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A methodological roadmap to assess the
costs and benefits of adapting to climate
change
The case of natural risks
Stéphane Hallegatte
Centre International de Recherche sur l’Environnement et le Développement (CIRED) et
École Nationale de la Météorologie, Météo-France
A methodological roadmap
A methodological roadmap
Global climate and socio-economic scenario
 A 10-percent increase in hurricane potential intensity, consistent
with a +2K warming of sea surface temperature in the Atlantic.
 At a later stage: the use of several Global Climate Models would be
required.
 Socio-economic scenario: unchanged economy in the U.S.
 At a later stage: the use of several economic growth and population
distribution scenarios
A methodological roadmap
Landfall probabilities:
information needed by risk
managers
Regional climate change and change in hazards
 Global Climate models cannot be used to assess changes in hurricane
risks.
 Instead, we use the Emanuel hurricane model, which takes as input
large-scale climate indicators and generates hurricane tracks and
intensities.
– Generation of 3000 tracks in the present climate
– Generation of 3000 tracks in a climate with a 10-percent increase in potential
intensity
HURDAT
PC
MC
0.8
0.6
0.4
0.2
0
1
2
3
4
5
Annual probabilities of
landfall for all categories,
according to the data
and to the model in the
present climate (PC),
and in the modified
climate (MC).
Landfall probability in the
present climate
Landfall probability in the
modified climate
A methodological roadmap
Future changes in direct
losses: information needed
by insurers
Change in direct losses
 Vulnerability of each county on the U.S. Atlantic and Gulf coastline is
estimated using past hurricane landfalls and the relationship: L = ai W3
95,426
Galveston
New Orleans
Cape Coral
17500
Currituck
New York
12500
Miami
7500
2500
-2500
1
106
 This vulnerability is used to assess how modified hurricane intensities
would translate into modified hurricane direct losses.
 A 10-percent increase in potential intensity would translate into a
54-percent increase in annual mean direct losses from hurricane
landfalls.
A methodological roadmap
Future changes in total
losses: information needed
by local authorities and
governments
Change in total losses including economic
response and indirect impacts

Direct losses:
– Casualties and injuries
– Direct economic losses (i.e., value of what has been destroyed or
damaged)

Indirect losses:
– Emergency costs (Katrina: $8 billion)
– Business interruption, supply-chain disruption, lost production during
reconstruction
– Demand surge (larger repair costs due to lack of workers and materials)
– Macro-economic feedbacks (e.g., through loss of jobs and tax revenue)
– Long-term adverse consequences on economic growth (developing
countries)

Other costs:
– Political destabilization
– Psychological trauma and social network disruption
0
Households
Government
Other services
Arts, accomodation…
Education, health care…
P&B services
Finance…
Information
Transportation…
Retail trade
Wholesale trade
Manufacturing
Construction
Utilities
Mining
Agriculture
Damages (US$m)
Assessment of production losses in Louisiana due to
the landfall of Katrina
We start from (quite uncertain) estimates of damages in 15 sectors.
35 000
30 000
25 000
20 000
15 000
10 000
5 000
An Input-Output Economic Model
We model the regional economy of Louisiana using the ARIO (Adaptive
Regional Input-Output) Model.
1/ To assess the propagations among sectors:
• we use BEA data on the exchanges between sectors, households and
government (input-output table);
• we assume simple “adaptation” rules (e.g., substitution with imports)
2/ To assess the reconstruction duration and demand surge, we assume that
all sectors have a limited production capacity.
Disaster consequences in economic models
The Katrina case
Production changes in 15 sectors in Louisiana, in the Katrina’s aftermath,
using the ARIO (Adaptive Regional Input-Output) Model.
An input-output
model of the local
economy, with 15
sectors that
interact with each
other.
We investigate the
interplay of:
(1) the decrease in
production
capacity due to
damages;
(2) the increase in
demand due to
reconstruction
needs
Disaster consequences in economic models
The Katrina case
Production changes in 15 sectors in Louisiana, in the Katrina’s aftermath,
using the ARIO (Adaptive Regional Input-Output) Model.
Boom and constraints in
the construction sector
Cross-sectoral
propagations
Decrease in production
capacity
Direct losses:
$107b
Production
losses:
$23b
Housing
service losses:
$19b
Total losses:
$149b
Imperfect results, but orders of magnitude are
consistent with data
Imperfect results, but orders of magnitude are
consistent with data
Small business bankruptcy?
See “the other” Venice
meeting.
Value added losses per sector, data and model
Change in total losses including economic
response and indirect impacts
Results from the ARIO model in Louisiana
Katrina
The 54% increase in direct losses translates into a 60% increase in
total losses.
Doubling of the probability of total losses larger than $50b.
A methodological roadmap
Adaptation to reduce direct losses
 In this assessment, county vulnerability is unchanged in the future.
 Adaptation measures can make this vulnerability decrease: building
norms, seawalls, risk-adverse land-use management…
 The assessment of adaptation options can most of the time only be
done at the local scale.
 Example on a GIS-based analysis of storm surge risks in Miami:
Adaptation to reduce direct losses
Work in progress, preliminary results
14
No SLR
50cm SLR
Mean annual losses (billion USD)
B
12
10
SLR
impact
(no ada)
8
A
6
The cost of doing
so is often small.
Adaptation "cost" (unchanged risk)
4
2
0
0
In any climate,
there are very
efficient opportunity
to reduce risks in
many places.
100
200
300
400
500
Protection level / dike height (cm), wrt current mean sea level
Climate change
makes only risk
management more
desirable.
A methodological roadmap
Adaptation to reduce indirect losses
 Adaptation strategy can also reduce indirect losses without reducing
direct losses: insurance schemes, government support of affected
businesses, emergency planning, etc.
Soft adaptation: insurance, foreign aid,
support to small-businesses,
support to evacuees, etc.
Hard adaptation: dikes, seawalls,
reinforced buildings, etc.
Katrina
Adaptation to reduce indirect losses
 In a Mumbai case study using ARIO, increase insurance penetration
from 10 to 100% would have reduced the production losses due to the
2005 flooding by 40% (from about US$300m to about US$200m)
Besides macroeconomic
benefits, insurance would help
poor households cope with the
disaster and restart economic
production (e.g., individual
businesses).
CONCLUSIONS
Landfall probabilities:
information needed by risk
managers
Future changes in direct
losses: information needed
by insurers
Future changes in total
losses: information needed
by local authorities and
governments
CONCLUSIONS

For the U.S. coastline:
– In absence of adaptation, a 2K warming of Atlantic Ocean could translate
into a 60% increase in hurricane total losses in the U.S.
– The real concern is about the most powerful hurricanes, with a
doubling of the probability of total losses larger than US$50 billion.
– The result is based on the Emanuel model, which is particularly pessimistic:
this outcome is not impossible, but is very uncertain.

From a methodological point of view:
– The assessment of climate change impacts requires the taking into
account of indirect impacts and ripple effects, especially when
considering significant shocks to the economy.
– Efficient adaptation options to control risks are available at low cost,
and are often “no-regret,” i.e. bring benefits in an unchanging climate.
– Adaptation options do not have to focus only on direct losses: efficient
strategies exist to reduce indirect losses.
– Someone has to explore the consequences of an absence of climate
stabilization. What about a +6K scenario?
CONCLUSIONS
 From a decision-making point of view:
– How can we make ‘adaptation’ decision considering the large
uncertainty in all available assessments?
– Adaptation decisions must not be made based only on (weak) costbenefit analysis, but also using robustness and flexibility criteria.
– Many options can be proposed that bring benefits in the present
climate (no-regret) and in most possible future climate (robustness),
and/or that can be adjusted when new information is available
(flexibility)
Examples of adaptation options
This work is presented in a series of papers available on my
website or on request to:
[email protected]