Disclosure focus
This disclosure asks an organisation to explain the method it used for scenario analysis and the main inputs and assumptions behind it. In practice, that means setting out how the scenarios were built, what time horizons were considered, what data or parameters were used, and any key judgement calls that shaped the analysis. The aim is to make clear how the organisation tested climate-related risks and opportunities under different possible futures.
The practical focus is on transparency and consistency: a reader should be able to understand what was included, what was left out, and how robust the analysis is. Organisations should be clear about the scope of coverage across the business, such as whether the analysis applies to the whole group, selected operations, or only certain assets or sites, and whether the same approach was used across those areas or tailored in different ways.
This LRA educational guidance supports disclosure preparation. For the exact requirements, always refer to the official IFRS source.
Before you start
A quick mental checklist before you prepare this disclosure — tick each as you settle it.
Preparation
Key datapoints to prepare
＋ Show s2-22-b sub-elements (LRA working checklist)
Set out the main policy, economic and technology assumptions used in the analysis.
Explain how a Paris-aligned scenario was applied.
Show whether the assessment covers physical risks, transition risks, or both.
State why these scenarios or assumptions are relevant to the business.
Identify the reporting period used for the analysis.
Name the scenario set used and where it came from.
Specify which parts of the organisation or operations were included.
Set out the time periods considered in the assessment.
How to prepare it
1Set the boundary for the analysis first: decide which operations, sites, activities and time periods are in scope, and make sure the period you analyse is stated clearly.
2Define the content of the assessment in business terms: identify the policy, macroeconomic and technology assumptions you will use, the climate scenarios you will rely on, and the time horizons you are applying.
3Gather the support for each input: keep the source material for the scenario set, the origin of the assumptions, and any documents showing how physical and transition risks were covered.
4Prepare the disclosure content itself: write the narrative or compile the figures so they explain why the chosen scenarios and assumptions matter for the entity and how they were used in the analysis.
5Record any limits or changes to the analysis: note what was left out, any changes from prior periods, and the reason each item is relevant to the disclosure.
6Check the draft against the official source before finalising: confirm the scope, assumptions, scenario sources, coverage, rationale and reporting period all match the underlying evidence and the source requirements.
Request the data
Request the scenario analysis pack from Strategy / Risk
Translate the disclosure into an internal business question — then adapt it to your organisation's own language.
What assumptions, scenario set, coverage, time horizons and supporting evidence were used for the latest climate scenario analysis?
Please use your organisation’s own terms first, then map them to the disclosure labels. For example, if you call this work a climate stress test, resilience review or planning case, keep that language in the request and only translate it to the reporting label at the end. This is a training template only; adapt it to your organisation and check the source material before sign-off.
Weak request
Please provide the scenario analysis information for the disclosure, including the method, inputs and assumptions.
Why it fails: This uses reporting jargon that may not match how the team works day to day, and it does not say what evidence is needed, which period is in scope, what parts of the business were covered, or which assumptions and source materials should be returned.
Better request
Please send the latest climate scenario analysis pack for [period], including the scenario cases used, the main policy / market / technology assumptions, the parts of the business covered, whether physical risks, transition risks, or both were assessed, the time horizons used, and the note explaining why these cases were relevant. Include the source file or link, version/date, and the person who prepared and reviewed it. Use your team’s own labels if different; we will map them for reporting.
Industry examples
Draft your disclosure
Notes that turn data into a disclosure
LRA training templates — adapt them to your organisation, and check the official source before sign-off.
Method note
Start by stating which scenarios were used, where they came from, which assumptions were applied, which parts of the business were included, and the time periods covered, so readers can see the basis of the analysis.
Context note
Explain what the scenario work is intended to show for the business, including how the chosen scenarios help assess climate-related exposure across the operations in scope and over the selected horizons.
Fluctuation statement
If the analysis changed from the prior period, note whether the shift came from different scenarios, updated assumptions, a wider or narrower scope, or a change in the time horizons reviewed.
Content index entry
s2-22-b Scenario analysis method, inputs and assumptions — [location / page] / [notes]
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Preparation tools & forms
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Assurance readiness
For each claim, check the evidence
Evidence pack to prepare
Common reporting gaps
The information is presented without a date or as-at point.The scope or boundary of the statement is left undefined.Key terms are used inconsistently across the report.Material changes since the previous period are not disclosed.Assertions are made without supporting detail or a source record.Boilerplate is used that does not actually answer what is asked.
Common gaps
Mistakes to avoid when collecting the data
Wrong owner, wrong language
The request goes to a team that does not hold the underlying model or assumptions, so the reply comes back in framework terms instead of the business terms used by the people who actually ran the analysis.
No clear boundary
The data pull is started without agreeing which sites, entities, or activities are in scope, so different teams send different slices of the business and the set cannot be reconciled.
Period mismatch
One team sends the latest forecast while another sends the period used in the analysis, so the inputs no longer match the reporting window being described.
Mixed counting basis
Headcount, emissions, spend, or asset data are gathered on different bases and then merged, which makes the scenario inputs inconsistent and hard to compare.
Source labels lost
Original file names, version tags, or source notes are stripped out during collection, so nobody can trace a figure back to the document it came from.
Separate groups merged
Physical and transition information, or other distinct populations, are combined into one file even though they need to stay separate for the analysis to make sense.
Missing evidence trail
The team captures the numbers but not the supporting notes, screenshots, or file references, leaving no proof of how each input was assembled.
No sign-off record
Draft inputs are circulated informally and then used without a dated approval trail, so it is unclear who checked the assumptions and when.
Scenario set not pinned down
The collection request does not name which scenario pack and source documents to use, so different contributors pull from different versions and the dataset becomes inconsistent.
Relevance not captured
The team records the inputs but never asks why each assumption matters to the analysis, so later reviewers cannot see the link between the data and the business judgement.
Where judgement is often needed
What to do when the business perimeter changes mid-year
Use the same cut-off point across the analysis, then explain whether bought-in or sold-off activities were included, excluded, or only partly reflected, and why that treatment best matches the period being described.
How to handle different local meanings for the same input
Where country teams use different definitions or source data, pick one basis for the analysis, state the mapping or conversion used, and explain any places where local practice could not be made fully comparable.
Whether small or borderline activities stay in or drop out
Set a clear inclusion rule for operations that sit near the edge of the chosen scope, apply it consistently, and disclose the rule so readers can see why some marginal items were kept or left out.
Which date or period anchors the analysis
Choose one timing basis for the scenario work, use it consistently across the narrative and inputs, and explain if the analysis reflects a point-in-time view, an average, or another period basis.
When to use estimates instead of direct measurements
If actual readings are missing or impractical, use the best available estimate, say where it was used, and explain the main assumptions and any known limits on accuracy.
How far to round figures before they lose meaning
Apply one rounding approach across the disclosure, keep the level of precision consistent with the underlying data, and note any material effect that rounding could have on the results.
How to summarise sensitive location or workforce data
If detailed site or people data cannot be shown without privacy risk, group it into broader bands, explain the aggregation method, and make clear what detail has been withheld.
How to treat scenario sources that do not line up neatly
When external scenario material is mixed or incomplete, identify the source set used, explain any selection or blending choices, and state the assumptions made to bridge gaps.
How to explain the link between the scenario set and the business model
Describe why the chosen scenario set is relevant to the organisation’s operations, and spell out the main policy, market, and technology assumptions that connect the scenario to the business.
How to separate physical and transition coverage
State which parts of the analysis look at weather- or location-driven effects and which parts look at policy, market, or technology change, and explain any areas where the two overlap.
Examples
Illustrative examples
Synthetic, written by LRA — not from a company report, not text from any standard.
Illustrative (synthetic) example — Power generation
We used a Paris-aligned pathway to test our 2025 reporting year, looking across our owned plants and contracted power assets in the UK and EU, with a 2030, 2040 and 2050 view for both weather-related and market-shift risks. The scenario pack came from a mix of public climate pathways and our own operating assumptions, including fuel prices, carbon costs, demand trends, technology uptake and plant availability; we judged this analysis relevant because it covers the parts of the business most exposed to policy change, extreme weather and lower-carbon competition. - The review covered 92% of our revenue base and 95% of our asset value, with 88% of revenue and 90% of asset value assessed under the weather-related pathway, and 84% of revenue and 87% of asset value assessed under the market-shift pathway. - The same scenario set was used for both pathways, and the figures above are internally consistent and rounded.
This synthetic disclosure shows how a company can explain the period reviewed, the parts of the business included, the time windows considered, the scenario sources used, the main assumptions applied, and why the exercise matters to the business.
Illustrative (synthetic) example — Food manufacturing
For our 2024 reporting year, we assessed our own factories, distribution centres and key agricultural sourcing regions in the UK, Spain and Brazil against a Paris-aligned pathway, using 2030 and 2040 as the main short- and medium-term checkpoints and 2050 for the longer view. We drew on a public climate scenario set and our internal planning inputs, including crop yield trends, water stress, energy prices, carbon charges, logistics costs and adoption rates for lower-emission equipment; we considered the exercise relevant because it captures the places and activities most likely to be affected by heat, drought, supply disruption and changing customer demand. - The analysis covered 78% of our direct operations and 81% of our purchased-input spend, with 70% of direct operations and 74% of purchased-input spend tested for weather-related effects, and 66% of direct operations and 69% of purchased-input spend tested for transition effects. - These results are based on one scenario set used across the full review, and all percentages are rounded from internally consistent underlying figures.
This synthetic disclosure illustrates how a company can describe the year reviewed, the business footprint included, the time horizons used, the scenario sources and assumptions, the Paris-aligned framing, and the reason the analysis is useful.
How companies report s2-22-b
Real reports where this topic is disclosed. These are report practice, not exact disclosure templates to copy.
Enel Chile S.A.
Electric Utilities / IPP / Energy Traders · Chile · 2025
Enel Chile S.A.'s 2025 Integrated Annual Report provides some context on its scenario analysis, referencing the Enel Group's 1.5°C consistent scenario methodology (p.187) and discussing energy transition scenarios related to climate risks and opportunities (pp.170, 372). However, the report does not clearly disclose key elements such as the use of Paris-aligned scenarios, reporting period of analysis, relevance rationale, time horizons, or the scope of operations for the scenario analysis. Several datapoints remain unclear, with only partial contextual information rather than explicit disclosures on the scenario set, sources, and physical transition coverage (pp.170, 372).
SITC International Holdings Company Limited
Water Transportation · Hong Kong · 2025
SITC International Holdings Company Limited’s 2025 Environmental, Social and Governance Report provides coverage on the relevance rationale for chosen climate-related scenarios (p.195), the scenario set and sources used in their analysis (p.195), and the time horizons considered in assessing the entity’s prospects (p.188). However, the report does not clearly disclose key policy macro technology assumptions, use of Paris-aligned scenarios, or physical transition coverage. Additionally, the reporting period of analysis (p.107) and the scope of operations (p.190) are mentioned with related context but lack clear, explicit disclosure.
MTR Corporation
Ground Transportation — Railroads · Hong Kong · 2025
MTR Corporation’s Sustainability Report 2025 includes a high-level diagnostic climate scenario study covering key railway and investment operations, indicating some physical transition coverage (p.82). The report discusses climate-related risks and protective measures adequate under mid-21st century extreme weather projections (p.80, p.83). However, the report lacks evidence on key policy macro technology assumptions, Paris-aligned scenario use, reporting period of analysis, scenario sets and sources, relevance rationale, and time horizons, with the scope of operations also unclear.
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Scenarios to work through
A manufacturer has run a climate scenario exercise for its main plants and distribution network. The team used one pathway from a recognised climate model, but the draft note only says the exercise was done and does not explain why that pathway was chosen or what business areas were included.
QWhat should the preparer check before signing off the disclosure?
Reveal model answer →Hide answer ↑The note should explain why the chosen scenario set is relevant to the business, identify the source of the scenarios used, and make clear which parts of the organisation and operations were covered. If the exercise only covered some sites or activities, that limitation should be stated so readers can see the scope of the analysis.
Why this matters · Readers need enough context to judge whether the scenario work is relevant and how far it reaches across the business.
A retailer has modelled both flood disruption and a rapid policy shift on carbon pricing. The draft wording mentions the two scenario types, but it does not say whether the analysis looked at both short and longer time periods, or how the assumptions were set for policy, market and technology change.
QHow should the preparer decide whether the disclosure is complete enough?
Reveal model answer →Hide answer ↑The preparer should check that the time periods used in the analysis are described, and that the main assumptions behind the exercise are clear, including the policy, market and technology views that shaped the scenarios. The disclosure should let a reader understand the time frame and the key drivers behind the modelling, not just the names of the scenarios.
Why this matters · A scenario description is stronger when it shows both the time frame and the assumptions that drive the results.
An energy company has used a Paris-aligned pathway for part of its transition planning and a separate physical-risk case for its coastal assets. The draft report says the scenarios were “aligned with climate goals” and “covered risks”, but it does not say whether the analysis included both transition and physical effects, or why those choices were relevant to the company.
QWhat judgement should the preparer make about the wording and content?
Reveal model answer →Hide answer ↑The preparer should make sure the disclosure states whether the analysis covered transition effects, physical effects, or both, and should explain why those areas were selected as relevant to the business. If a Paris-aligned pathway was used, the note should identify it clearly in plain language and show how it fits the company’s scenario set rather than leaving the reader to infer the link.
Why this matters · The disclosure should show the type of climate risk tested and why that mix matters for the business.
A diversified group has prepared a scenario analysis for the current reporting year, but the draft note mixes together assumptions from last year’s model with new assumptions from this year’s planning cycle. It also leaves out the period the analysis relates to, making it hard to tell which year the results describe.
QWhat should the preparer do before finalising the note?
Reveal model answer →Hide answer ↑The preparer should tie the analysis to the reporting period it relates to and make sure the assumptions described are the ones actually used for that period’s work. If assumptions changed from the prior year, the disclosure should not blur them together; it should present the current-year basis clearly so the reader can follow the analysis.
Why this matters · Scenario disclosures should be anchored to the reporting period and the assumptions used for that period’s analysis.
Framework references
Related framework references
How this disclosure maps across the major reporting frameworks.
Primary
Related & explore
FAQ
Questions this page answers
How do I use the s2-22-b page to draft a climate disclosure from scratch?+−
Start with the plain-language explainer, then work through the step-by-step preparation section, the datapoints to prepare, and the draft-output ideas. The page is designed to help you turn source data into a first draft, not to act as an official source.
What data do I need to collect for s2-22-b before I can write the disclosure?+−
The page points you to policy and technology assumptions, Paris pathway use, hazard and transition coverage, why it matters, the analysis period, scenario set and sources, operational scope, and forecast horizons. Use those as the core inputs for your data request and evidence pack.
How should I set the scope and methodology for s2-22-b in practice?+−
Use the page’s guidance on operational scope, forecast horizons, analysis period, scenario set and sources, and the way Paris pathway use is described. Keep the methodology tied to the specific assumptions and sources you can evidence.
Who should own the s2-22-b disclosure data and evidence pack?+−
The page is written for sustainability/ESG managers, HR or data owners, and assurance reviewers, so ownership should sit with the people who can explain the assumptions, sources, and supporting evidence. The step-by-step preparation section and evidence pack are the best places to align responsibilities.
What should I put in the evidence pack for s2-22-b assurance readiness?+−
The page includes an evidence pack with five items and six assurance claims to verify, each framed around claim, risk, and evidence. Use those to build a file set that shows how the disclosure was prepared and what supports the numbers and narrative.
What are the common mistakes to avoid when preparing s2-22-b?+−
The page lists common reporting gaps and mistakes, so use that section as a pre-submission check. It is especially useful for spotting missing scope, unclear assumptions, or weak support for the narrative and figures.
How do I use the Prep & Assurance workbook for s2-22-b?+−
The Download Centre includes a Prep & Assurance workbook in .xlsx format and a printable Library Card in .pdf. Use the workbook to organise the preparation steps, evidence, and draft output before you finalise the disclosure.
What can I copy from the synthetic example disclosure for s2-22-b?+−
The page includes synthetic illustrative example disclosures, including a quantitative table, to show how the disclosure can be presented. Treat them as format and structure examples only, and make sure any numbers you use are internally consistent and based on your own data.
How do I turn the s2-22-b data into a draft narrative and content index line?+−
Use the draft-output section, which gives visualisation ideas, narrative starters, and a content-index line. That section is there to help you convert prepared data into a readable draft without having to invent the structure yourself.
Can I reuse my s2-22-b data for ESRS E1 climate reporting?+−
The page notes ESRS E1 (Climate Change) as the closest correspondence, so the same underlying data may be reusable across both contexts. It does not say the requirements are identical, so check the other framework separately before relying on the same wording or mapping.
More questions this page can help with
s2-22-b disclosure checklist for sustainability managers2-22-b climate disclosure evidence pack templates2-22-b workbook download how to uses2-22-b common reporting mistakes and gapss2-22-b synthetic example disclosure tables2-22-b scenario set and sources guidances2-22-b operational scope and forecast horizonss2-22-b policy and technology assumptions data requests2-22-b assurance claims claim risk evidences2-22-b draft narrative starters and content index lines2-22-b from company reports exampless2-22-b ESRS E1 data reuse
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