The document discusses the use of narratives and numbers in climate change science and policymaking. It notes that while climate models provide quantitative projections, there is still significant uncertainty. Narratives are therefore also used to describe potential climate futures in a qualitative way. The "2 degree Celsius" narrative in particular aims to motivate climate action by framing 2C as the maximum safe level of warming. However, it emerged indirectly and its cost-benefit analysis is still debated. The document argues that to best inform policymaking, climate projections need to better integrate narratives with socioeconomic factors to assess impacts across scales and sectors. Foresight approaches should combine top-down and bottom-up methods to explore uncertain long-term issues like climate change.

1. Integrated
foresight
methods
that
avoid
models
locking
into
the
present
Learning
With
Futures
Using
Narra1ves
And
Numbers
NAEC
Seminar
Series,
OECD
Paris,
1st
December
2014
Prof.
Diana
Mangalagiu
Oxford
University
&
Sciences
Po
diana.mangalagiu@ouce.ox.ac.uk
&
diana.mangalagiu@sciencespo.fr

2. Narra1ves
and
numbers
in
climate
change
science
and
policy
• Uncertainty
in
climate
change
• Climate
science
and
climate
policy:
numbers
and
narra1ves
• The
2°C
narra1ve
as
a
focal
point
in
the
climate
debate
• Integra1ng
foresight
methods
that
avoid
models
locking
into
the
present
2

3. Uncertainty
in
climate
change
• Uncertainty
is
intrinsic
to
climate
change:
we
have
evidence
that
the
climate
is
changing,
but
not
precisely
about
how
fast
or
in
what
ways;
• We
don’t
understand
fully
the
social
and
economic
consequences
of
climate
change;
• “It
is
extremely
likely
that
we
[humans]
are
the
dominant
cause
of
warming
since
the
mid-­‐20th
century”
(IPCC
AR5,
2014);
• What
can
we
meaningfully
characterize
with
probabili1es
derived
from
data
and
what
remains
unquan1fiable?
3

4. Climate
science
uncertainty
language
(IPCC)
Calibrated
uncertainty
language:
• Amount
of
evidence:
limited,
medium,
robust
• Degree
of
agreement:
low,
medium,
high
• Confidence
(qualitaCve):
very
low,
low,
medium,
high,
very
high
• Likelihood
(quanCtaCve):
Virtually
certain
(99-­‐100%
probability),
Extremely
likely
(95-­‐100%),
Very
likely
(90-­‐100%
probability),
Likely
(66-­‐100%
probability),
…
IPCC
main
purpose:
• To
produce
assessment
reports
that
"provide
rigorous
and
balanced
scien1fic
informa1on
to
decision-­‐makers”
4

5. Sources
of
evidence:
climate
science
Climate
Variability
&
Change
Atmosphere
Carbon
Cycle
&
Water
Cycle
Land
Use
&
Cover
Change
Ecosystems
Topical
Elements
Cross-­‐Cu3ng
Elements
ObservaDons
Models
&
Scenarios
Decision
Support
Basic
Understanding
Forcing
Impacts
Responses
5

6. Numbers:
climate
scenarios
&
models
Scenarios:
– Responses
of
the
climate
system
to
different
greenhouse
gas
levels
based
upon
simula1ons
by
climate
models;
– Climate
scenarios
produced
in
sets
to
reflect
the
range
of
uncertainty
in
projec1ons;
– Recently,
climate
projec1ons
(Representa1ve
Concentra1on
Pathways)
combined
with
Shared
Socio-­‐Economic
Pathways
(qualita1ve
narra1ves
and
quan1ta1ve
elements)
to
assess
climate
change
impacts
and
vulnerabili1es
across
different
sectors;
• Models:
– Difficult
to
account
for
natural
variability
and
regional
climate
variability;
– Make
trade-­‐offs
between
increasing
spa1al/temporal
resolu1on
and
represen1ng
addi1onal
physical/biological
processes.
6

7. Science
and
policy
on
climate
change
• „there
are
experimental
methods
and
conceptual
confusion
[...]
• the
existence
of
the
experimental
method
makes
us
think
we
have
the
means
of
solving
the
problems
which
trouble
us;
though
problem
and
method
pass
one
another
by”.
The
Art
of
Inquiry,
WiKgenstein
(1953,
p.
232)
7

8. Narra1ves:
the
2°C
narra1ve
as
a
focal
point
• The
2°
limit
has
emerged
nearly
by
chance,
and
it
has
evolved
in
a
somewhat
contradictory
fashion:
– policy
makers
have
treated
it
as
a
scien1fic
result,
– scien1sts
have
treated
it
as
a
poli1cal
issue;
• Presented
as:
– a
threshold
separa1ng
a
domain
of
safety
from
one
of
danger/
catastrophe,
and
– an
op1mal
strategy
balancing
costs
and
benefits.
• Provides
a
focus
that
can
mo1vate
and
structure
prac1cal
steps.
8

9. Narra1ves
and
numbers:
the
cost-­‐benefit
dimension
in
the
2°C
narra1ve
• 1996
and
2005:
EU
Council:
– “There
is
increasing
scien1fic
evidence
that
the
benefits
of
limi1ng
the
global
average
temperature
increase
to
2°C
outweigh
the
costs
of
abatement
policies”;
• 2006:
Stern
Review
on
the
Economics
of
Climate
Change:
– “The
benefits
of
strong,
early
ac1on
considerably
outweigh
the
costs”;
• 2014:
IPCC
AR5:
– “Delaying
mi1ga1on
will
substan1ally
increase
the
challenges
associated
with
limi1ng
warming
to
2°C”;
• Related
narra1ves,
‘green
growth’,
‘low
carbon
economy’,
offer
policy-­‐
makers
a
more
op1mis1c
view
of
short-­‐term
prospects.
9

10. Economics
of
climate
change
• Some
of
the
most
important
uncertain1es
in
climate
economics
cannot
be
characterized
with
objec1ve
probabili1es;
• The
intergenera1onal
aspect
of
climate
change
challenges
conven1onal
economic
frameworks
and
tools
(expected
u1lity,
efficient
alloca1on,
marginal
analysis
etc.);
• Efficient
policies
are
not
necessarily
sustainable
policies;
• We
witness
baqles
of
narra1ves
(and
numbers):
– E.g.
we
must
choose
between
going
green
or
going
for
growth.
10

11. How
helpful
are
climate
scenarios
and
models
to
policy-­‐makers?
Source:
Berkhout
et
al,
2013
• There
is
a
need
to
match
uncertain1es
in
scenarios
and
models
to
the
actor
framing
of
uncertain1es
11

12. What
can
we
learn
from
use
of
numbers
and
narra1ves
in
climate
science
and
policy?
• There
is
a
mismatch
between
the
current
capacity
to
make
precise
climate
predic1ons
at
most
policy-­‐makers’
level
of
interven1on;
• Use
of
narra1ves
goes
beyond
transla1ng
quan1ta1ve
outcomes
as
a
way
to
inform
decision-­‐makers
about
the
complexity
of
systems;
• To
enable
forward-­‐looking
policy-­‐making,
numbers
and
narra1ve
approaches
need
to
feed
each
other
rather
than
compete
in
the
evidence-­‐based
policy
arena;
• Forward-­‐looking
approaches
must
help
reflec1ng
appropriate
trade-­‐offs
between
transparency
and
complexity;
• Scenarios
based
on
analy1cal
models
need
to
be
beqer
integrated
with
socio-­‐economic
narra1ves
to
envisage
impacts
and
vulnerabili1es
across
different
scales
and
sectors.
12

13. Integra1ng
narra1ves
and
numbers
to
avoid
models
locking
into
the
present
• Explore
futures
of
global,
long-­‐run,
and
uncertain
issues
such
as
climate
change
provides
is
an
opportunity
for
an
inclusive,
crea1ve
approach
to
policy
analysis;
• Scenarios
can
be
used
as
frames
enabling
projec1ons
of
future
climate
and
impacts
to
be
shared
and
debated;
• Scenario
approaches
need
to
be
matched
to
the
frames
of
stakeholders
who
are
situated
in
specific
decision
contexts
and
at
various
scales
in
the
system;
• A
variety
of
approaches
and
methods
need
to
be
considered:
top-­‐down,
boqom-­‐up,
interac1ve
foresight
approaches
can
be
combined.
13