Presentation made at the expert meeting organised jointly by the European Commission, the OECD and the project PLACARD, in Paris 26th -28th October 2016. For more information see www.oecd.org/gov/risk/joint-expert-meeting-on-disaster-loss-data.htm

1. 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

2. 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

3. 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.

4. 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.

5. 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].

6. 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].

7. 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]

8. 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.

9. 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).

10. 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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.

15. 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

16. 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.

17. 0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
MillionEuro
Loss deflated and adjusted to wealth increase
Loss deflated
00,000
05,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
MillionEuro
Insured
Not insured
Distribution of deflated losses (million
Euro in 2013 values)
Adjusted for wealth increase
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
MillionEuro
type D
type C
type B
By category of events. B: Meteo, C: Hydro, D:
Clima. [Mysiak J., Carrera L., Vanneuville W,
2014]
0
10
20
30
40
50
60
70
80
90
100
0
5,000
10,000
15,000
20,000
25,000
30,000
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
Nr.events
MillionEuro
Flood Losses: 40% or around 160
billion Euro
Europe’s exposure to climate risks

18. 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