Risk assessment across DRR and CCA communities: opportunities and gaps

Jaroslav Mysiak, Euro-Mediterranean Centre on Climate Change (CMCC), and Fondazione Eni Enrico Mattei (FEEM)

Joint Expert Meeting on Disaster Loss Data

26-28 October 2016

Placard

Platform for climate adaptation and risk reduction. H2020 CSA, 2015-2010

- Facilitate multi-stakeholder dialogues and consultations

- Establish a network of networks

- Explore gaps and challenges in research, policymaking and practice

- Support to the development and implementation of evidence-based and innovative policies

http://www.placard-network.eu/

How can foresight help to reduce vulnerability to climate-related hazards? Vienna, 24-25/10/2016

Exploring the potential of ecosystem based approaches – Ecosystem based Adaptation (EbA) and Ecosystem based Disaster Risk Reduction (Eco-DRR). Adaptation Futures Conference, 11/05/2016

Climate extremes and economic derail - Impacts of extreme weather and climate-related events on regional and national economies. Understanding Risk Forum, Venice, 17/05/2016 2016

Learning across communities of practice: risk assessment for disaster risk reduction and climate risk management. Understanding Risk Forum, Venice 17/05/2016

Connecting CCA & DRR – priorities & opportunities in Europe. Brussels 19/04/2016

Climate (variability and change) risk assessment

serves different purposes

[1] Effectiveness and efficiency of reducing and financing disaster risk, and adapting to changing climate. Informs a variety of public and private choices (e.g. cost recovery of water/environmental services).

[2] Guiding risk-sensitive development, social protection systems, economic cohesion and solidarity, (climate justice and liability).

[3] Fostering climate, meteorological and hydrological services and market. Ot at least exploiting the value unleashed by Copernicus Earth observation program and climate change services (C3S).

[4] Micro- and macro-prudential regulation, economic policy coordination and internal security.

Better understanding of climate risks has economic and financial value, and hence market. The challenge is how to harness this potential for the Sendai Framework for DRR.

Advancements in CRA for climate adaptation

- High performance computing has enabled new generation of climate models that are better capable of simulating climate extremes [e.g. Alexander 2016, Hay et al. 2016, Heim Jr. 2015]. Robust estimates are possible also for longer period return values.

- Multi-model ensembles with high spatial resolution capable of exploring model uncertainty and better inform public policy choices [e.g. Ciscar et al. 2014, Forzieri et al., 2014, Jacob et al., 2014, Prudhomme et al., 2014, Roudier et al. 2016].

- Detection and attribution more reliable when based consistent evidence from observations and numerical models capable of replicating the event e.g. Brown, 2016, Easterling et al. 2016, NAS 2016, Sarojini et al. 2016, Stott et al., 2016].

- Near-term (multi-year to decadal) predictions reliability [e.g. Doblas-Reyes et al., 2013; van den Hurk et al., 2016; Meehl et al., 2013]. Grand challenge of WCRP.

Advancements in CRA for DRR

- Improved modelling capability, including multi-hazard assessment, empirical corroboration of damage models, impact propagation through networks, stress testing of critical infrastructure components. Improved availability of hazard data (e.g. flood hazard and risk prone areas) [e.g. Domeneghetti et al., 2015, Kellermann et al., 2015, Notaro et al., 2014, Rose and Wei, 2013, Ward et al., 2014]

- High resolution exposure data including population, gross added value, gross domestic/regional product, buildings, infrastructure, industrial facilities [e.g. Amadio et al., 2016, Figueiredo and Martina, 2016]

- Better record of existing risk mitigation measures [e.g. Jongman et al., 2012, Ward et al., 2015]

- Working in partnerships [e.g. typology of public-private and public-public partnerships in Mysiak et al 2016].

Economic assessment of climate risk

- Economic damage and losses caused by natural hazards in Europe are driven by small number of highly damaging events (70% of damage caused by 3% of events) [EEA 2015].

- Hazard interdependencies and correlated loss probabilities critical for designing robust insurance schemes [e.g. Jongman et al 2014, 2015]. Vulnerability a key hazard variability explains a minor part of the observed variation in the recorded damage.

- Expected sequence or chain of events, amplifiers, interdependencies and spillovers, speed of recovery and distribution of impacts important for understanding fiscal impacts [e.g. Carrera et al 2016, Koks et al 2016].

- Natural hazard risk relevant for governments’ debt sustainability. Marginal changes in nominal GDP growth and interest rates may lead to much higher debt-to-GDP ratio than the one projected as a baseline [e.g. S&P, 2013, EC 2016].

Economic assessment of climate risk (2)

Flood risk in the area of the port of Rotterdam [Nicolai et al 2015]

Impact of 1:200 year flood on regional economy in Emilia Romagna and other regions in IT [Mysiak et al 2015]

Gaps and opportunities

Monitoring of disaster impacts is important but alone not sufficient. Recorded losses should be complemented by hazard simulations and model-based losses, improved exposure data and better understanding of the multiple vulnerabilities. Transparency a key.

Engagement of national statistical offices (NSOs) and national meteorological and hydrological services (NMHS) – data standardisation, quality assurance, and accessibility.

Open data and reuse of public sector information (PSI) have a role to play. Additional data sources notified or granted state aid, climate risk disclosure, solidarity aid, EU CPM multi-hazard assessments, etc.

Further improvements in CRA from behavioural studies (risk perception and risky choices); better understanding of ecosystem services (and their decline) attenuating disaster risk; advanced statistical methods; better incorporation of high resolution exposure data; empirical records of speed of recovery, and wider social impacts.

Gaps and opportunities (cont.)

Monitoring of progress made under the SFDRR in Europe can be integrated with more ambitious (EU/OECD) goals (e.g. OECD recommendation on disaster risk financing strategies). Better understanding of the full economic costs of disasters in the increasingly interconnected economies should be a part these efforts.

Ecosystem-based approaches may be cost-effective, have certain co-benefits, and may become increasingly valuable in the face of more frequent and/or severe extreme events.

Public-private partnerships - role models for a join bearing of responsibilities and efficient risk-sharing, intentional of increasing insurance coverage and penetration, and guaranteeing a strong financial backing in view of uncertain tail distributions of risk.

Advancement in CRA for DRR-CCA can contribute to improving integrated

assessment models IAMs (e.g. damage functions).

Thank you for your attention! jaroslav.mysiak@cmcc.it

The research reported here was conducted with financial contribution from the European Union, the H2020 under the Grant Agreement no. 653255, and

the FP7 under the Grant Agreement no. 308438

visit www.placard-network.eu and enhanceproject.eu

for more information and reports

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Disaster risk and insurance in Europe

Convergence regions (2007-2013, left) and less developed regions (2014-2020, right) of the Cohesion Policy (CP).

Share of insured out of total disaster losses 1980-2013. Based on data from MR NatCatService

Differentiated impacts on competitiveness

Distribution of past (1980-2013) flood damage across European regions (NUTS2), as percentage of European average.

Current and future climate risk further exacerbate regional differences and undermine economic, social and territorial cohesion across Europe.

Relative changes of the real GDP across European regions between 2002-2011, result of economic and financial crisis.

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Flood Losses: 40% or around 160 billion Euro

Europe’s exposure to climate risks

Ecosystems and disaster risks

a) Simplified natural asset - benefits relation, based on Mace et al. (2015) modified

b) Economic framework for ESS provision, based on Fisher et al. (2008) but modified

c) Financial flows and distribution, based on (World Economic Forum, 2011) but modified

d) Effects of risk-mitigating ESS on exceedance curve