At the heart of climate disclosures is a “climate scenario analysis” or “climate risk scenario planning” which may baffle and frustrate many first-time climate reporters. This article is meant to provide context and make CSAs more accessible. It reflects on our experience working with a wide range of clients across different industries, summarizing the key challenges companies face with climate scenario analysis, the use of qualitative versus quantitative analysis, and how climate scenario analysis fits into a company’s existing processes. Our goal is to not only help companies comply with investor or regulatory CSA requirements, but to add value to their business planning by helping companies understand and anticipate their risk exposure and identify a range of strategic options that you may not be aware of.
How did we get here?
1970s-1980s: Climate scenario analysis began as a forward-looking planning tool used by Shell and then other energy companies to explore oil price volatility and long-term energy trends.
1990s: Climate scientists and economists developed integrated assessment models (IAMs) to link emissions, climate outcomes, and policy responses, forming the basis for IPCC scenarios commonly used in CSAs.
2000s: Financial institutions began recognizing climate change as a systemic risk. Key industries—including energy, finance, agriculture, and manufacturing—began adopting scenario planning to assess exposure to both transition and physical climate risks. Likewise, utilities and municipalities began using climate impact studies to model long-term physical risks like heatwaves, droughts, and infrastructure vulnerability, integrating findings into infrastructure resilience, urban planning and investment planning.
2015 Paris Agreement: The G20’s Financial Stability Board created the Task Force on Climate-related Financial Disclosures (TCFD) which formally recommended climate scenario analysis as part of corporate risk disclosure.
2019: Central banks like the Bank of England and the NGFS began climate stress tests for financial institutions, accelerating adoption.
2022–Present: Climate scenario analysis became a regulatory requirement in major jurisdictions under frameworks like California’s SB 219, the EU’s CSRD, the UK’s TCFD-aligned rules, Canada’s OSFI guidance, and Australia’s IFRS S2-based standards.
Key Challenges for Companies
Across the industries and clients GSI serves, there are challenges that we must overcome both in terms of building trust and capacity with our clients in terms of how they rely on and use the analysis, and that we disclose for liability purposes.
Client data gaps and quality: One of the biggest challenges is the scarcity and/or inconsistency of data. We find limitations in emissions and asset data (especially for supply chains and smaller counterparties) common, as well as gaps in company–specific loss data. Regulators (e.g. NGFS, FSB) report that data deficiencies can understate climate risk and make results unreliable. To overcome these gaps, we often piece together information from public sources or third-party providers, but this increases uncertainty.
Methodological complexity: Climate scenario analysis spans diverse disciplines (climate science, economics, finance), making integration difficult. The Central Bank NGFS guide notes “climate scenarios provide a flexible ‘what-if’ framework,” and linking physical climate outcomes with macroeconomic and financial impacts remains a work in progress. In practice, we may use multiple model types and simplifying assumptions to make the analysis relevant and feasible, but this again increases uncertainty.
Uncertain scenarios: We are in uncharted territory, and the future trajectory of climate change and policy is highly uncertain. We must select a range of plausible scenarios (e.g. below-2°C “orderly transition” versus high-warming “hot house” pathways), but there is no single best set of scenarios. Each scenario’s assumptions (carbon prices, technology uptake, physical effects, etc.) have high uncertainty. In practice, we recommend companies run as many scenarios as makes sense; this judgment is inherently subjective unless determined by reporting jurisdiction.
Internal capabilities and governance: Many companies we work with are still building their climate expertise, where the CSA is led by mid-level managers or a sustainability team with limited access across key functional roles or authority. Because key business units (finance, operations, procurement, strategy) may have little input, the results may be too technical or miss opportunities to make an impact across the company. Without strong governance and board oversight, scenario planning risks remaining an academic or compliance exercise.
Regulatory alignment and “alphabet soup”: Companies must navigate multiple, sometimes overlapping regulations and frameworks. Besides California’s SB 219 (TCFD or IFRS), they may face the EU’s CSRD, UK’s TCFD-aligned mandates, Canada’s OSFI Guideline B-15, Australia’s upcoming IFRS S2-based disclosures, and others. Each has its own nuances (different scope definitions, disclosure formats, scenario specifications). Aligning efforts to satisfy all requirements (e.g. scenario outputs that meet both CSRD/ESRS and IFRS S2, which may differ slightly) adds to the challenge, risking duplication and compliance burden (see our previous article on the topic/link here).
Even as data and models improve, there will always be challenges that we have to disclose.
Integrating Climate Scenarios with Existing Processes
Rather than starting from scratch, we look for ways we can build on established processes:
Risk Management: Scenario analysis should be integrated into the organization’s risk management. If a company has a formalized enterprise risk management framework (ERM), this means treating climate as a key risk category by involving risk officers and audit/ risk committees in overseeing scenario work and ensuring outputs feed into existing risk registers. When ERM teams update risk registers or perform annual risk assessments, they can overlay climate drivers (e.g. carbon-pricing or supply-chain disruptions). (See our previous article on the topic). Similarly, a defined risk appetite makes determining what level of financial, operational, or reputational impact from climate change a company is willing to tolerate. For example, a risk-averse company might stress-test severe scenarios (like a rapid transition to a low-carbon economy) more rigorously than one with a higher risk tolerance.
However, many companies don’t have a formalized ERM, so we can review existing financial disclosures (like a 10K) and engage with key personnel to develop a risk appetite to set the tone for how bold or cautious the company is willing to be when planning for future climate-related events. Even an informal understanding of a company’s risk appetite is useful for a CSA because it influences which climate scenarios are considered. For example, a company with a high appetite for transition risk might embrace scenarios that include rapid policy shifts or technological disruptions. Meanwhile, a company more concerned with physical risks might model chronic climate hazards like rising sea levels or extreme weather.
Operational Risk and Business Continuity: Many companies have robust operational risk management in place already, where climate scenarios are used to further inform risk management and business continuity planning. For example, manufacturing firms can use extreme-weather projections to assess supply-chain risk. Existing operational risk assessments (e.g. scenario plans for factory outages or natural disasters) can be expanded to include climate variables. Firms with physical assets can incorporate long-range climate projections (temperature rise, sea-level) into site plans.
Capital and Strategy Planning: Scenario outputs must be tied back to capital budgeting and business strategy. If a climate scenario implies reduced demand for fossil fuels or stranded assets, investment plans and transition strategies need adjustment. Thus, finance and strategy teams can fold climate-driven revenue/cost projections into their multi-year plans. For example, if an electric utilities company uses a below-2°C scenario, it might factor a faster decline in coal plant revenues into its capital allocation decisions. Integrating climate scenarios into traditional budgeting cycles and strategy reviews ensures the analysis informs real decisions rather than being an isolated report.
By reusing existing frameworks—ERM, stress tests, budget models—companies can make climate scenario planning a practical extension of what they already do. By integrating scenario analysis into strategic planning or risk management, companies can evaluate their strategy. Importantly, this mindset avoids treating CSAs as a compliance, one-off exercise, embedding it into your governance and decision-making.
Modeling Approaches: Qualitative vs. Quantitative
Climate scenario analysis ranges from high-level qualitative narratives to detailed quantitative modeling. TCFD recommends companies start with a qualitative analysis, and we generally agree, and IFRS S2 acknowledges that scenario inputs can be qualitative or quantitative. A smaller company with limited capacity or data might rely primarily on narrative scenarios for several years.
Qualitative narratives: Many companies begin by outlining storylines (e.g. “Net-Zero 2050,” “Delayed Transition,” “Hothouse World”) that describe plausible futures for policy, technology and market conditions. These narratives may note key drivers (carbon price path, energy mix, regulatory changes) without assigning exact values. Such qualitative scenarios help identify broad risk themes and strategic implications. For example, a company might describe a 1.5°C scenario where strict carbon policies accelerate electrification, and another 3°C scenario where action is delayed.
Quantitative modeling: More mature analyses incorporate numeric projections of climate and economic variables. Core tools include:
- Integrated Assessment Models (IAMs): These coupled climate-economy models (e.g. AIM, MERGE, REMIND) generate pathways for greenhouse-gas emissions, temperature rise, energy use and GDP under various assumptions. IAMs underpin major scenario sets (the IPCC’s RCP/SSP scenarios). For example, the widely used NGFS scenarios draw primarily on existing mitigation and adaptation pathways assessed by the IPCC. IAM outputs can be downscaled to industries or regions, offering consistency with global science.
- Macroeconomic models (CGE, econometric): Models like Computable General Equilibrium (CGE) systems or macro-econometric frameworks (e.g. OECD ENV models, DNB’s use of NiGEM) translate climate policy shocks into economic effects. For example, a CGE model can show how a carbon tax affects GDP, sector output and trade balances. Quantitative methods often combine a bespoke IAM and CGE. For example, a company can use this combination to gauge macro impacts on product demand and material costs.
- Sector-specific tools: In addition to economy-wide models, many industries use tailored scenarios. Energy companies often rely on IEA or national energy agency scenarios for power and oil markets. Auto manufacturers may use transport decarbonization forecasts. Agricultural firms use climate impact models (e.g. crop yield simulation under temperature/precipitation changes). For physical risk, specialized models from climate science and insurance (e.g. downscaled GCM projections, CAT models for storms and floods) help quantify asset-level impacts. Such tools can convert a scenario (e.g. +3°C by 2100) into sector KPIs (e.g. % of crops failing, % of coastline inundated).
Hybrid approaches: Most of our corporate scenarios analyses blend narrative and numbers. A firm might start with a published scenario (“2°C gradual transition” or “Delayed action leading to 4°C warming”) and then apply internal financial assumptions. For example, the company’s finance team could take the NGFS 1.5°C pathway for carbon prices and feed it into the enterprise resource planning system to project energy costs and profit margins.
It is critical that we meet our clients where they are in terms of readiness to complete the analysis and organizational capacity to leverage the analysis. Regardless of approach, users of the analysis (including regulatory mandates) require we meticulously document the methodology and under assumptions.
CSA in Action
When done well, a CSA is more than a compliance exercise and can inform decision-making. John Deere, a global leader in agricultural machinery and technology, is exposed to climate-related risks in multiple ways—through its supply chains, customer base (farmers), and resource availability (like water and soil health). Recognizing this, John Deere has started aligning its strategy with climate resilience, using tools like scenario analysis in accordance with TCFD. In its Sustainability Reports and CDP Climate Change responses, John Deere discusses using their existing enterprise risk management criteria in their climate scenario planning to evaluate future risks and opportunities under various temperature rise scenarios (low emissions/RCP 2.6 and high emissions/RCP 8.5). John Deere evaluates how different climate futures could affect agricultural productivity (e.g., how droughts or floods might shift crop production areas), customer behavior (e.g., increased demand for precision agriculture solutions that reduce water and fuel use), supply chain resilience (e.g., disruptions from extreme weather events) and regulatory shifts (e.g., carbon pricing or emissions standards). Their CSA reveals a balanced picture of future climate-related challenges and opportunities:
Physical risks under high emissions futures:
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- Extreme weather increases frequency of heatwaves, heavy rainfall and fire that threatens crop yields, raising insurance costs and reducing farmers purchasing power – impacting sales
- Water stress and droughts raise irrigation costs – impacting demand for equipment
Transitional risks under low emissions futures:
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- Disruptive technologies that impact Deere’s market share if they lag.
- Carbon pricing under that impact operating costs and drive customer demand.
The CSA results have companywide implications to mitigate risk and capitalize on revenue generating opportunities. Their response includes anticipating supply chain disruptions and preparing alternative logistics and sourcing strategies, including scaling renewable energy options by 20%, and investing roughly 2.2B in green innovation such as precision agriculture to reduce inputs and increase yields, electric and hybrid machinery to lower emissions, and digital platforms that help farmers adapt to weather variability and long-term climate trends.
Summary
In summary, climate risk scenario planning spans a spectrum. At one end are qualitative “what-if” narratives; at the other end are fully quantitative simulations that output numeric changes in revenues, costs or asset values. Major climate scenarios and models (RCP/SSP pathways, IEA scenarios, NGFS scenarios) serve as common starting points. We then work with companies to tailor these using the models and data relevant to their industry and geography. Firms with higher climate exposure and capability are expected to use more sophisticated (quantitative) approaches. As internal expertise and the climate field grows, businesses are moving from narrative sketches toward more data-driven scenario projections, while still acknowledging inherent uncertainties.
At GSI, we have worked across this spectrum with a wide range of clients. We have a deep bench of climate modelers and experts. If you have questions or need support, please get in touch with us.
