The Emperor’s
New Climate Scenarios
Limitations and assumptions of commonly usedclimate-change scenarios in financial services
Authors: Sandy Trust, Sanjay Joshi, Tim Lenton, Jack Oliver

www.actuaries.org.uk

July 2023

Contents
Foreword – Professor Tim Lenton

3

Introduction – IFoA Presidential Team

4

Key Findings

6

Section 1: The climate-scenario modelling conundrum

8

Section 2: Climate-scenario modelling goes mainstream

15

Section 3: Climate scenarios – a warning for financial services

18

Section 4: A new beginning

24

Appendix A – Example qualitative, narrative scenario

27

Appendix B – SSP creation diagram

28

Appendix C – Principles for actuarial work

29

References30

2

Nigel Topping

Willemijn Slingenberg-Verdegaal

Everyone who cares about the stability of our financial systemshould read this paper. Failing to include known non-linear
effects in strategic thinking about climate change will lead tocomplacency, heightened risk and missed opportunities. So thescenarios that are used as part of TCFD processes really matter– both because economic damage will grow much faster andbecause the transition to clean technologies will happen much
faster than conventional economic modelling suggests.

It is critically important for stewards of capital to account forthe state of the natural world, including climate change, when
thinking through their investment strategies. A tick-the-box
approach is no longer good enough. It is all about understanding
and taking ownership of assumptions and modelling choices andacting upon insights to set appropriate investment strategies.

UN Climate Change High-Level Champion, COP26

Mukami Njeru
Director, PWC

Unfortunately, achieving the net-zero transition is now an
optimistic scenario rather than the best-estimate scenario.
While this is not an ideal place to be in as a global society, it isa place from which we can make informed decisions on policies
relating to managing climate-related risks. This paper shows
there are fundamental gaps in our current approach to climatechange analysis, highlighted by the application of actuarial
principles. It is another example of how the actuarial profession
can contribute to the management of climate risk. We trust it
will be well received and, more than that, acted upon.

Lucy Saye

Chair, IFoA Sustainability Board
Climate and nature-related risks are subject to high levelsof uncertainty, making scenario analysis a key tool inunderstanding and managing them. However, widely available
climate change scenarios, while commendable, systematicallyunderestimate the risks. Actuarial principles emphasise theneed to understand and communicate material judgements
and limitations to decision makers. This paper is a welcome
addition, helping actuaries and other users of climate scenarios
explore limitations and assumptions across the climate
modelling chain, as well as setting out a way forward morealigned with climate science.

Julius Pursaill

Investment Adviser, Cushon
Few trustee boards have made significant changes to asset
allocation as a result of scenario analysis, making it an
expensive exercise of little practical value, with benign results
potentially delaying decisions to support decarbonization. Thissituation needs to change; a radical new approach is needed toensure scenarios add value, are actionable and more accurately
represent the level of risk we face if we don’t decarbonize.

3

Managing Director Climate & ESG Solutions at Ortec Finance

Simon Sharpe

Author of Five Times Faster, Rethinking the Science, Economics
and Diplomacy of Climate Change
A decade ago, one of the world’s top climate economists said it
would be irresponsible to act as if dominant models of the economic
costs of climate change were sensible. To continue to act thatway now would be grossly negligent. This paper points the way
to a more realistic assessment of risk, which is much needed.

Katie Blacklock

Non-executive director of Edmond de Rothschild, member of
M&G’s With Profits Advisory Board and Governor of the HealthFoundation
This report is an important intervention that directly addresses
and challenges the disconnect between what we know fromclimate science and what economic scenario analysis is telling
us about the impact of doing nothing. Those in governancepositions have a clear fiduciary duty to understand and mitigate
the risks posed to clients’ financial assets. To do so, we need to
improve our collective climate literacy. Accepting the output ofclimate-scenario modelling at face value is at best inadequate
and at worst dangerous – not just for the price of financial assets
but for the planet. This report provides an excellent starting
point for model users to understand the critical limitations andinherent uncertainties of scenario modeling when applied to an
unprecedented and structural change in the risk landscape.

Dr Sarah Ivory

University of Edinburgh
There is a problem with the current climate-scenario modellingwhich means it does not accurately depict the future we know
is coming, or the financial implications of this. Climate scenario
users in financial services have two pathways forward. To spend
all of your time understanding why existing models are wrong
and tweaking them is equivalent to rearranging deck chairs on
the Titanic. To build new models which get political buy-in on
climate action is equivalent to launching the life boats. It still
won’t save all of us, but it’s the best option we have.

Foreword

Professor Tim Lenton, Chair in Climate Change and Earth System Science at the
University of Exeter
It is concerning to see these same economic models being
used to underpin climate-change scenario analysis in financial
services, leading to the publication of implausible resultsin the Task Force on Climate-related Financial Disclosures(TCFD) reporting that show benign, or even positive, economic
outcomes in a hot-house world. This jars with climate science,
which shows our economy may not exist at all if we do not
mitigate climate change. It is essential that financial services
institutions and regulators understand the limitations of thesemodels and move towards realistic climate scenarios thatrecognise the catastrophic downside risk of a hot-house world.

We have left it too late to tackle climatechange incrementally. It now requires
transformational change and a dramatic
acceleration of progress.
A growing threat is the approach of ‘tipping points’ – thresholds
which, once crossed, trigger irreversible changes, such as theloss of the Amazon rainforest or the West Antarctic ice sheet.
Some tipping point thresholds have already been reached,while others are getting closer as global warming continues.
Once tipped into a new state, many of these systems will cause
further warming – and may interact to form cascades that could
threaten the existence of human civilisations.
However, some economists have predicted that damages
from global warming will be as low as 2% of global economic
production for a 3˚C rise in global average surface temperature.
Such low estimates of economic damages – combined withassumptions that human economic productivity will be anorder of magnitude higher than today – contrast strongly withpredictions made by scientists of significantly reduced humanhabitability from climate change.

4

My hope is that this will spur a further acceleration of activity
towards net zero in financial services, as it is only by reducing
emissions, repairing the climate system and removing
greenhouses gases that we will avoid the worst impacts ofclimate change – and we will need the support of the capitaland insurance markets to achieve this.
Actuaries have an important contribution to make here. The
application of actuarial principles to climate-change scenario
analysis demonstrates the significant weaknesses in current
approaches. Actuaries also wield enormous influence in the
global financial system. In addition to their role in the insurance
markets, their work in pensions means they can impact capital
allocation in long-term savings in a way few other professions
can, – the financial system is critical to accelerating a range of
positive socio-economic tipping points.
Because just as tipping points are part of the greatest threat
we face, the same logic may also provide the solution. We haveidentified a variety of positive tipping points in human societiesthat can propel rapid decarbonisation, in areas includingtransportation, agriculture, ecosystem regeneration, politics andpublic opinion. This concept could unlock the stalemate – thesense that there’s nothing we can do about climate change.
Operationalising positive tipping points will require leadership
across society to seek out and deliver these transformational
opportunities. Like the negative tipping points in the Earth system,some positive tipping points are already in motion. We must now
seize the opportunity to accelerate this process further.

Introduction

The IFoA Presidential Team– model users must therefore understand the limitations anduncertainties. Indeed, communicating limitations, assumptions
and uncertainties clearly to users is a key tenet of actuarial
thinking, embodied in the Financial Reporting Council’s‘reliability objective’ for actuarial work that informs Technical
Actuarial Standards:1

Matt Saker
President, Institute andFaculty of Actuaries

Louise Pryor
Immediate Past
President

Kalpana Shah
President-electFollowing the policy briefing for COP27, Climate Emergency– tipping the odds in our favour, with Sir David King’s Climate
Crisis Advisory Group, we are delighted that the IFoA is
continuing its collaboration with scientists on climate changewith this paper in partnership with Exeter University’s Global
System’s Institute. This paper focuses on how a deeper
understanding of climate change, including tipping points, canimprove financial services climate-scenario modelling.
Scenario modelling is an important component of the actuarialrisk-management toolkit. Investigating adverse yet plausible
scenarios enables actuaries to investigate how different
combinations of risks could impact the future solvency of afinancial entity and what action could be taken to mitigate this.
In the context of climate change, scenario modelling enables
financial institutions and regulators to investigate the impact ofdifferent climate futures, which is important given the challenges
we face. It has advanced considerably since its inception in
financial services five years ago, and those who have advanced
this should be congratulated on their significant efforts.
Climate-change scenario modelling is complex and nuanced,
requiring sophisticated model builds that link different
models together – physical climate models, economic models,insurance models and asset models. Many assumptions are
required and, as with any model, it is a simplification of reality

5“To allow the intended user to place a high degree of relianceon actuarial information, practitioners must ensure the actuarial
information, including the communication of any inherent
uncertainty, is relevant, based on transparent and appropriate
assumptions, complete and comprehensible.”This paper examines the limitations and assumptions in relation
to climate-change scenario modelling practices in financial
services, focusing on hot-house world scenarios of 3˚C or moreof warming. It demonstrates how current techniques exclude
many of the most severe impacts we can expect from climatechange, such as tipping points and second order impacts – they
simply do not exist in the models. The consequence of this isthat the results emerging from the models are far too benign,
even implausible in some cases. It’s as if we are modelling the
scenario of the Titanic hitting an iceberg but excluding from theimpacts the possibility that the ship could sink, with two thirdsof the souls on board perishing.
This means the usefulness of the current scenarios is limited,as they do not communicate the level of risk adequately. More
dangerously, the artificially benign results can easily serve as an
excuse for delaying action, as consumers of these results, suchas policymakers and business leaders, may reasonably believe
the results to adequately capture the risks.
We hope this report will help by clearly highlighting areasof challenge, as well as providing ideas on ways to develop
scenario techniques to better capture the severe risks we face.
We also hope this more realistic assessment of risk will act tofurther catalyse the collaboration and investment into solutions
that is required to ensure these risks don’t materialise.

Key findings

Climate-scenario modelling is a structured exploration of different plausible futures.
It is a valuable tool for informing investment decision making,risk management and financial system resilience. It has evolved
rapidly in financial services and is becoming mainstream.
Regulators should take well-deserved credit for driving
this adoption, along with the pioneering organisations andindividuals who have led the way.

However, there are some important challenges that model users
must be aware of, largely caused by the disconnect between
climate scientists, economists and model users in financial
services.

Challenges
Commonly used climate models in financial services are underestimating risk
1. Many climate-scenario models in financial services are
significantly underestimating climate risk
There is a disconnect between climate science andthe economic models that underpin financial services
climate-scenario modelling, where model parsimony
has cost us real-world efficacy. Real-world impacts ofclimate change, such as the impact of tipping points(both positive and negative, transition and physical-risk
related), sea-level rise and involuntary mass migration,
are largely excluded from the damage functions ofpublic reference climate-change economic models. Somemodels implausibly show the hot-house world to beeconomically positive, whereas others estimate a 65%
GDP loss or a 50–60% downside to existing financial
assets if climate change is not mitigated, stating these
are likely to be conservative estimates.
2. Carbon budgets may be smaller than anticipated andrisks may develop more quickly
Earth-system models also have limitations anduncertainties with profound implications. We may haveunderestimated how quickly the Earth will warm for agiven level of emissions, meaning we need to update our
expectations as to how quickly risks will emerge. A fasterwarming planet will drive more severe, acute physicalrisks, bring forward chronic physical risks, and increase

6

the likelihood of triggering multiple climate tipping
points, which collectively act to further accelerate therate of climate change and the physical risks faced. A
significant consequence of this is that carbon budgets
may be smaller than those we are working with and may
now be negative for a temperature goal of 1.5°C. All ofwhich reinforces the need to urgently reduce emissions,remove greenhouse gases from the atmosphere andrepair broken parts of the climate system.
3. Regulatory scenarios introduce consistency but
also the risk of group think, with scenario analysis
outcomes being taken too literally and out of context
Firms naturally begin with regulatory scenarios, but thismay lead to herd mentality and ‘hiding behind’ Network
for Greening the Financial System (NGFS) thinking,rather than developing an appropriate understandingof climate change. Key model limitations, judgements
and choice of assumptions are not widely understood,
as evidenced by current disclosures from financial
institutions. Investors and regulators assessing financial
resilience need to be particularly careful not to place
undue reliance on artificially benign model results.

Moving forward
Education, qualitative scenarios and margins for uncertainty
1. Education on the assumptions underpinning the models
and their limitations
There is a discrepancy between climate scientists, thosebuilding the models, those working with the models, anddecision makers in financial services. Deeper insights
don’t flow between the different actors, meaning thatmodelled results don’t reflect climate science. Financial
services institutions have expended considerable effort
on producing results, meaning there has been less time
for analysis and understanding. The limitations of themodels and uncertainty in results is communicatedbadly or not at all. All those involved in climate-scenario
modelling – including model providers, professional
advisers, those in governance positions and regulators –need to develop an appropriate understanding and work
to break down silos.
2. Development of realistic qualitative and quantitative
climate scenarios is required
Financial institutions should be encouraged to develop
plausible qualitative and quantitative scenarios alongsideregulatory ones. A simple quantitative approach could be
to use a reverse stress-testing approach based on a ruin
scenario of 100% loss of GDP at a certain temperature
limit. This should be supported by robust internal debate
around assumptions, development of appropriate
investment beliefs around climate-related risks, andopportunities to foster ownership of assumptions
and mitigate risk of group think. This should include
developing thinking on ways in which climate change
may realistically evolve based on current emissions andwarmings.

7

Time is too short
to wait for models
that are perfect.
3. Model development required to better capture risk
drivers, uncertainties and impacts
Time is too short to wait for models that are perfect.
Development is needed, including looking beyond
the commonly used general equilibrium economic
models that underpin many approaches today, to findsolutions that can realistically capture risk drivers
and the interaction between policy, technology, thereal economy and markets. A practical fix is to use
qualitative scenarios that reflect the emerging realityof climate change to complement models, as wellas out-of-model adjustments and margins to reflect
uncertainty.

1: The climate scenario
modelling conundrum

Modelling global warming, and our society’s reaction to it, to assess physical andtransition risks under a range of possible future scenarios is hugely complex.
For each scenario we wish to assess, we need to estimate thelevel of future greenhouse gas (GHG) emissions driven by how
quickly we transition, how quickly the planet will warm due tothese emissions, what impacts our global society will feel and,
finally, what this will all mean in terms of economic outcomes.
The complexity is compounded by the limited relevant historical
data on which to base our modelling – our society has notbeen through an energy transition of this pace and scale while
simultaneously facing into physical climate change. It is achallenge that is matched in its complexity only by its importance.
Further risk, uncertainty and complexity is introduced bymatters such as the inherent uncertainty in climate scienceand the pace of climate change (faster than expected) driving
extreme weather events and the emergence of climate tipping
points. These reinforce the importance of limiting global
warming to 1.5°C, with warming beyond this level extremely
risky, with an unknown set of impacts. It is overwhelmingly in
our economic interest to limit global warming.

However, this is not reflected in modelling results, which showa wide range of economic impacts from a hot-house world
scenario where we fail to transition. Some models estimate
this to be economically positive, which is implausible given thesignificant devastation and risks we expect to face.

Climate-change scenario modelling– setting the scene
Modelling how an individual financial organisation such as apension scheme, insurance company, bank or investment firmmight be impacted by physical and transition risks in a rangeof climate scenarios is complex. Figure 1 below illustrates at ahigh level the different models that are required, with further
details provided in Appendix B on the scenario creation
process. Users in financial services may only be familiar withthe models used in the final state of the process.

Figure 1: Schematic of climate-change scenario modelling
NGFS suite of models approach
Transition
riskTransitional pathways
Integrated Assessment Models
Temperaturealignment

Physical climate models estimate how
the climate will evolve for a certain
level of GHGs.

Energy and emission
related variables

Transition models estimate how theeconomy will change as it delivers this.

1.5°C, 2°C, 3°C +Chronic climate impacts
Earth System Models
Climate Impact Models

Country productivity
damagesMacro-financial
impacts
Macroeconomic
ModelPhysicalrisk
AssetsAcute climate impacts
Natural Catastrophe Models

damages*

Data available in IIASA database8

A macro-economic model takes thephysical and transition model outputs
and translates these into country-level
GDP impacts over time.
This allows for the creation of economic
scenarios, outputs that can be used in
traditional financial models.

Data available in NGFS CA Climate Impact Explorer

Source: NGFS, ‘NGFS Scenarios for central banks and supervisors, September 2022’, reproduced with permission

The climate-modelling conundrum – limited relevant data,high uncertainty and interconnectedness
Modelling climate change and society’s reaction to it is hugely
complex, requiring us to make assumptions about many
unknown factors for each scenario we wish to model, including:• The level of future emissions in each scenario• How quickly the climate will warm for a given level ofemissions• Whether we cross climate or ecosystem tipping points• The level of damages we will experience as the climate
warms, mitigated by adaptation• How quickly we will transition as we react to the physicalchanges we experience• The pace and scale of the transition in different geographies,
economies and sectors• How to incorporate factors such as land use, technologicalchange and nature.
Actuaries typically set assumptions in a model using past data.
For example, examination of mortality rates enable actuaries
to set assumptions for life insurance or pensions. Historic
stock market returns allow actuaries to estimate what sort ofeconomic volatility might be experienced in the future. If thingschange, such as mortality improvements, then actuaries adjust
their assumptions accordingly.

With climate modelling there is limited relevant past data.
There is no historical precedent for the rate of increase of
GHGs, so we cannot be confident about how quickly the planet
will warm, although we can estimate where we might end
up with this level of GHGs. Similarly, our economy has neverbeen subject to an energy transition of this speed and scale,alongside the increasing physical risk environment we face into.
Modelling physical and transition risks based on past data isakin to looking backwards from the deck of the Titanic on theevening of 14 April 1912 and predicting a smooth passage to
New York because no icebergs have yet been hit.
Further complexity is introduced because many of thesefactors are interdependent. For example, a rising physical risk
environment may bring increased support for policy shifts,
which will accelerate the transition, arguably a phenomenon
we are now observing. Ongoing investments into fossil fuelinfrastructure will bring increased emissions, which will
accelerate warming, another current phenomenon. Figure 2
below illustrates this interaction between the Earth’s physicalclimate system and our human society.

Figure 2: Double materiality – the interaction between the physical climate and our economy

Global vital signs - a warming planetSociety and the economy

Earth System Impacts

Physical, transition and liability risks• Floods

Mitigation and adaptation opportunities• Wildfires• Storms• Droughts• Sea-level rise
• Tipping points• etc

Accelerate

Finance
Mitigate

Source: Sandy Trust, reproduced with permission

9

€
¥$

Climate change – a risky and uncertain
business, tipping into the unknown

The Paris Agreement recognised that financial institutions havea critical role to play in climate change, with the inclusion of agoal to make finance flows consistent with a pathway towards
low GHG emissions and climate-resilient development, resulting
in the creation of the Glasgow Financial Alliance for Net Zero
(GFANZ)2 to help enable this. While GHG emissions physicallydrive global temperatures, financial systems play a huge role
behind the scenes because every pound that is lent, spentor invested has a real-world impact (so arguably could beviewed as a risk transfer payment). Therefore, climate change
is a dynamic problem, where the financial system is not only
impacted by climate change but also impacts climate change,
a concept known as double materiality.

Climate change is happening more quickly than anticipated,with severe impacts already being felt by millions globally at
the current level of warming of 1.2˚C. A consistent pattern ofcorrections over time is observed, in the direction of worse
than we anticipated, leading to downward revisions of ‘safe’
temperature levels towards 1.5˚C as illustrated in Figure 3
below, a limit we are fast approaching. These impacts are
expected to increase as the temperature rises further. Figure 3
also shows how uncertain climate change is, with the rangeof uncertainty on the temperature for high and low-emissions
scenarios overlapping until around 2070.

Figure 3: Risks are increasing with every increment of warming

A. High risks are now assessed to occur at lower global warming levels
Global surface temperature change
relative to 1850-1900

Global Reasons for Concern (RFCs)
in AR5 (2014) Vz AR6 (2022)

˚C 5

Very high

4

˚C 5
4

High

3

Intermediate

2

2
1.5
1

Low
Very low

1

3

0

0

-1
1950

2000 2015

2050

Shading represents theuncertainty ranges for the low
and high emissions scenarios

2100

2011-2020 was around
1.1˚C warmer than
1850-1900

AR5 AR6

AR5 AR6

Unique &threatenedsystems

Extremeweather
eventsAR5 AR6
Distributionof impacts

Risk/impact (Risk is thepotential for adverse consequences)
Very high

AR5 AR6

Globalaggregate
impacts

AR5 AR6
Large-scale
singulareventsTransition range
Confidence levelassigned to transition range

High
Moderate

Low

Very highB. Risks differ by system

Undetectable

Midpoint of transition

Land-based systems

Ocean/coastal ecosystems

˚C 5
4
3
2
1.5
1
0

Wildfire Permafrost Biodiversity Dryland
damage degradation
loss
water
scarcityeg. over 100 million
additional people exposed

10

Tree
mortality

eg. increase in thelength of the fire season

Carbonloss

Warm-watercoralseg. coral reefs
decline by 70-90%

Kelp
forestseg. coral reefs
decline >99%

Seagrass Epipelagic
meadows

RockyshoresSalt
marshesC. Risks to coastal geographies increase with sea-level rise and depend on responses
Global mean sea-level rises relative to 1900

r

cm

R

r

R

r

R

r

R

cm

100

Very highHigh
Intermediate
Low
Very low

75
50
25

100

1986-2005
baseline

0
1950

2000

2050

75
50
25
0

2100

Low-likelihood, high-impact storyline,
including ice sheet instability process

Urban atoll
islands

Arcticcommunities

Risks are assessed withmedium confidencerLarge tropicalagricultural deltas

No-to-moderate
response

R

Resource-richcoastal cities
Maximum potential
response

D. Adaptation and socio-economic pathways affect levels of climate-related risk
Limited adaptation(failure to proactively adapt; lowinvestment in health systems)
Incomplete adaptation(incomplete adaptation
planning; moderate investment
in health schemes)
Proactive adaptation(proactive adaptation
management; higher
investment in health systems)

Heat-related morbidity andmortality

Food insecurity(availability, access)1

The SPP1 pathway illustrates
a world with low population
growth, high income andreduced inequalities, foodproduced in low GHG
emission systems, effective
land use regulation and highadaptive capacity (ie low
challenges to adaptation).

0

The SSP3 pathway has the
opposite trends.

˚C 4

SSP3

3

SSP1

2
1.5

Limited Incomplete Proactive
adaptation adaptation adaptation

High
Low
Challenges to adaptation

Figure SPM.4 from IPCC, 2023: Summary for Policymakers. In: Climate Change 2023: Synthesis Report. A Report of the Intergovernmental Panel on Climate
Change. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team,H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, (in press). Report. © IPCC, reproduced with permission (Figures: AR6 Synthesis Report (ipcc.ch))

One of the drivers for the range of uncertainty aroundtemperature outcomes for different emissions scenarios is theuncertainty, and hence probabilistic nature, of carbon budgets.
As detailed in the position paper of the Climate Crisis Advisory
Group (CCAG):3“The latest assessment from the IPCC indicates that around 320
billion tonnes (Gt) of CO2 can be emitted from the beginning of2022, to have a 67% chance of staying below 1.5°C, and 420 Gt
can be emitted for a 50% chance.”
With current emissions running at c.40 billion Gt per annum,
this gives eight years of budget left before we exceed thebudget for keeping below 1.5˚C of warming. This budget isprobabilistic, though, giving a 2/3 chance of success and so a
1/3 chance of failure. Given the risks associated with exceeding
1.5˚C of warming, these are not wise odds.

11

CCAG go on to summarise the level of uncertainty associatedwith these carbon budgets and the very real risk that they
may be smaller than advertised, even for these relatively low
probabilities of success:“There are a large number of uncertainties that impact uponestimates of the remaining carbon budget. The figures above
assume strong action on non-CO2 emissions, no big shift in the
AMOC, and that we do not cross any unexpected tipping points;
in other words, no surprises. Further, this would only provide a
certain probability of remaining below 1.5°C: there is a possibility
that the remaining carbon budget for limiting warming to 1.5°C
is already zero.”... there is a possibility that the remaining carbon
budget for limiting warming to 1.5°C is already zero.

But these underlying assumptions do not hold. There has
not been strong action on non-CO2 emissions, methanelevels are at an all-time high (at a little over 1˚C of warming),tipping points have been partially triggered, and deforestationequivalent to adding the annual emissions of India is taking
place. The consequences of these are to effectively either
reduce the probability of success for a given carbon budget or
to reduce the carbon budget for that probability of success.

of ice sheets in Greenland, West Antarctica and the Himalayas,
permafrost melt, Amazon die back and halting major ocean
current circulation.4
These tipping points may interact, triggering each otherand cascading like dominoes. Once triggered they may beirreversible and would act to accelerate global warming (byincreasing GHG levels) and increase the severity of impacts(eg accelerating multi-metre sea level rise). There are early
indicators that we are now approaching some of these tipping
points, as illustrated in Figure 4 below, taken from ‘Exceeding
1.5°C global warming could trigger multiple climate tipping
points’.5 Tipping points are particularly important as, if
triggered, we may find the climate moves into a different statethat we no longer have the ability to control.6

The emergence of climate tipping points
Further non-linear impacts may be driven by multiple climatechange tipping points, which are not currently captured in
IPCC estimates and are increasingly likely to be triggered as
temperatures go past the 1.5°C level. These include the collapse

Figure 4: The likelihood of tipping points being triggered for different global warming temperatures
10
Tipping:very likely

86

likelyCentralpossible

Minimum estimate

4
Current policies
2

Paris range

East Antarctic Ice Sheet

Arctic Winter Sea Ice

Boreal Forest (N. expansion)

Boreal Forest (S. dieback)Atlantic M.O. Circulation

Boreal Permafrost (collapse)

Amazon Rainforest

Sahel & W. African Monsoon

Extra-polar Alpine Glaciers

Barents Sea Ice

East Antarctic Subglacial Basins-6

Labrador Sea/SPG Convection-4

Boreal Permafrost (abrupt thaw)-2

Low-latitude Coral Reefs

0West Antarctic Ice Sheet

Current warming

Greenland Sheet

Global warming (in °C, relative to pre-industrial)

Maximum-8-20,000-15,000-10,000-5,000Year CE
Source: McKay et al, Exceeding 1.5°C global warming could trigger multiple climate tipping points, 2022. Reproduced with permission.

12

0

Today
2100

The implications of tipping points include an impact on carbon
budgets (they are likely to be smaller than currently assumed
if we are to avoid tipping points) and accelerated, or more
severe, climate impacts emerging at lower temperatures thanpreviously thought. Consider the impact of just two of thesetipping points in combination: glacial melt in mountainous
regions and faster than expected sea level rise. In the regionof two billion people rely on meltwater from the third
cryosphere – the Himalayan icecap – for irrigation and drinking
water. Hundreds of millions of these same people live in
low-lying areas, such as Vietnam and Bangladesh, which may
be inundated at high tide by 2050.7 It is hard to see how a
population could endure water shortages, flooding and theanticipated heat spikes; this is likely to be untenable and aforcing factor for involuntary mass migration.

results can vary wildly. Three different credible institutions
estimate the impact of a hot-house world on global GDP by
2100 as ranging from -73%, to a milder -18%, to ongoing GDP
growth, which is counter-intuitive given the severe physicalrisks we anticipate if temperatures continue to rise.

The latest science on tipping points reinforces the need torace to zero and makes decarbonisation scenarios that feature
temporary overshoot (ie allowing the temperature to increasebeyond 1.5˚C before reducing it again) significantly more risky.
Tipping points must be included if scenarios are to be realistic.
They are no longer high-impact, low-likelihood events but are
now high impact, high likelihood, and we need to mitigate
and plan for them. Ignoring them in scenarios and modellingsignificantly understates risk.

The IPCC’s Sixth Assessment Report explores future scenarios
known as the shared socioeconomic pathways (SSPs). Creatingthese scenarios is inherently complex, requiring estimates of
population, emissions, growth and the use of many integrated
assessment models (IAMs) – a diagram of the process andinputs is shown in Appendix B to illustrate this. Key aspectsof the scenarios are shown in Table 1 below. Note again theoverlap in temperature ranges.

Inconsistencies and counter-intuitive results in
scenario output
The severe physical impacts of higher levels of warming meanthat it is overwhelmingly economically positive to limit global
warming to 1.5˚C.8 However, climate-change scenario modelling

Climate scenarios are roadmaps that show us how the future
might evolve, including ways in which we could reach net
zero. Many show that it will be extremely challenging toreach net zero in the timelines that we aspire to. Appendix
A of the United Nations Environment Programme FinanceInitiative’s (UNEP FI) 2023 Climate Risk Landscape 9 provides
a list of commonly used scenario providers, including theIntergovernmental Panel on Climate Change (IPCC),10 NGFS,11
the International Energy Agency (IEA),12 and others.

SSP5 is a scenario that foresees fossil-fuel development andhigh levels of global warming reaching 4˚C by 2100 andrequiring the use of solutions such as geoengineering. The
frequency and severity of physical risk impacts from this highemissions pathway include increases in heat stress, extreme
weather (including heavy precipitation), more frequent
droughts, higher sea level rise, and a greater chance oftriggering further climate tipping points.

Table 1: A summary of temperature rise statistics from IPCC reports

Scenario

Temp rise 2100 (°C)
(50th (5th-95th)
percentile values)

Peak temp rise (°C)
(50th (5th-95th)
percentile values)

SSP1-1.9 (very low)

1.3 (0.8-1.5)

SSP1-2.6 (low)Likelihood of staying below (%)

2000 year
sea-level rise

<1.5°C<2°C<3°C

1.6 (1.3-1.6)

38

90

100

1.6 (1.1-1.8)

1.7 (1.4-1.8)

20

76

99

SSP2-4.5 (intermediate)

2.7 (2-2.9)

2.7 (2-2.9)

0

8

71

4-10m for 3°C

SSP3-7.0 (high)

3.5 (2.5-3.9)

3.5 (2.5-3.9)

0

0

22

12-16m for 4°C

SSP5-8.5 (very high)

4.2 (3.3-5)

4.2 (3.3-5)

0

0

4

19-22m for 5°C

2-3m for 1.5°C

Temperature rise and likelihoods are taken from Table SPM.2 of the AR6 WG3 Summary for Policymakers and are relative to1850-1900 baseline. Sea-level rise taken from Table 9.10 of the AR6 WG1 Full report with the sea-level rise for a given
temperature matched to the nearest scenario.

13

Figure 5: Global GDP per Capita by SSP

Global GDP per capita by SSP
Gross domestic product (GDP) is measured in 2005 international dollars.
This means it is adjusted for inflation and cross-country price differences.
SSP5 – Baseline
Fossil-fuelled Development– Taking the Highway$120,000$100,000

SSP1 – 1.9
Sustainability – Taking the Green Road
SSP1 – 2.6
Sustainability – Taking the Green Road

$80,000$60,000

SSP2 – 4.5
Middle of the Road

$40,000$20,000
$0
2005

2020

2040

2060

2080

2080

Source: Riahi et al, The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview,
licensed under CC BY 4.0.

However, as shown in Figure 5 above, this scenario predicts
the highest global GDP, which is incorrect, given the physicalimpacts anticipated.
A comparison with other scenario-modelling results reveals
inconsistencies, with some providers showing the most severe
negative GDP impacts in the highest-warming scenarios. NGFS
states that ‘for all scenarios and time scales, physical risks
outweigh transition risks.’13 In a current policies scenario (3.2˚Cof warming), NGFS estimates a reduction in global GDP of 18%
by 2100 but caution that this does not include ‘impacts related
to extreme weather, sea-level rise or wider societal impacts
from migration or conflict’, all of which it estimates would
act to further reduce global GDP by 2%. Adaptation costs are
likewise excluded. Other limitations of the IAMs underlying
NGFS scenarios include reliance on carbon prices as the
exclusive policy lever, which fails to capture the full impactsof policy tools, and not accounting for the role of the financial
sector (including feedback between finance and real economy
transition) in mitigation pathways.

14

In a joint paper with the IFoA, Ortec Finance provide a more
severe estimate of impacts, citing a negative GDP impactof 73% in the event of a failed transition.14 Cambridge
Econometrics, whose model Ortec Finance use, estimates thata 4˚C temperature rise would result in a 65% negative impact
to global GDP by 2100.15 Again, the authors advise that thisis likely to be an underestimate as it does not account for
tipping points or other unprecedented changes in the climate
system. The International Monetary Fund’s World Economic
Outlook Report, October 2022 16 reinforces this message, urging
policymakers to establish credible and irreversible climate
policies and stating that the costs of transitioning would be‘dwarfed by the innumerable long-term costs of inaction’.
Further analysis is provided by WTW’s Thinking Ahead Institutein ‘Pay now or pay later’17 where they estimate that “If climate
tipping points, that could magnify the costs of inaction, areconsidered we could see a 50-60% downside to existing
financial assets in a business-as-usual scenario where climate
risks are not addressed. In contrast, taking action to transition
to a well below 2°C world might lead to a loss of 15% of existing
assets which could be partly offset by the positive benefits fromnew primary investment.”

2: Climate scenario modellinggoes mainstream

Climate-change scenario modelling is now increasingly mainstream in financial
services. Financial regulators across the world are mandating that regulated
entities carry out climate-scenario modelling and produce TCFD disclosures.
Financial institutions are developing their capabilities to support risk
management and disclosure.
Financial regulators and central banks from 31 nations haveused climate-change scenario modelling to assess impacts on
their economies and financial systems. This is supported by aclimate-scenario modelling support ecosystem worth hundredsof millions of dollars a year.
However, closer examination shows firms largely rely on
outsourced model providers, many do not yet fully understandthe limitations of the models they are using, and in somecases firms are making public disclosures that raise significant
questions – showing benign economic results in high physicalrisk scenarios, consistent with those detailed in the previous
section. These outputs may provide false comfort to institutions
and advisers. They may be particularly dangerous for regulators
seeking to understand systemic risk, as an aggregation of
benign results may result in misplaced confidence regarding thethreat of climate change to financial resilience.18...over 80% of firms
are now undertaking
climate-scenario analysis,
an increase of over 30%
since the 2019

Snapshot of market practice – use cases andcommonalities
The Global Association of Risk Professionals (GARP) has
carried out four global surveys of climate-risk management at
financial firms, providing a useful summary of market practice.19
The 2022 survey showed that over 80% of firms are now
undertaking climate-scenario analysis, an increase of over 30%
since the 2019 survey result, when under half of firms surveyed
had carried out scenario analysis. A significant driver of thisis regulatory expectations, with GARP stating that: “Nearly
90% of firms report that their regulators have published formal
expectations for climate risk management, while nearly 80% saythat regulators are now requiring them to report their climaterelated risks.”
GARP collaborated with an industry working group sponsoredby UK financial regulators – the Climate Financial Risk Forum(CFRF) – to provide more detailed analysis on climate-change
scenario analysis based on GARP’s survey results for 51 firms,
published in October 2022 by the CFRF.20 This showed that:• Firms are using scenarios to assess financial impact and risk
identification
95% of firms surveyed use the scenarios to assess thefinancial impact of climate change, with 80% of firms using
them for risk identification.
• Firms are using a range of time horizons, including shorterone to five years
Nearly 60% of firms used shorter term (one to five year)
time-horizon scenarios and 80% use medium (five to 10 year)
time horizons as well as longer time horizons.21

15

• The most commonly used scenarios are NGFS orderly,
disorderly and hot house
A range of scenarios are used across the industry including
NGFS, IEA, Representative Concentration Pathways (RCPs),22
SSPs and regulatory scenarios. 11% of companies use ‘other’scenarios, suggesting a level of sophistication in scenario
design and choice.
The most commonly used scenarios for transition risk are
NGFS (orderly, disorderly, hot house). The most commonlyused scenarios for physical risk are RCP8.5, NGFS hot houseand regulatory defined scenarios.
• Scenario choice is driven by the Paris Agreement, current
trajectory and regulators
70% of firms selected scenarios that covered risks that could
arise if the Paris Agreement is met, with 60% selecting
scenarios expected to cover current policy and businessenvironment risks, with around 55% using a regulatory driven
scenario.

The report is clear eyed on the limitations of climate-change
scenario modelling, stating that:“There are certain
challenges and limitations
that these tools might
never be able to overcome
because of the uncertainty
of climate change or
because of the limitationsof modelling and data.”• 2/3rds of firms are now using a baseline scenario to assess
impacts
A significant increase was observed in the number of firms
using a baseline scenario against which to assess impacts,with 65% of firms using a baseline compared with 38% in theprevious year. Of these, around 20% had developed their own
baseline, a similar number used a regulatory scenario, andaround 17% used a regulatory scenario.
When the regulatory scenarios require a substantial amountof effort, this can contribute to the perception that they are
the gold standard in climate-scenario modelling, even when
the regulators themselves point out the weaknesses and areas
for further improvement. Further, the effort required to carryout the complex calculations can mean there is less time formanagement education, interpretation and understanding.

The scenario modelling ecosystem
The United Nations Environment Program Finance Initiative(UNEP FI) 2023 Climate Risk Landscape 23 provides a thoroughoverview of climate-change scenario modelling practices
for physical and transition risk in financial services. As
well as providing details on current practices and areas ofdevelopment, including the trend of aggregation in this sector,
the report provides an overview of climate-change scenario
model providers, listing 16 transition-risk solution providers and19 physical-risk solution providers.

16

The report also makes clear that solution providers have madesignificant efforts to improve their transparency, with many
now providing extensive documentation of models, alongsidetraining.

Models users must choose from a wide variety
of solutions
While the UNEP FI report was largely driven by banking,scenario analysis is becoming ubiquitous in financial services
sectors, with pension schemes, insurance companies andasset managers also developing their capabilities, driven by a
combination of business needs, client and regulatory demand.
In developing their approach, firms must make decisions
on which climate risks they are most interested in (physicalor transition – recognising these are not independent) andthe model methodology, ‘top down’ or ‘bottom up’. With
top-down modelling, firms seek to estimate the impact ofclimate scenarios on global GDP, then national GDP and finallyasset class returns. Bottom up seeks to model the impact
of climate change on individual companies or assets, before
aggregating this into an overall portfolio position. In thispaper, our focus is on top-down modelling of climate change
physical risk, particularly focusing on the hot-house world
scenario, although the principles of understanding limitations
and assumptions apply equally to bottom-up modelling andtransition risk. Other institutions are publishing on climatechange scenario limitations and assumptions, for example the
UK Centre for Greening Finance and Investment.24

A small number of anonymised samples is shown opposite
in Table 2, taken from public TCFD disclosures from regulated
entities, that show the estimated impact on portfolio values ofdifferent climate scenarios.
In displaying these, our intention is not to target any particularmethodology or climate-scenario provider. It is illustrative,
to show the jarring disconnect between climate science andfinancial services. We explore the reasons for this disconnect in
Section 3.
There is a disconnect because there is no plausible future
without global warming. The economics of the energy
transition suggest its inevitability. However, we model theimpact of various climate scenarios against a base case of no
global warming and no energy transition.25 But climate scienceand in particular the emergence of tipping points suggest there
is a level of warming that will cause a very significant loss of
GDP.26 We explore an alternative approach that would reflect
this reality in Section 4.

Sample of publicly disclosed TCFD results frommajor UK investors
No comprehensive sample of TCFD results has been
undertaken. All the institutions that these results are taken fromhave committed to net zero and demonstrate a comprehensive
understanding of climate change and the risks it presents. All
these institutions stated that the hot-house world results arelikely to understate physical risk, possibly significantly.
Three of the institutions surveyed did not provide quantitative
results of climate-change scenario analysis, citing thelimitations and uncertainties inherent in current methodologies.
One institution provided ranges rather than precise figures.
However, these ranges showed the disorderly transition to havea greater impact on the institution’s asset portfolio (>5%) thanthe hot-house scenario (between 2% and 3.5% impact).
Table 2 opposite shows the percentage per annum impact ofdifferent climate scenarios on portfolio returns figures from a
set of anonymised publicly disclosed TCFD reports for longterm scenarios, typically 2050 or 2060. In many cases theresults for the hot-house scenario are similar to those produced
for more benign temperature scenarios. Some results showthat the hot-house scenario results are the most positive
economically.

17

Table 2: Sample TCFD results from UK investors, impact on portfolio
returns per annum, long term

Institution

Orderly

Disorderly

Hot House

Institution 1

-0.2%

-0.2%

-0.1%

Institution 2

-0.1%

-0.1%

Institution 3

-0.1%

-1.0%

Institution 4

0.7%

-0.5%

Institution 5-0.1%

Institution 6

0.0%

-0.5%

-0.4%

-0.2%

In several cases, the failed transition or hot-house world
scenario is shown as the most negative outcome, with someinstitutions providing analysis that equates this to a 1% negative
impact on returns over a long time period (typically 30 or 40
years) which, all other factors being equal, would equate to a
1/3 loss in portfolio value. Other institutions show the hothouse scenario to be only slightly less economically damaging
than a disorderly or orderly transition.
Given the differences in asset portfolios, underlying models andscenario specifications this analysis is necessarily limited.

3: Climate scenarios– a warning for
financial services

In this section we describe at a high level the different stages of a climate model,
what principles actuaries use to support reliable use of models, and how to apply
these to climate modelling. We focus on top-down physical risk modelling andthe hot-house scenario, although the principles apply to all modelling of climatechange scenarios.
Applying actuarial principles to climate modelling shows thatthe observed benign results for the hot-house scenario are theconsequence of a number of significant judgements that are
made throughout the modelling process. These include thespecification of the chosen scenario, key climate modellingassumptions concerning how much and how quickly the planet
will warm for a certain level of GHGs, a damage function that
excludes many of the risks we expect to face, and the choice ofeconomic model.
Consequently, many climate models are severely underestimating the economic impact of climate change because:
1. Modelled scenarios do not incorporate our experience on
climate change and may not be realistic when compared
to experience. There is also limited consideration of higher
warming scenarios.
2. There is considerable uncertainty in key climate-systemmodelling assumptions, including how rapidly the climate
will warm for a given level of emissions, which are likely tobe prudent meaning the carbon budget for limiting global
warming to 1.5°C may now be exhausted. However, nomargins are currently included to represent this uncertainty.
3. Damage functions that are used to estimate the economic
impacts of climate change exclude many of the risks we
expect to face, such as those impacts from tipping points, or
societal consequences such as involuntary mass migration.

18

4. General equilibrium models that are widely used toestimate economic impacts contain a number of simplifying
assumptions that do not hold in the real world.
We conclude that it is essential for model users to be climate
literate in order to understand the context in which models
are used and the limitations that apply to climate models.
They should be used alongside narrative scenarios to provide
direction and rank on risks – but users must not interpret
results as accurate.
In particular, the observed benign results for the hot-house
world are deeply flawed and underestimate the impact of therisks we expect to face.

Many climate models areseverely under-estimating
the economic impact ofclimate change.

History is replete with incidents in which we haveplaced too much faith in models.
Actuarial principles
Actuaries have well-established standards that apply to‘technical actuarial work’. In the UK, the over-arching objective
set for actuarial work by the Financial Reporting Council (FRC)
is that it should meet the Reliability Objective, as stated in
TAS100.27 This says:“To allow the intended user to place a high degree of relianceon actuarial information, practitioners must ensure the actuarial
information, including the communication of any inherent
uncertainty, is relevant, based on transparent and appropriate
assumptions, complete and comprehensible.”
Underpinning this is a set of principles 28 for actuarial work
covering seven areas: Risk Identification, Judgement,
Data, Assumptions, Models, and Communications andDocumentation, which are detailed in Appendix C. By applying
these principles to the area of climate-change scenario analysis,
we can test whether current approaches meet the standards for
actuarial work.
A clear theme that runs through these principles is the needto explain judgements, methodologies and assumptions,particularly where these are material and contribute tolimitations or uncertainties. Actuaries themselves have been
warned by external parties 29 and their profession 30 about
the need to appropriately consider climate change in theirprofessional advice, a warning reinforced by the FRC’s updated

Technical Actuarial Standards,31 which specifically call out
climate change as a material external factor that may influence
actuarial work.
These principles are important, as they are designed to mitigate
the risk of placing too much faith in models. History is repletewith incidents in which we have placed too much faith inmodels, including the global financial crisis, the collapse ofLong-term Capital Management, and, more recently, the UK
pension scheme LDI crisis. A common theme is that models
under-estimate the level of risk because it is mathematicallytractable to do so, in some cases due to underpinningassumptions that do not hold in the real world.
Figure 6 below shows a simplified climate-change scenario
modelling process.
This challenge requires significant judgements in many areas,
including which scenarios to model, selection of appropriate
models and methodologies, modelling linkages between the
Earth’s physical climate system and human society, whichdata sets to use to parameterise those models, and how toincorporate uncertainty.

Figure 6: The climate-change modelling process

19

I: Emissions

II: Warming

III: Damages

The first step is to estimate how
GHGs emissions will change inthe future, as this will determine
the levels of atmospheric GHGs,
which in turn will drive warming.
This is a key specification of any
climate scenario.

Following this, a key questionis how much warming will be
driven by a certain level of GHGs
and how quickly this warming
will happen, as this will drive thefrequency and severity of theacute and chronic physical risks
we expect to be impacted by.
This is driven by climate models,
which are parameterised to past
climate-system changes.

Finally, we seek to estimate howmuch damage these physicalrisks will inflict – what could theimpact be on individual assets,companies, countries and theglobal economy.

I: Emissions
Scenario choice and emissions
Most firms begin by using three climate scenarios, often thosespecified by NGFS or local regulators. A recent paper32 foundthat the focus of IPCC reports has drifted to focus on lower
temperatures over time, perhaps reflecting the focus on net
zero and the goals of the Paris Agreement.
The report found that there has been relatively limited
consideration of the impacts of higher temperature and, as ouranalysis has shown, the modelled results for a hot-house world
are overly benign.
However, we are now at a point where the level of greenhousegases in the atmosphere is double the pre-industrial level,33
driving accelerating warming. This level of emissions is inline with the high emissions scenario RCP8.5, which the
IPCC estimate would lead to over 2°C of warming by 2050.
As illustrated in Section I, there is also a significant range of
uncertainty associated with carbon budgets.
A faster warming planet will drive increasingly severe acutephysical risks, increase the pace of chronic physical risks, andincrease the likelihood of triggering multiple climate tipping
points, which collectively act to further accelerate the rate ofclimate change and increase physical risks.

Organisations should therefore think carefully about choice of
scenario, recognising that although regulatory scenarios havethe advantage of providing consistency, they may not capture
recent experience, may not fully reflect the risks we face, andmay not be particularly realistic or even likely. Organisations
must also recognise that the regulatory scenarios are not stressor tail scenarios (eg 1-in-200) that are familiar from regulatory
capital requirements.
More sophisticated firms are now working with model providers
to develop bespoke scenarios that they feel reflect moreaccurately some of the risk drivers we face into – on both
physical and transition risk.
Some organisations are also developing a baseline or best
estimate scenario that takes into account factors such as
those described in the previous section. Qualitative narratives
should be developed initially, with modelling undertaken
where appropriate to do so. However, given the challenges
of calibrating a model to a complex basket of never before
experienced risks, users should beware of spurious accuracy– it is better to be roughly right than precisely wrong.

II: Warming
The earth’s climate may be more sensitive than we thought
A simple analogy for global warming is to think of the planet as
an electric oven and the level of GHGs in the atmosphere as thetemperature setting. If we increase GHG levels, we are turningup the temperature – but it takes time for the oven to come up
to temperature.
Without delving too deeply into climate science, for the
purposes of climate-change scenario analysis we are interested
in two key points:
A. How much the planet will warm for a given level of GHGs?
B. How quickly the planet will warm?

20

A. How much will the planet warm for a given level of GHGs?
Equilibrium climate sensitivity (ECS) is one of the key
assumptions used to derive estimates of warming for different
levels of GHGs. A short briefing on ECS provided by Carbon
Brief,34 states that ECS was first defined in 1979 in the Charneyreport from the National Academy of Sciences in the US. This
report estimated that if we doubled atmospheric CO2, then ECS
would be between 1.5°C and 4.5°C.
ECS estimates have remained remarkably stable over time, the
IPCC’s 2021 Sixth Assessment Report giving an updated rangeof 2.5°C–4°C, with a best estimate of 3°C. Some scientists
estimate that the best estimate could be higher at 4°C due
to uncertainties associated with key variables such as aerosol
cooling and the rate at which ocean mixing occurs.35

Some scientists estimate that Earth-system sensitivity
may be double ECS, after allowing for thefull impact of reducing ice sheets.

A key takeaway is that an ECS of 3°C means that if we double
GHGs, as we have, then we would expect the planet to warmby 3°C.

ice sheets. A full risk assessment of climate change should take
Earth-system sensitivity into account and recognise that therate of warming may be faster than we have anticipated.

Although it is hard to be precise about what conditions wemight experience once the planet warms by this amount,scientists estimate this level of GHGs to be comparable to
the Pliocene period, when sea level may have been 17 metres
higher, global temperatures 2˚C–3˚C higher and the poles
ice free.

B. How quickly will the planet warm for a given level of GHGs?

However, ECS has a wide range of uncertainty and as Kemp
et al 36 point out, is heavy tailed, with an 18% chance of being
greater than 4.5˚C.
This uncertainty is partially reflected in the overlapping
temperature ranges predicted by the various RCPs (as shownin Section I, Figure 3) – with the lower temperature range of
RCP8.5 overlapping the higher temperature range of RCP7,
and so on.
It is also important to note that ECS is calculated without theeffect of longer-term feedbacks such as changes in ice sheets
and vegetation. Earth-system sensitivity, which allows for thesechanges, has been estimated to be significantly higher than
ECS. Some scientists estimate that Earth-system sensitivity may
be double ECS, after allowing for the full impact of reducing

Climate response time (CRT) is also uncertain and hard to
estimate. On the one hand, a long CRT is problematic, as
the time lag between rising GHG levels and changes to theclimate may be long, meaning we may not take action to
reduce emissions as we are not yet experiencing the warming
associated with those emissions. On the other hand, a long CRT
means we have an opportunity to reduce GHG levels before theclimate warms too much.
Overall, we conclude that there is significant uncertainty aroundthe warming associated with a particular emissions scenario.
It is likely that we have now exhausted the carbon budget for
1.5°C and may breach 2˚C by 2050 with the current level of
GHGs in the atmosphere. If ECS is closer to the top of the range
or even above it, we may already be headed for higher warming
even if emissions remain in the RCP2.6 to RCP4.5 range.
Scenario users need to think through the implications of this in
scenario design, as well as developing a view on what is likely
as emissions continue to rise along with the global temperature.

III: Damages
Choice of damage function and economic
model drives material changes in results

Damage functions exclude many of the risks
anticipated to arise from climate change

In this section we examine damage functions, showing thatcalibration choices drive very material results differences, aswell as highlighting the risks excluded from these damage
functions. We also examine the choice of macro-economic
model, referencing analysis that shows that a driver of somecounter-intuitive results is the assumptions underlying
traditional general equilibrium economic models.

As the climate continues to warm we are likely to face
increased extreme weather events, changing climaticconditions driving floods and droughts, heat spikes and in
the longer term glacial melt and sea level rise. We also risk
triggering multiple climate tipping points which would act
to further accelerate climate change or its impacts. These
impacts could drive second order events such as shocks toglobal food supplies or involuntary mass migration.

21

Economists have estimated the economic losses from climatechange in a hot-house scenario to be “as low as 2.1% of global
economic production for a 3˚C rise in global average surface
temperature, and 7.9% for a 6˚C rise.” In the paper this quote
is from ‘Economists’ erroneous estimates of damages fromclimate change’37 Keen et al look at why this is the case,
exploring the methodologies used and the striking disconnect
from climate science. In particular, the methodologies used bysome economists exclude many of the risks we expect to face,
including those from tipping points. Further analysis of the
weaknesses and limitations of IAMs is provided by Stern andStiglitz.38

scenarios (which include Climate Biennial Exploratory Scenario(CBES) scenarios) may understate climate exposures andvulnerabilities.

Any methodology based on these economic models will
therefore also exclude these risks, as is the case with many
current climate scenarios used in financial services. NGFS
estimates a reduction in global GDP of 18% by 2100 fromchronic physical risks but caution that this does not include‘impacts related to extreme weather, sea-level rise or wider
societal impacts from migration or conflict. For given countries
these would likely strongly increase the physical risk. Theseestimates also do not fully capture adaptation, which would
reduce impacts but require significant investment.’ 39 Including
acute physical risks increases this GDP impact to nearly 20%
by 2100, although this is based on cyclones and river flood
damages, rather than all physical risks. This is a significant
increase from its previous estimate of a 6% reduction in global
GDP, which NGFS recognises was too conservative.

An alternative academic paper (Burke-Tanutama ‘BT’, 2019)provides higher estimates for gradual physical shocks to GDP
and is used to underpin the Cambridge Econometrics model.
The BT approach assumes a higher temperature level has anegative impact on GDP growth, as well as GDP level, which
is why GDP impacts are higher than KW’s – as GDP level isnegatively impacted as well as growth. However, this approachstill excludes many of the risks detailed in the previous section,such as tipping points, because it works from historical data stillgiving a conservative estimate of the damage function.

Indeed, NGFS has reiterated this point by issuing a jointstatement with the Financial Stability Board (FSB)40 on
15 Nov 2022, pointing out that scenarios derived from NGFS

This damage function is not distributed evenly acrosseconomies – some equatorial countries face GDP impacts ofover 30% while some Northern Hemisphere countries face
impacts of less than 10%. This is because NGFS damage
functions are calibrated to an academic paper (Kalkuhl & Wenz
‘KW’, 2020) that estimates the impact on productivity of higher
temperatures on GDP level but, as stated above, does not
capture other risks.

Figure 7 below, from ‘Integrated perspective on translating
biophysical to economic impacts of climate change’41 shows acomparison of results for global GDP loss due to temperaturerise, using the BT and KW methodologies for the Failed
Transition scenario. The KW paper leads to a 10% global GDP
loss, compared to a 63% GDP loss by 2100 using BT, althoughby 2050 the two approaches are closer, 2% vs 10%.

Figure 7: Comparison of GDP losses by 2100 based on two different methodologies

Final impacts, top down
80
Ref. 42GDP loss (%)

60
Burke
et al
(2015)

40

Ref. 53
Ref. 41
Ref. 8
Ref. 101

20
K&W(2020)
0
1˚C

2˚C

3˚C

4˚C

5˚C

Temperature increase above pre-industrial level
Source: Piontek et al, ‘Integrated perspective on translating biophysical to economic impacts of climate change’, 2021. Reproduced with permission.

22

Ref. 7

In summary, commonly used loss functions are based on pastdata and exclude many of the risks we expect to face. Choiceof loss function has a very material impact on results – varying
from 6% to 18% to 63% loss in global GDP by 2100. The NGFS
estimate of 20% (including acute physical losses) should beviewed as a conservative lower bound for expected GDP losses
we should expect if we do not change course.

Macro-economic model choice has a verysignificant impact on results
Public reference scenarios, including the NGFS, rely on models
referred to as computable general equilibrium models (CGE).
CGE models were created by the climate-science community to
inform high-level public policy making. Traditionally, they havebeen used to assess the socio-economic impacts of various
climate pathways. The macroeconomic modules of thesemodels had a very different use case from how the financial
sector is currently applying them. They have some simplifying
neoclassical economics assumptions which generate outputs
that do not adequately capture real-world economic dynamics,
such as:• Individuals act only in their own self-interests and are
dedicated to maximising their utility• Individuals have perfect knowledge and perfect foresight anduse this information to calculate all possible outcomes andoptimise their decisions• CGE models results are presented as long-term outcomes,
without considering possible upheaval or length of thetransition process• Money is ‘neutral’(required only to facilitate real transactions)and fixed in supply.
• Banks are treated merely as intermediaries, failing torecognise their role in money creation.42
Non-equilibrium models, such as the post-Keynesian E3ME
model maintained by Cambridge Econometrics, still have
limitations but are designed to simulate real-world economic
dynamics more accurately. For example, actors are notassumed to be all knowing, perfectly efficient entities but
derive behavioural parameters from historical relationships.
Also, money can be created by banks through new loans andthis investment is not crowded out. Further analysis on thisis provided in an article in The Actuary magazine from March
2022,43 which emphasises how significant model choice is on
results.

23

Non-equilibrium models,such as the post-Keynesian
E3ME model maintained byCambridge Econometrics,
still have limitations but aredesigned to simulate realworld economic dynamics
more accurately.

4: A new beginning“A model might show you some risks, but not the risks of using it. Moreover, models
are built on a finite set of parameters, while reality affords us infinite sources of risks.” 44
Nassim Nicholas Taleb was not describing climate-change
scenario modelling when he used these words but they areapplicable nonetheless. Climate change is complex, nuanced
and characterised by deep uncertainty – and it is essentialthat model users understand this – as well as developing theirunderstanding of how climate risks could impact their models.

Figure 8: Cascading global climate failure

Globalwarming

To address this, further work will be required on bothquantitative and qualitative fronts. We suggest a possible way
forward below.

Extremeweather events

Sea-level rise

Qualitative – rich narrative scenarios
As illustrated in Figure 8 opposite from ‘Climate Endgame:
Exploring catastrophic climate change scenarios’,45 global
warming will impact a number of interconnected risk drivers,
which in turn will impact factors that influence financial
markets and financial institution solvency. Firms should develop
qualitative scenarios that explore how these risks could cascade
and what actions could be taken.
Visualisations of climate impacts can be helpful to drive debate
and illustrate potential future scenarios, such as flood maps
showing the difference between areas that will be inundated
in a 1.5˚C degree scenario compared to a 4˚C degree scenario.
See, for example: https://coastal.climatecentral.org/ andfurther thoughts on approach in Appendix A.

Quantitative – a new baseline and an updated
loss function
A practical fix may be to ‘invert’ scenario analysis and use areverse stress test approach, as used in financial services risk
management. This would start with what we want to avoid,
then work backwards from there. Rather than carrying out
climate-scenario analysis against a fictional world in whichclimate change is not happening, we could work from a new
baseline of achieving the net-zero transition. This is the best
outcome we can hope for and resolves the issues of having abaseline that assumes neither climate change nor the energy
transition is happening.

24

Vector-borne
disease

Economic
inequality

Displacement

International andlocal conflictMortalityStatefragility

Biodiversity

Ecosystem
services

Food, fuel andwater shortages(resource scarcity)

Source: Kemp et al, ‘Climate Endgame: Exploring catastrophic climate change
scenarios’ (2022). Licensed under CC by 4.0.

Climate change is complex, nuanced andcharacterised by deep uncertainty – and it is essentialthat model users understand this.

Figure 9: Climate damage functions – % GDP loss vs temperature

Damages as percent of GDP

Damage functions vs temperature anomaly
100%

Logistic 4 degrees

80%

Logistic 5 degrees

60%

Logistic 6 degrees
Quadratic

40%

Disasters/GDP

20%
0%
0

1

2

3

4

5

Global Warming Temperature Anomaly w.r.t. 1900
Source: Carbon Tracker (forthcoming), Keen et al, IFoA analysis. Reproduced with permission.

A relatively simple log damage function could be used thatassumes 100% GDP loss at a certain level of warming, say 6˚C,
5˚C, or 4˚C, although some may argue that even 3˚C would be
extremely challenging to adapt to, and certainly sensitivities
should be undertaken at all of these.
Figure 9 above, adapted from analysis undertaken by Carbon
Tracker, illustrates this, as well as comparing the output withthe current quadratic damage function used by economists.
The quadratic damage function is what underpins the economic
models described in previous sections. This is based ondamages in the future being an extrapolation of damages in thepast ‘when it got a bit warm’. This damage function excludes
tipping points and many of the risks we expect to face. As
observed from the graph, this damage function does not show
significant GDP losses, even at 5˚C of warming.
The logistic damage function assumes total economic
destruction at c.6˚C but close to total at 5˚C, based on analysis
provided by Carbon Tracker. This approach does not explicitly
model the impact of the various risks we will face, rather ittakes the approach that we will be unable to adapt beyonda certain level of warming, recognising the challenges ofaccurately modelling the unknown impact of tipping points andother factors.

25

The red and orange lines show an approximation of GDP losses
up to 100% at 4˚C and 5˚C of warming. This is a global averageand different countries would be impacted at different rates.
An alternative would be to calibrate to 90% or 80% GDP loss,
assuming some adaptation that permits survival of somehuman population with associated residual economic activity.
Three key assumptions are needed, which are:i. How much warming we expect for a certain level of GHGs
ii. What the rate of warming will beiii. At what temperature do we cease to function as a society?
Using a logistic loss function implies significant economic loss
occurs at 2˚C of warming, then between 2˚C and 3˚C, although
there is significant variation depending on the assumptions
used. With the 6˚C ruin parameterisation around 30% GDP loss
occurs at 3˚C of warming compared with 80% GDP loss using
the 4˚C ruin parameterisation. Taking this approach would
drive more realistic TCFD results than the benign hot-house
world disclosures we currently see, and is arguably morevaluable in terms of considering the possible implications ofadverse scenarios.

There is uncertainty around how much warming we will
experience. As described in the previous section, atmospheric
GHGs are now double their pre-industrial level, which is what
ECS is calibrated to. A reminder that best estimate ECS = 3˚Cbut there is an 18% chance that ECS>4.5˚C.
Earth-system sensitivity is greater than ECS, as ECS assumes
ice sheets and vegetation fixed, with a possibility that ESS
is significantly greater than ECS. Conservatively, there is anargument for at least a 20% chance that we may be on a
trajectory to 5˚C or more of warming at current levels of GHGs.
The pace of warming is also uncertain. However, some scientists
now estimate warming of 0.3˚C per decade or around 1˚Cevery 30 years, which would imply warming of greater than 2˚Cby 2050 and 3˚C by 2080. This is well within life expectancy formany in workplace schemes now and in range for the European
Insurance and Occupational Pensions Authority (EIOPA) who
have specified 80 years as long range for the Own Risk andSolvency Assessment (ORSA).
Put another way, at what point do we expect 50% GDP
destruction – somewhere between 2070 and 2090 depending
on how you parameterise the distribution. It is worth a momentof reflection to consider what sort of catastrophic chain of
events would lead to this level of economic destruction.
This analysis provides a compelling logic for net zero becoming
part of fiduciary duty, as if we do not mitigate climate change,
it will be exceptionally challenging to provide financial returns.

26... at what point do
we expect 50% GDP
destruction – somewhere
between 2070 and 2090
depending on how
you parameterise the
distribution.

Appendix A

Example qualitative, narrative scenario

A complementary approach is to provide a narrative scenario,
especially where quantitative scenarios are ill-equipped
to effectively model the impacts of tipping points and thecascading effects of climate change. Instead, descriptions canbe helpful for decision-makers to understand the potential
impacts of a hot-house world for companies and investors. One
area of financial risk that has previously been articulated is theimpact of climate change on the insurance sector – insurability
is not limitless and comes at a price. Insurance leaders haveunequivocally stated that if climate change raises averagetemperatures to 4˚C above pre-industrial levels most assets
will be uninsurable.46 Without insurance, investment, finance,business slow to a halt – we will no longer have an economy.
Governments will no longer have a tax base from which todeliver vital services or repay coupons on gilts.
Using visualisations, we can also look at the physical, land use
and population movement impacts to consider the potentialchange to our Earth’s regions in terms of productivity andhabitability. Through these narratives and visualisations, we canconsider the impacts a 4˚C rise would have on business andinvestments. For example, Climate Central 47 is a website thatprovides visualisations of sea-level rise, showing land that isprojected to be below the tideline by 2050. This in turn can beused to inform estimates of involuntary mass migration, which
can help decision-makers take the actions they need to today
to avert this potentially financial and human disaster.

27

Insurance leaders
have unequivocallystated that if climatechange raises averagetemperatures to 4˚Cabove pre-industrial
levels most assets will
be uninsurable.
47

Appendix B

SSP creation diagram

Figure 11: Schematic of process for creating Shared Socioeconomic Pathways

Narratives

Baseline scenarios

Mitigation scenarios(Storylines)• Six IAMs
O’Neill et al.

• Five marker scenarios• 19 non-marker
scenarios depicting
uncertainties

SSP Scenario drivers• Shared policy
assumptions• Four long-term
radiative forcing targets• 81 mitigation scenarios• Assessment of costs
and feasibility

Population

Urbanisation

GDP

KC & Lutz

Jiang & O’Neill(1) Dellink et al(2) Crespo(3) Laimbach et al

Models: AIM-CGE, GCAM, IMAGE, MESSAGE-GLOBIOM,REMIND-MagPie, WITCH-GLOBIOM
Calvin et al., Kriegler et al., van Vuuren et al., Rao et al.,Fricko et all., Fuijimori et al., Bauer et al., Popp et al.,SSP Web-database
https://secure.iiasa.ac.at/web-apps/ene/SspDb/

Country projections:

IAM output for five regions:GDP, POP, Education,
Urbanisation• Energy supply & demand (Bauer et al.)• Air pollution and aerosol emissions (Rao et al.)• Land-use & land-cover change (Popp et al.)• Mitigation costs• GHG emissions• Prices, etc

Source: Riaha et al, ‘The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas
emissions implications: An overview’, 2017. Licensed under CC BY 4.0
The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications:An overview - ScienceDirect28

Appendix C

Principles for Actuarial Work

General Actuarial Standards - Version 2.0 (frc.org.uk)• Risk identification
Practitioners carrying out technical actuarial work must
identify and consider all relevant material factors andrelevant material risks that may affect or have the potential
to influence their technical actuarial work and which thepractitioner might reasonably be expected to know about at
the time of carrying out the work.
• Judgement
Practitioners must exercise judgement in a reasoned andjustifiable manner, so that the intended user can rely on the
resulting actuarial information.
• DataPractitioners carrying out technical actuarial work mustseek to ensure data is sufficiently accurate, complete andappropriate, so that the intended user can rely on the
resulting actuarial information.
• Assumptions
Assumptions used, or proposed for use, by practitioners
in their technical actuarial work must be appropriate, sothat the intended user can rely on the resulting actuarial
information.

29• Models
Practitioners must ensure models used in their technicalactuarial work are fit for purpose and subject to sufficient
controls and testing, so that the intended user can rely on the
resulting actuarial information.
• Documentation
Practitioners must ensure documentation relating to theirtechnical actuarial work contains sufficient detail to enable
technically competent persons responsible for reviewing
or providing assurance in relation to the technical actuarial
work to understand the matters involved and assess thejudgements made.
• Communications
Practitioners’ communications must be clear, comprehensive
and comprehensible, so that the intended user canreasonably be expected to understand matters relevant toactuarial information and make informed decisions.

References1.

See www.frc.org.uk/actuaries/technical-actuarial-standards

2.

Glasgow Financial Alliance for Net Zero (gfanzero.com)

3.

CCAG PositionPaper CriticalPathway.pdf (squarespace.com)

23. The 2023 Climate Risk Landscape – United Nations Environment –Finance Initiative (unepfi.org)

4.

https://www.theguardian.com/world/2023/mar/30/meltingantarctic-ice-predicted-to-cause-rapid-slowdown-of-deep-oceancurrent-by-2050

24. Toward a Framework for Assessing and Using Current Climate Risk
Scenarios Within Financial Decisions

5.

Exceeding 1.5°C global warming could trigger multiple climate
tipping points | Science

6.

Trajectories of the Earth System in the Anthropocene | PNAS

26. Climate Endgame: Exploring catastrophic climate change
scenarios | PNAS

7.

Climate emergency final report.pdf (actuaries.org.uk)

27. frc.org.uk

8.

See eg Climate emergency final report.pdf (actuaries.org.uk) or
Pay now or pay later? - Thinking Ahead Institute

28. General Actuarial Standards - Version 2.0 (frc.org.uk)

9.

The 2023 Climate Risk Landscape – United Nations Environment –Finance Initiative (unepfi.org)

29. https://www.clientearth.org/latest/documents/risky-businessclimate-change-and-professional-liability-risks-for-db-pensionsactuaries/

10. Intergovernmental Panel on Climate Change
11. Network for Greening the Financial System
12. International Energy Agency
13. NGFS climate scenarios for central banks and supervisors.pdf
14. Climate scenario analysis - An illustration of potential long-term
economic & financial market impacts
15. IPCC report: the macroeconomic impacts of climate action andinaction - Cambridge Econometrics (camecon.com)
16. World Economic Outlook, October 2022 (imf.org),
Near-Term Macroeconomic Impact of Decarbonization Policies
17. Pay now or pay later? - Thinking Ahead Institute
18. The economy is a complex adaptive system – it is unclear that
aggregate outcomes can be inferred from the impact on individual
actors. Beinhocker, The Origin of Wealth: The Radical Remaking of
Economics and What it Means for Business and Society, 2007.
19. GRI_22ClimateRiskSurveyReport.pdf (garp.org)
20. CFRF Guide 2022: Scenario Analysis - financial firms (fca.org.uk)
21. EIOPA consider 5-10 yrs short term, 30 yrs med term and 80yrs
long term for the purpose of the ORSA: https://www.eiopa.europa.
eu/publications/opinion-supervision-use-climate-change-riskscenarios-orsa_en

30

22. Representative Concentration Pathways – emissions trajectories
defined by IPCC Topic 2: Future changes, risks and impacts — IPCC

25. Climate tipping points change everything - Thinking Ahead
Institute

30. https://actuaries.org.uk/media/btbbojpz/2022-climate-changeand-sustainability-risk-alert-final.pdf
31. General Actuarial Standards - Version 2.0 (frc.org.uk)
Paragraph A1.2
32. Climate Endgame: Exploring catastrophic climate change
scenarios | PNAS
33. [2212.04474] Global warming in the pipeline (arxiv.org)(Noting paper is not yet peer reviewed)
34. Explainer: How scientists estimate climate sensitivity(carbonbrief.org)
35. [2212.04474] Global warming in the pipeline (arxiv.org)(Noting paper is not yet peer reviewed)
36. Climate Endgame: Exploring catastrophic climate change
scenarios | PNAS
37. 2108.07847.pdf (arxiv.org)
38. Full article: The economics of immense risk, urgent action andradical change: towards new approaches to the economics ofclimate change (tandfonline.com)
39. NGFS Climate scenarios for central banks and supervisors.pdf
40. Current climate scenario analysis exercises may understate
climate exposures and vulnerabilities, warn FSB and NGFS |Banque de France

41. Integrated perspective on translating biophysical to economic
impacts of climate change (Piontek et al, 2021)
42. https://www.bankofengland.co.uk/-/media/boe/files/quarterlybulletin/2014/money-creation-in-the-modern-economy.pdf
43. Under the bonnet: different economic engines that drive climatechange scenario models | The Actuary
44. Against Value-at-Risk (fooledbyrandomness.com)
45. Climate Endgame: Exploring catastrophic climate change
scenarios | PNAS
46. https://www.bloomberg.com/news/articles/2018-01-25/
basements-in-new-york-mumbai-seen-as-uninsurable-in-nextdecade
47. Climate Central | Land projected to be below annual flood levelin 205031

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