalclimatemodels

Regionalisation

Impacts

Vulnerability(physical)

Vulnerability(social)

Adaptivecapacity

Indicatorsbaseon:TechnologyEconomicresources

Information&skillsInfrastructureEquityInstitutions

Past Present Future

Bottom-upapproach

Top-downapproachGlobal

Local

Dessai,S.andM.Hulme(2004)Doesclimateadaptationpolicyneedprobabilities?ClimatePolicy,4,107-128.

ClimatechangeuncertaintyfromAboveandBelow

Climateadaptation

policy

Worlddevelopment

Globalgreenhousegases

Globalclimatemodels

Regionalisation

Impacts

Vulnerability(physical)

Vulnerability(social)

Adaptivecapacity

Indicatorsbaseon:TechnologyEconomicresources

Information&skillsInfrastructureEquityInstitutions

Past Present Nextseason,year,decadeandbeyond

Bottom-upapproach

Top-downapproach

Global

Local

AdvancingKnowledgeSystemstoInformClimateAdaptationDecisions

(2012-2017)

ResearchDomain2Thesocialstatusoftechno-scientific

knowledgeinadaptationtoclimatechange

ResearchDomain1Understandingclimate

informationneedsacrosssociety

Methods:• Documentaryanalysisof

officialsources• In-depthinterviews(n=95)

withclimateexperts,governmentofficials,andconsultants

JointworkwithDrJamesPorter

UKAdaptationContext:Legislation

UK Adaptation Context: ScienceMet Office Hadley Centre – unified model, Numerical Weather Prediction and Climate Change

World-leading status with international collaborations and research substantially contributing to the IPCC assessment reports

Small, centralised, network of UK climate science (e.g. NERC)

Met Office Hadley Centre has a strong commitment to serve policy priorities

Climate Prediction Programme(CPP), funded by Defra and DECC

AchronologyofUKclimatescenarios

CCIRG91 CCIRG96UKCIP98 UKCIP02

UKCP09

Hulme,M.andS.Dessai(2008)Negotiatingfutureclimatesforpublicpolicy:acriticalassessmentofthedevelopmentofclimatescenariosfortheUK.EnvironmentalScience&Policy,11,54-70

UKCP09 projections• First projections designed to

treat uncertainties explicitly (Murphy et al. 2009)

• More informative but also more complex than previous scenarios (Murphy et al. 2009)

• Designed to inform adaptation decisions – “usable science”

• Cost £11 million • User Interface• Reviewed by Steering and User

group and 5 experts

Change in temperature

(c) UKCP09 outlines the probability of different amounts of change in temperature

Prob

abilit

y of

cha

nge

Change in temperature

(b) Using many models gives a range of different changes in temperature but no information on which to use

Change in temperature

(a) UKCIP02 gave a single estimate of change in temperature

(a) (b) (c)UKCP09

On interpreting multi-model ensemble outputs:

‘They’re very useful, but they’re ad hoc in construction… They provide no basis to advise users on whether a response “near the middle” should be considered more likely than one “at the edge”, or if the actual response lies outside the multi-model range altogether’ (MOHC Climate Scientist 6 – Interview).

(a) 10% probability that change in temperature is very likely to be greater than this

(c) 90% probability that temperature change is very likely to be less than this

(b) 50% probability that change in temperature, also known as the “central estimate”, will likely be in this range

UKCP09 provided probabilities measuring how strongly different outcomes for climate change were supported by evidence available at the time (models, observations, understanding). Rise in temperature.

(a) (b) (c)

Bayesian framework to handle uncertainty

'from a methods point of view the goal just seemed right and it was something that should be done. [What] really gives me confidence is the Bayesian framework... we've put our own interpretation on it... but it's all written down in the maths, it's there to debate... you can see it in black-and-white. It's just good science' (Met Office Scientist 3, Interview).

Change in temperature

(c) UKCP09 outlines the probability of different amounts of change in temperature

Prob

abilit

y of

cha

nge

Change in temperature

(b) Using many models gives a range of different changes in temperature but no information on which to use

Change in temperature

(a) UKCIP02 gave a single estimate of change in temperature

(a) (b) (c)UKCP09

Changing relationship between climate scientists and users (roles and responsibilities)

Listening and responding to user demands (higher spatial resolution and quantification of certainty)

Complexity of the method has restricted uptake and shifted responsibility onto consultancies

Was the science stretched too far (e.g. cascade of uncertainty, user-demand)?

‘it ends up pushing people towards complete rejection or more dangerously complete acceptance. Imagine if we had a large number of intelligent numerate users who embraced the probabilities, who learnt how to use them, and then realised five years down the line that these are immature probabilities, that the Andes are 1km too short, and we knew this back in 2009. Why would they trust us again?’ (Academic Climate Scientist 7 – Interview).

'There was a feeling that you shouldn't be seen arguing about what we can or can't do on climate change because that'll undermine the need for action. I was sympathetic with that view when UKCP09 started but I'm much less so now. I think the public needs to hear scientific disagreement, especially for things as serious as climate change' (Academic Climate Scientist 5 - Interview).

Will users take responsibility?

Atmosphere for criticism?

Is scientific disagreement in public necessarily bad? Especially with the danger of UEA leaked emails used by the anti-science lobby to cast doubt

Next wave of scepticism will come from within the academy

Isco-producingclimatescienceanddecision-makingariskworthtaking(forscientists)?

• UKgovernment iscommittedtocreatingusablescience foradaptationdecision-making

• Butscientistshavecompetingpriorities• Ifscientistsrespondtoostronglytouserdemandstheycan

riskpushingscience farther thanit’sreadytogo (displeasingtheirpeers)

• Ifscientistsfailtorespondstronglyenough theycanriskusersbeingunabletoapplycomplexclimateinformation.

• Creatingusablescience isnotaneutral activity (Turnhout etal2016).Ratherit’sthecontestedoutcomeofintensepolitical strugglesoveritsmeaningandapplication,wherenewfrictions,antagonism,andpowerconcernsareoftenintroduced (Klenk &Meeham 2015).

Encounters in the middle: robust decision-making and the management of deep uncertainty in climate change adaptation

Why is there uncertainty about future climate?

Future society

GHG emissions

Climate model

Regional scenario

Impact model

Local impacts

Adaptation responses

The envelope of uncertainty

The

casc

ade

of u

ncer

tain

ty

Wilby and Dessai (2010)

Uncertain knowledge

Future society

GHG emissions

Climate model

Regional scenario

Impact model

Local impacts

Adaptation responses

Envelope of uncertainty

The

casc

ade

of u

ncer

tain

ty

Adapted from Wilby and Dessai (2010)

Robust decision-making and deep uncertainty

Robust Decision Making (RDM) is a family of decision analytic methods developed specifically for decisions with long-term consequences and deep uncertainty (Lempert et al. 2006)

Deep uncertainty is a situation in which analysts do not know or cannot agree on (1) models that relate key forces that shape the future, (2) probability distributions of key variables and parameters in these models, and/or (3) the value of alternative outcomes (Hallegatte et al. 2012)

Vulnerability(now)

Adaptation options

A, B, C....

Preferred measuresB, H, S, W

Vulnerability(future)

Robust measures

B, W

Adaptation pathwaysW then B

Observed climate variability and

change

Observed non-climatic pressures

Climate change narratives

Narratives of non-climatic pressures

Social acceptability

Technical feasibility

Economic appraisal

Regulatory context

Adaptation principles Sensitivity analysis

Performance appraisal New evidence

Monitoring

AFrameworkforRobustAdaptation

Wilby,R.L.andS.Dessai(2010)."Robustadaptationtoclimatechange."Weather65(7):180-185.

Dessai,S.andR.Wilby.“HowCanDevelopingCountryDecisionMakersIncorporateUncertaintyaboutClimateRisksintoExistingPlanningandPolicymakingProcesses?”WorldResourcesReport,WashingtonDC.

“Top-down” and “bottom-up”

Top-down scenario, impacts-first approach (left panel) and bottom-up vulnerability, thresholds-first approach (right panel) – comparison of stages involved in identifying and evaluating adaptation options under changing climate conditions (IPCC SREX, 2012).

An example: Thames Estuary 2100

Ranger et al. 2013

Adaptationpathwaysandtippingpoints

Haasnoot etal.2013Exploringpathwaysforsustainablewatermanagement inriverdeltas inachangingenvironment.ClimaticChange

ApplyingRDMintheCauveryRiverBasininKarnataka

90°0'0"E

90°0'0"E

80°0'0"E

80°0'0"E

70°0'0"E

70°0'0"E

30°0'0"N 30°0'0"N

20°0'0"N 20°0'0"N

10°0'0"N 10°0'0"N

80°0'0"E

80°0'0"E

78°0'0"E

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76°0'0"E

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14°0'0"N 14°0'0"N

12°0'0"N 12°0'0"N

10°0'0"N 10°0'0"N

8°0'0"N 8°0'0"N

• CRB-K (area: ~35960 sq.km) has a unique combination of characteristics: high groundwater extraction, rapidly expanding cities (Bangalore, Mysore etc), increasing costs for pumping water to urban areas, falling water quality, irrigation expansion and conflict with riparian states

• Uncertain future socio-economic changes– Urban expansion and increasing water

use– Trade-off between increasing irrigation

efficiency and irrigation expansion• Uncertain future climatic conditions

• What water management strategies are robust to wide ranges of uncertainty by the 2030s and 2050s?

InitialreflectionsofapplyingRDMinthemiddle/hybridspace

• RDMapproachesrequirespecificexpertisefromanalystsandasmallnumberofstakeholders,thusleaningtowardstheaboveperspective(perhapscharacterisedastechnocratic)

• Tensionsbetweentheaboveandbelowperspectives,namely:– expertise (scientistsandelitesversusthepublic)– temporality (longtermversusthenow)– representation (thepowerful fewversusthedisempoweredmany)