Climate change poses a systemic risk to institutional investors. All portfolios are exposed to it, yet the impacts will be uneven across asset classes, sectors and geographies. Understanding how this could play out is of central importance to investors’ response to the climate challenge. A key approach is the use of scenario analysis to test the resilience of the portfolio to a number of future states. This can further be developed for financial analysis.

This paper primarily seeks to help investors, both Asset Owners and Asset Managers and their service providers to:

  1. understand an end point ambition requires a scenario pathway to be of use in financial analysis;
  2. understand the scenario pathway architecture (defined in this paper as key variables, metrics, attributes and drivers) determine the financial impact of any scenario. This can be used to compare and contrast scenarios;
  3. understand how climate scenarios can then be used in risk analysis of their own portfolios and engagement with companies following the Paris Agreement and the IPCC SR1.5°C study;
  4. understand how scenarios can then become base case forecasts to begin to inform actual business and portfolio planning and decisions using business level metrics such as production, capex and emissions, which leads to action.

Investors can use scenarios to inform engagement with companies and/or directly to inform their portfolio construction.

Whatever investors adopt will be of great interest to companies and should certainly be a key input to their own thinking and approach.

This is also of relevance in a TCFD disclosure/reporting context for investors, as well as the EU sustainable finance taxonomy, which takes a bottom up economic activity approach and has set thresholds following a trajectory consistent with the EU -55% by 2030 and Net Zero by 2050.

The NGFS and other regulatory bodies, such as EIOPA, are also working on scenarios for full blown stress testing for financial institutions which may have implications for investors too. The classifications of “orderly vs disorderly” and “met vs unmet” will become well used, as will scenarios fitting into that.

What is happening now?

Currently, investors are focussed on three aspects of climate scenario architecture:

  1. Resilience and risk testing (encouraged by the TCFD) and choosing a scenario as a function of whether it meets a “temperature outcome”.
  2. Setting a “net zero target” (usually 2050) associated with that:
    • Whatever temperature outcome we will ultimately achieve, we will have to get to net zero to stabilize temperatures.
    • The sooner we get to net zero the better to reduce the existential threat of climate change.
  3. For financial leaders who are prepared to adopt a climate constraint now in order to influence change this would extend to aligning their portfolio to a scenario/target.

This approach to choosing scenarios and targets suffers from several challenges:

  • Temperature outcomes may hide fundamental differences in scenario architecture, and therefore near-term pathways, with dramatic ramifications for the actual ambition.
  • Long-term net zero targets are important, but could become “time washing” where long-term goals are set without short-term accountability and the opportunity to verify them.

Many of the more ambitious climate constrained scenarios are still considered “pie in the sky” and tail risks, useful for long-term resilience testing, and even adopted by “ambitious investors”. However, as such they are not necessarily used by “mainstream” investors in their day to day investment process. This is because many Investors simply have not been convinced of policy and technology assumptions while scenarios architecture for long-term temperature targets tends to assume economically optimal pathways.

This also points to looking at scenarios that do not optimise for temperature but set out assumptions that might actually happen.

This paper concludes that:

  • The pathway as defined in the “scenario architecture” is crucial for financial analysis.
  • The IEA SDS and B2DS are commonly used as a base case or reference point at present in the context of resilience and stress testing, with further scenarios under development by the NGFS and others 2° Investing Initiative (2DII).

Most discussions around net zero treat the “well below 2°C” ambition as a “tail scenario” or something more adapted to stress-testing, rather than base-case planning. One of the reasons for that is that many scenarios that create net zero pathways generally suffer from two flaws, making them less relevant for base case use, namely:

  • Highly unrealistic short-term policy ambition, and
  • Economic optimization” inconsistent with a more realistic “messy” and disruptive transition.

In this context, “mainstream” investor planning or base cases should reflect a policy and techno-economic scenario based on high conviction expectations or forecasts, underpinned by key real-world assumptions.

The Inevitable Policy Response Forecast Policy Scenario (IPR FPS), commissioned by PRI, represents this type of policy forecast scenario with a “real world” approach to modelling. IPR FPS tries to solve the problem by creating an alternative relevant base case that reflects the “inevitability” of net zero through the concept of the inevitable policy response (IPR) by 2025, even if the scenario itself does not necessarily meet temperature goals without a second policy ratchet in the medium-term.

In terms of architecture (defined in this paper as key variables, metrics, attributes and drivers), we would highlight the following key aspects to any climate scenario pathway in an investor context:

Table 01: Key variables associated with emissions pathway

Metrics Description
Source: ETA
Target temperature ove pre-industrial levels This describes the temperature above pre-industrial levels with which the scenario is consistent, in most cases this is a constraint reflected in the carbon budget and so the pathway (or an outcome of assumptions such as with IPR).
Probability of achieving temperature target This is the probability of achieving a particular temperature outcome. This is a critical datapoint, as the uncertainties within climate science lead to wide ranges of outcomes meeting that a probabilistic presentation is useful.
Carbon emissions budgets Global warming is fundamentally linked to the absolute concentration of greenhouse gases in the atmosphere. To stabilise global temperature at any level vs pre-industrial, there is then a finite amount of emissions that can be released before net emissions need to reach zero – for C02 emissions this can be referred to as a carbon budget. (See Figure 22 in Appendix).
Scenario start year This is the year the analysis of the particular scenario model starts.
Emissions peak This is the year at which emissions peak. 
Year temperature target is first reached This the year when the temperature target is first reached.
Net zero year  – emerging as a key metric This is the year where globally there are zero net emissions which means any residual direct emissions are offset by CDR (e.g. NETS including BECCS).
Overshoot The degree of temperature overshoot above the set target of the scenario. Overshoot can occur during the pathway time frime.
Return year Return year refers to the year when the temperature returns again to target after overshoot.
Scenario transition modelled end year This is the last year of the detailed modelling in the scenario. At this point the temperature target may not be stable and further assumptions are required to establish that.
Emissions reduction on base year % This is the percentage reduction of emissions highlighted in the scenario at its end year measured against its base year which is not always the first year of the scenario model. Again this needs to be put in the context of a pathway –  the slope of this curve shows timing of impact.


Table 02: Associated key economic and financial variables

Metrics Description
Source: ETA

Geography and sector

Geographic jurisdictions

Key sectors covered

The more granularity the more useful for investment analysis.

Countries and regions in scope of analysis.

The range of sectors included in the scenarios. Note that this includes any references to sectors at any point on the supply chain, thus including end use sectors as well as primary producers.

Key policy drivers

Carbon prices


Carbon pricing is the most cited policy method to optimize the shift of capital from high to low carbon assets and, because it can be added to the asset level, represents a favourite method for modellers and analysts. Indeed, it is often used as an overall proxy for all policies by modellers. Hence need to identify if endogenous or exgenous to the model.

Key economics and financial variables

Technology trajectories/demand profiles  –  see below other key variables

This is what drives the economic results of the scenario. They are both inputs and outputs.

These are not a single data point but are a series of (often complex) signposts and datapoints that define how various technologies are developing e.g. volume of electric cars, GW of renewable capacity. These in effect set out production profiles and so reflect expected demand in the economy.

Asset level For investors and companies, granular real sset data and financial data is needed to apply economic results to portfolios and indeed in engagement with companies. So, this level has to be linked to the technology/demand profiles. An example is Carbon Tracker’s ’Breaking the Habit’ report and the 2DII SEI metrics projects.
Associated capital investment The amount of capital required in order to achieve the various demand/production/emissions targets.
Stranded assets Stranded assets are now generally accepted to be those assets that at some time prior to the end of their economic life (as assumed at the investment decision point), are no longer able to earn an economic return (i.e. meet the company’s internal rate of return), as a result of changes associated with the transition to a low-carbon economy (lower than anticipated demand/prices.
Associated commodity demand and prices Energy scenarios in particular have implications for the broad commodity level analysis in terms of demand/supply and price.
Other policy levers These describe the types of policy needed to incentive investment in new technologies or assets to achieve various emissions reduction targets. IPR sets these policy levers out in detail. In some models these in turn are proxied by a carbon price.
Other key technology variables to identify These inputs/assumptions make a substantive difference to the investment outlook in a scenario.
CCS/CCSU CSS in Carbon Capture and Storage which describes the capture of C02 and the subsequent geological storage of those gases. Carbon Capture Storaage and Use extends this to using carbon in various technologies.
NETS/CDR NETS is Negative Emissions Technology (sometimes knows as CDR – Carbon Dioxide Removal) which describe any technology or series of processes where there is a reduction in emissions by either capturing the emissions at the point of process of physically extracting the emissions from the atmosphere. BECCs is one form of NETs.
BECCs BECCs describes capturing CO2 from bioenegy applications and sequestering it through Carbon Capture and Storage.