Climate Change Uncertainty and Risk: From Probabilistic ......30.04.18 (9) Basics of economic...

Climate Change Uncertainty and Risk: From Probabilistic Forecasts to Economics of Climate AdaptationDavid N. Bresch, IED ETHReto Knutti, IAC ETHAssistants: Kathrin Wehrli, Thomas Röösli, Marius Wälchli

David N. Bresch, Reto Knutti, ETH Zürich

mailto:[email protected]





David N. Bresch / IED ETH Zurich | Reto Knutti / IAC ETH Zurich

Schedule26.02.18(1) Logistics, Introduction to probability, uncertainty and risk management

(RK, DB)05.03.18 (2) Predictability of weather and climate (RK)

Exercise 1 (toy model)12.03.18 (3) Probabilistic risk assessment model and some insurance basics (DB)19.03.18(4) Detection/attribution (RK)

Exercise 2 (toy model)26.03.18 (5) Model evaluation & calibration (RK)

Exercise 3 (toy model), preparation of presentation02.04.18 Ostermontag (no course)09.04.18 (6) Climate change and impacts, use of scenarios (RK, DB)16.04.18 (7) Presentations of toy model work, discussion (DB, RK)23.04.18 (8) 2-degree target and adaptation in UNFCCC (RK, DB)

Exercise 4 (introduction to climada)


Schedule

30.04.18 (9) Basics of economic evaluation and economic decision making (DB)

07.05.18 (10) The cost of adaptation - in developing and developed regions (DB)

Exercise 5 (impacts)

14.05.18 (11) Shaping climate-resilient development – valuation of a basket of adaptation options (DB)Exercises 6 (adaptation measures, preparation of presentation)

21.05.18Pfingstmontag (no course)28.05.18 (12) Presentations of climada exercise and final discussion (DB, RK)


Research opportunitiesThe weather and climate risks (WCR) group is currently looking for students to support and engage in our work, namely:

Student Research Assistant (HiWi): § Analyzing the Private Climate Services Sector, see

http://www.wcr.ethz.ch/the-group/open-positions/research-assistants.html:

Master thesis topics:§ Health costs due to heat waves in the canton of Zurich§ Climate change and labor: Impacts of heat in the workplace§ How do organizations include weather in their decision-making? A

quantitative analysis of Swiss organizations

See https://www.intranet.usys.ethz.ch/UMNW/master-arbeitenAnd please feel free to contact the assistants and/or David N. Bresch

http://www.wcr.ethz.ch/the-group/open-positions/research-assistants.html

https://www.intranet.usys.ethz.ch/UMNW/master-arbeiten


https://services.iac.ethz.ch/survey/index.php/335513/lang-en

Case study selection – your choice!

A short list of proposed case studies to learn more about, you made your

choice… this defines the content of today’s lecture (22 responses):

https://services.iac.ethz.ch/survey/index.php/335513/lang-en


What about this?

A house near the flooded village of Moorland in Somerset.


How are those two connected?


Causal chain of climate change from actions by people to impacts on people

weather

eval

uatio

n

From: Smith, L. A., & Stern, N., 2011: Uncertainty in science and its role in climate Policy

design policy


Climate-compatible development requires both mitigation and adaptation


Shaping climate-resilient developmentKey questionsDecision makers of national and local economies ask

§ What is the potential climate-related damage to the economies and societies over the coming decades

§ How much of that damage can we avert, with what measures?

§ What investments will be required to fund those measures and will the benefitsof that investment outweigh the costs?

The Economics of Climate Adaptation (ECA) methodology provides decision makers with a fact base to answer these questions in a systematic way. It enables them to understand the impact of climate change on their economies and identify actions to minimize that impact at the lowest cost to society. It therefore allows decision makers to integrate adaptation with economic development and sustainable growth.


Climate-resilient developmentEconomics of climate adaptation (ECA)Objectives§ Provide decision makers with the facts and methods necessary to design and

execute a climate adaptation strategy

Key features of the methodology:§ Follow a rigorous risk management approach to assess local total climate risk,

the sum of§ today’s climate risk,§ the economic development paths that might put greater population and value

at risk (à projection)§ the additional risks presented by climate change (à scenarios)

§ Propose and prioritize a basket of adaptation measures (i.e. options) to addresstotal climate risk on an economic basis


More than twenty Economics of Climate Adaptation (ECA) studies worldwide

Guyana: Flash flood risk to a developing urban area

Tanzania

Tanzania: Drought risk to health and power generation

Samoa: Risk of sea level rise to a small island state

Florida: Hurricane risk to public and private assets

Mali: Risk of climate zone shift to agriculture

India: Drought risk to agriculture

Caribbean: Hurricane risk to small islands

US Gulf Coast: Hurricane risk to the energy system

New York: Cyclones and surge risk to a metropolis

Hull, UK: Flood and storm risk to urban property

China: Drought risk to agriculture

Bangladesh: Flood risk to a fast-developing city

El Salvador: Flood and landslide risk to vulnerable people

Economics of Climate Adaptation (ECA) Working Group, a partnership between the Global Environment Facility, McKinsey & Company, Swiss Re, the Rockefeller Foundation, ClimateWorks Foundation, the European Commission, and Standard Chartered Bank.

http://www.wcr.ethz.ch/research/casestudies.html

http://media.swissre.com/documents/rethinking_shaping_climate_resilent_development_en.pdf

http://www.wcr.ethz.ch/research/casestudies.html


Economics of climate adaptation (ECA)

The working group

Plus scientific advice by many institutions, e.g. ETH Zürich

Comprehensive report at https://www.ethz.ch/content/dam/ethz/special-interest/usys/ied/wcr-

dam/documents/Economics_of_Climate_Adaptation_ECA.pdf

https://www.ethz.ch/content/dam/ethz/special-interest/usys/ied/wcr-dam/documents/Economics_of_Climate_Adaptation_ECA.pdf


Hull, UK: Flood and storm risk to urban property

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New York: Tropical cyclones and storm surge risk to a metropolis

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ECA full report featuring the first 8 case studies, 164 pages

http

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US Gulf Coast: Hurricane risk to the energy system

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Caribbean: Hurricane risk to small islands

http

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Guayana: Flash flood risk to a developing urban area

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Mali: Risk of climate zone shift to agriculture

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India: Drought risk to agriculture

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China: Drought risk to agriculture

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A global overview of ECA studies with a focus coastal communities

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TEST CASE ONBARISAL, BANGLADESH – FOCUS ONFLOOD AND TROPICAL CYCLONE RISK

Study partners funded by

Ecorys

Wieneke & Bresch, 2016: Economics of Adaptation (ECA) in Development Cooperation: A Climate Risk Assessment Approach Supporting decision making […]. Materials on Development Financing, UNU, KfW. https://www.kfw-entwicklungsbank.de/PDF/Download-Center/Materialien/2016_No5_Economics-of-Adaptation_EN.pdf

https://www.kfw-entwicklungsbank.de/PDF/Download-Center/Materialien/2016_No5_Economics-of-Adaptation_EN.pdf


Tropical Cyclones 1950-2016 x 100 (probabilistic)


Risk and capacity based allocation of resources: Poor in the West of the city most affected

∼2km

exposure

simulated impact

CLIMADAweather

red: highgreen: low

Barisalcity center


CLIMADA



Risk assessment

?

Risk today+development+climate change: the ‘waterfall chart’Annual average expected flood victims in the city of Barisal, Bangladesh


CLIMADA



Options appraisalThe adaptation cost curve: adaptation measures sorted by cost and benefità Powerful measures exist to save people’s lives in the city of Barisal, Bangladesh


CLIMADA



Solid waste management reduces flood losses by 10% in the core city of Barisal

CLIMADA

Barisalcity center

low averted damage

high averted damage

exposure

∼2km

red: highgreen: low




Flood resilient crops reduce agricultural losses by

40% mostly in the western part of Barisal

Barisalcity center

low

averted

damage

high

averted

damage

relative damage

∼2km

red: high

green: low

Wieneke & Bresch, 2016: Economics of Adaptation (ECA) in Development Cooperation: A Climate Risk Assessment Approach Supporting decision making […].

Materials on Development Financing, UNU, KfW. https://www.kfw-entwicklungsbank.de/PDF/Download-Center/Materialien/2016_No5_Economics-of-Adaptation_EN.pdf

CLIMADA



TEST CASE ONSAN SALVADOR, EL SALVADOR – FOCUS ONFLOOD AND LANDSLIDE RISK

Study partners funded by




100 year flood event around Acelhuate River, San Salvador, reaches up to 4 m water depth Acelhuate region, as a part of the metropolitan area of San Salvador, is selected to analyse flood risk and identify adaptation measures


CLIMADA



Exposure


Annual expected flood damage in Acelhuate can increase from USD 5 to 19 mio by 2040Roughly 140 people are affected today, we project almost 200 people affected due to flood under an extreme climate scenario in 2040


CLIMADA



Drainage, relief channel and ecologic restauration can protect up to 4’500 people until 2040


CLIMADA



Ecologic restauration, absorption wells and urban planning are powerful measures to reduce flood riskRoughly USD 200 mn assets are at risk from flooding until 2040


CLIMADA



Ecologic restauration in the upper catchment area an reduce up to USD 50 mn flood damage until 2040The restoration of forest areas in the upper catchment of Acelhuate leads to increased infiltration of rainwater and therefore reduces flood runoff in the city


CLIMADA



Synergies and dis-synergies, an example: Implementation of 4 cost efficient measures may avert 53% of the expected loss in 2030

Samoa case study

http://media.swissre.com/documents/rethinking_shaping_climate_resilent_development_en.pdf#page=110

http://media.swissre.com/documents/rethinking_shaping_climate_resilent_development_en.pdf


TEST CASE ONMAHARASHTRA, INDIA – FOCUS ONDROUGHT RISK TO AGRICULTURE


India, Maharashtra – Overview

Source: ECA group


India, Maharashtra case study

Focus on drought due to its large impact on agriculture and human livelihood

Source: ECA group


Maharashtra has the largest drought prone area of all states in India

Source: ECA group


• Predicting local climate is inexact given limited data. Therefore, 3 scenarios were developed for rainfall change in the 2030 timeframe– Based on temp and precipitation

predictions from 22 global climate models

– Distribution in rainfall varied from 92-102% of today’s value

• While some regional climate models exist assessing at a higher resolution and smaller grid area than GCMs, the science behind these models is still developing

• Climate scenarios were later used to develop 3 hazard scenarios

Description2030 scenarios

• Historic rainfall and drought data used to estimate rainfall frequency

Today’s climate

1

• Average change based on the mean rainfall predicted from 22 GCMs1

“Moderate”change

2

• Extreme change based on average of 90th percentile values for predicted rainfall from 22 GCMs

“High”change

3

GCM results consistent with output from regional models (A2 and B2) for Maharashtra

SOURCE: Results for GCMs from Prof. Reto Knutti, ETH Zurich; RCM results for A2 and B2 from Prof. Krishna Kumar, Indian Institute of Tropical Meteorology

1 22 GCMs for Maharashtra, run with the A1B scenario

India, Maharashtra case study

Given the uncertainty in future climate projections, we developed 3 scenarios for climate change

Source: ECA group


200

570

238

2030, total expected loss

Incremental increase from climate change

2008, Today’s expected loss

132

Incremental increase from economic growth; no climate change

35% of 2030 total expected loss

23% of 2030 total expected loss

• Expected loss is driven by current risk, agricultural growth, and climate change

• Agriculture income growth would contribute to an additional 23% of 2030 upper bound loss

• Climate change (occurring in combination with income growth) will account for 35% of 2030 upper bound loss

Expected loss from exposure to climateHigh climate change scenario, 2008 USD millions

The economic value at risk – driven by economic growth and climate changeIndia, Maharashtra case study

Source: ECA group


570

360370

238

Percent of region’s agriculture output

Annual expected loss in 2008 and 2030$ Millions, 2008 dollars

4.1

Scenarios

SOURCE: Swiss Re; team analysis

2.5

2008Today’s climate

2030Today’s climate

2030Moderate change

2030High change

2.63.1

• The three scenarios represent a range of uncertaintyaround the implications of climate change

• Even without an increase in hazard from climate change (scenario 1), there is still significant “annual expected loss” in the 2030 timeframe

The economic value at risk – driven by economic growth and climate changeIndia, Maharashtra case study

Source: ECA group


Severe impact of an extreme event on small and marginal farmers

figures for today’s climateSource: ECA group


Infrastructure and asset- based responses

Technological and procedural optimization responses

Systemic and behavioral responses

Risk transfer and contingent financing

Portfolio of responses

Hazards

Value

Vulnerability

Total Climate

Risk

Managing total climate risk requires a cost-effective adaptation portfolio

Source: ECA group


Measures are first screened based on feasibility and availability India, Maharashtra case study

Source: ECA group


Cost (mn $)

74

1,109

447

1,438

7,978

1,155

3,280

551

1,374

4,545

5,467

2,733

2,733

1,384

12,027

20

1,035

NA

-80Drainage systems (rf)

-197Soil techniques

-74Drainage systems (ir)

14Irrigation controls

139Drip irrigation

81Crop engineering (ir)

285Sprinkler irrigation

49Integrated Pest Mgmt. (ir)

146IPM (ir)

534Watershed +rwh

1,553Last mile irrigation

966Rehab. of irrigation systems

1,837Ground water pumping

271Crop engineering (rf)

8,987Planned irrigation projects

16Canal lining

1,035Insurance

NARelief and rehabilitation

1

3

499

1,036

556

21

16

59

547

64

225

36

91

312

227

113

113

35

-2.13

-0.18

-0.16

0.01

0.02

0.07

0.12

0.09

0.11

0.12

0.28

NA

0.73

0.67

0.35

0.75

0.81

1.00

*All figures are in terms of PV values, in current prices, up to 2030

Measure* Cost/Benefit ($/$)Benefit (mn $) Loss averted (mn $)

Totals 2,200 24,370 NA 3,000

• Only 80% of the expected loss can be mitigated by 12 measures. The remaining 20% is “residual” loss, which will require additional penetration of insurance, or relief and rehabilitation to address

11

10987654321

12

CBA

DE

Second, measures are analyzed in respect of costs and benefits (averted loss) in great detailIndia, Maharashtra case study

Source: ECA group

David N. Bresch / IED ETH Zurich | Reto Knutti / IAC ETH Zurich1 Estimated present value out to 2030 at 2009 dollars

In addition to agricultural ‘best practice’, index-based micro insurance is a powerful toolIndia, Maharashtra case study

Source: ECA group


In addition to agricultural ‘best practice’, index-based micro insurance is a powerful toolIndia, Maharashtra case study

Source: ECA group

Total climate risk570 mn USD

Dra

inag

e sy

stem

s an

d so

il te

chni

ques

Drip

and

spr

inkl

er ir

rigat

ion

Rai

n w

ater

har

vest

ing

Cro

p en

gine

erin

g

Insu

ranc

e

Averted damage (mn USD)

Reduced damage per USD invested (USD)

0 100 200 300 400 5001

7

13

19Most cost−effectiveFurther measures


Need for a set of changes to take place to achieve thefull extent of benefits of these 5 measuresIndia, Maharashtra case study

Source: ECA group


▪ The top eleven cost effective measures can address ~80% of the expected loss across a range of risk frequency/severity – However, the only measure

truly effective in high severity events is index insurance

▪ Measures included (to cover the range of risks) are:– Drainage systems (rf) – Soil techniques – Drainage systems (ir) – Irrigation controls – Drip irrigation – Crop engineering (ir) – Integrated Pest Mgmt. (ir)– IPM Rainfed– Sprinkler irrigation – Watershed +rwh– Crop engineering (rf)– Indexed insurance

11,657

11,6570

1/25 to 1/10

21,163

39,302

4,03404,655

7,054

<1/50

64,499

Residual loss

Index insurance

Other measures

1/10 to annual

29,665

0

9,512

13,099

4,655

1/50 to 1/25

0

Hazard frequency(1/return period) 11

10987654321

Loss profile

Loss across hazard frequencies*$ Million, 2008 dollars

* This is loss before adjusting for frequency range. Annual expected loss is area under the curve12

Micro insurance most effective for rare eventsIndia, Maharashtra case study

à see climada_adaptation_event_view

• Swiss Re significantly supported development of Indian weather insurance market as a first mover

• First deal in 2004 with Basix (microfinance institution) for Castor and Groundnut crop in Mehbubnagar, Andhra Pradesh against deficit rainfall covering 1’500 farmers

• Since then numerous reinsurance contracts closed providing coverage for >1’500’000 insured

• Most policies cover precipitation, temperature or a combination thereof

Source: ECA group


Global overview: Expected loss averted by adaptation measures


Roadmap and business case for adaptation funding

Risk assessment

Cost-benefit analysis

Risktoday

Develop-ment

Climate change

Risk 2030

What if we …

• specify our risk appetite in line with development priorities

• incorporate further criteria relevant to us in addition to cost-benefit ratio

• (re-)prioritize risk mitigation and transfer measures based on our priorities

• calculate an adaptation business plan and corresponding investment plan

• develop a roadmap including priority initiatives

• use roadmap and business case for funding discussions

• speed-up implementation with the additional funding and hence further strengthen resilience


www.climatefinancelandscape.org

http://www.climatefinancelandscape.org


1. Problem definition, Goal

7. Implementation

6. Decision (?)

NO

NO

Criteria met?

Problemdefined

correctly?

2. Decision criteria

3. Risk analysis

8. Monitoring

Note on decision strategies

CLIMADA

4. Identify options5. Options appraisal

Souvignet, Wieneke, Müller & Bresch, 2016: Economics of Climate Adaptation (ECA) - Guidebook for Practitioners. https://www.kfw-entwicklungsbank.de/PDF/Download-Center/Materialien/2016_No6_Guidebook_Economics-of-Climate-Adaptation_EN.pdf

https://www.kfw-entwicklungsbank.de/PDF/Download-Center/Materialien/2016_No6_Guidebook_Economics-of-Climate-Adaptation_EN.pdf


Notes on validity – adaptation

Unrealistic?

ModelledNot modelled

Reality à Model: Abstraction

Described in Model

Model à Reality : Interpretation (Verification/Falsification/Calibration)

incrementalconceptional

Cha

ngin

g re

ality

àe.

g. c

limat

e ch

ange


The purpose of a model

§ A prediction for the future§ A tool to test different scenarios§ A tool to test hypothesis about the system and to better

understand it

§ A framework to compare different options and put them on a common scale


Do we trust a model?§ “A vigorous Climate Prediction Project [] would ensure that the goal

of accurate climate predictions at the regional scale could begin to aid the global society in coping with the consequences of climate change.” (http://wcrp.wmo.int/documents/WCRP_WorldModellingSummit_Jan2009.pdf )

§ “New models that exploit extreme scale computing could determine the future frequency, duration, intensity, and spatial distribution of droughts, deluges, heat waves, and tropical cyclones.”(http://www.sc.doe.gov/ober/ClimateReport.pdf )

§ “Verification and validation of numerical models of natural systems is impossible. This is because natural systems are never closed and because model results are always nonunique.” (Oreskes et al. 1994)

§ “…what these instances of fit [between their output and observational data ] might confirm are not climate models themselves, but rather hypotheses about the adequacy of climate models for particular purposes.� (Parker 2009)


Do We Need Better Predictions to Adapt to a Changing Climate?

§ “Given the deep uncertainties involved in the prediction of future climate,

and even more so of future climate impacts, and given that climate is

usually only one factor driving the success of adaptation decisions, we

believe that the “predict-then-act” approach to science in support of

climate change adaptation is significantly flawed.”

§ “…use climate models to provide information that can help evaluate

alternative responses to climate change, without necessarily relying on

accurate predictions as a key step in the assessment process. The basic

concept rests on an exploratory modeling approach whereby analysts use

multiple runs of one or more simulation models to systematically explore

the implications of a wide range of assumptions and to make policy

arguments whose likelihood of achieving desired ends is only weakly

affected by the irreducible uncertainties.”

(Dessai et al. EOS 2009)


The Hartwell Paper: A new direction for climate policy after the crash of 2009§ “A second misunderstanding has developed in parallel with that of the

misapplied analogies from other treaty situations. In its way, it is as profound and as widely shared a ‘mis-framing’ and it concerns the popular view of science as projected by users of scientific information and by those producers of primary science on climate issues who have chosen also to act as advocates and activists. They employ a ‘deficit model’ of science. The expert scientist pours knowledge into the ignorant and passive heads of the public and their representatives. Their deficit is remedied. They trust the expert’s superior knowledge and qualifications and the scientist then leverages that power to instruct further the ignorant public and to delineate the correct actions to remedy the situation which the expert has described.”

§ “This error has led to the common and flawed assumption that the solutions to climate change should be ‘science driven’ as if a shared understanding of science will lead to a political consensus.”

(http://eprints.lse.ac.uk/27939/)


§ “Politics is not about maximising rationality. It is about finding compromises that enough people can tolerate to allow society to take steps in the right direction. So, contrary to all our modern instincts, political progress on climate change simply cannot be solved by injecting more scientific information into politics. More information does not automatically reduce uncertainty and increase public confidence, which is the common politicians’ assumption. But, in consequence of that assumption being present and potent in this (or any) politically hot field, there is a constant temptation for experts to overstate and to oversimplify: something that is plainly revealed in the recent history of climate issues. But this is a recipe for political disappointment…”


The Hartwell Paper: A new direction for climate policy after the crash of 2009


§ “The consequence of this misunderstanding [the climate change problem is a ‘pollution problem’ and CO2 must be reduced] was that there was a fundamental framing error, and climate change was represented as a conventional environmental ‘problem’ that is capable of being ‘solved’. It is neither of these. […] Rather than being a discrete problem to be solved, climate change is better understood as a persistent condition that must be coped with and can only be partially managed more – or less – well.”


The Hartwell Paper: A new direction for climate policy after the crash of 2009


Making a decision

Theory

Obser-vationsModels 42

(Answer to the Ultimate Question of Life, the

Universe, and Everything)

57

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