Climate Scenario Analysis for Infrastructure: From NGFS Scenarios to Asset-Level Financial Impact
Climate scenario analysis for infrastructure is the process of modelling how different climate pathways, from orderly net-zero transitions to high-warming futures, affect the financial performance of physical assets over their operational lifetimes. It translates global scenarios from frameworks like NGFS and IPCC into asset-level revenue impacts, CapEx acceleration, and valuation adjustments.
Table of Contents
- Why Infrastructure Investors Cannot Ignore Climate Scenario Analysis
- What is Climate Scenario Analysis?
- Choosing the Right Scenario Framework
- NGFS Scenarios: The Financial Sector Standard
- IPCC SSP-RCP Framework: The Climate Science Standard
- IEA Scenarios: The Energy Transition Standard
- Which Framework Should You Use?
- How to Run Climate Scenario Analysis for Infrastructure: A Five-Step Process
- Step 1: Define Scope and Calibrate Time Horizons
- Step 2: Select and Weight Scenarios
- Step 3: Translate Scenarios to Asset-Level Physical Impacts
- Step 4: Quantify Financial Impact Across Scenarios
- Step 5: Aggregate to Portfolio Level and Stress Test
- From Scenarios to Decisions: Closing the Operationalization Gap
- Communicating Scenario Uncertainty to Investment Committees
- Frequently Asked Questions
The infrastructure investment industry has a scenario analysis problem. Not a shortage of scenarios, but a failure to use them. The NGFS Scenarios Portal offers six detailed climate pathways. The IPCC publishes granular physical projections under multiple Shared Socioeconomic Pathways. The IEA models energy transition trajectories out to 2050 and beyond. Yet in practice, most infrastructure funds treat scenario analysis as a reporting exercise rather than a decision-making tool.
A senior infrastructure finance professional with over three decades in the energy sector described the prevailing attitude: “It’s like selling a home where you know there may be a little black mold. Legally you’re bound to say it. But it’s like, well, it’s not that big. Maybe we won’t say anything right now. Anything that devalues an asset isn’t becoming standard practice. It’ll take a catastrophic event before people say: these guys were right, we now have to put this on the map.”
This guide addresses the methodology gap. Not what climate scenario analysis is in theory, but how to construct, calibrate, and apply it to infrastructure portfolios so that the outputs actually change investment decisions.
Why Infrastructure Investors Cannot Ignore Climate Scenario Analysis
Three forces are converging to make climate scenario analysis unavoidable for infrastructure funds.
Regulatory requirements are hardening. IFRS S2 raises the expectation that climate disclosures be financially connected and decision-useful, including explaining how climate-related risks and opportunities affect financial position, performance and cash flows, and how they are considered in relevant assumptions and analysis where material. In practice, for infrastructure, this often means a stronger linkage to impairment testing, provisions and valuation-related assumptions. A standalone sustainability report that sits alongside the financials, disconnected from them, no longer satisfies the standard. For a practical guide to meeting these requirements, see this overview of TCFD reporting for infrastructure.
P50 forecasts are failing. A portfolio manager at a major European infrastructure fund recently described calling their finance team because wind yields in 2025 came in 10% below expectations. The question for the board: “Is this structural change or a black swan?” Without scenario analysis that accounts for forward-looking climate projections, there is no way to answer that question. The shortfall could be temporary weather variation. Or it could be the beginning of a systematic decline in wind resource that will persist for the remaining life of the asset.
Insurance markets are repricing ahead of investors. Insurers are already running their own climate scenario models and adjusting premiums accordingly. Infrastructure funds that have not run equivalent analysis face a growing information asymmetry: the insurer knows more about the asset’s climate exposure than the asset owner does.
What is Climate Scenario Analysis?
Climate scenario analysis is a structured method for exploring how different plausible climate futures affect the financial performance of assets and portfolios. Scenarios are not predictions. They are internally consistent narratives about how climate, policy, technology, and markets might evolve together over defined time horizons.
For infrastructure, scenario analysis serves a distinct purpose compared to corporate applications. Infrastructure assets are fixed in location, built for decades of operation, and exposed to physical climate hazards that compound over time. A corporate with offices in 30 countries can relocate operations. A wind farm in the North Sea cannot. This means infrastructure scenarios must account for hyperlocal physical risk projections, engineering-specific damage thresholds, and asset lifespans that extend well beyond typical corporate planning horizons.
Climate scenarios split into two categories: physical risk scenarios (how changing weather patterns affect asset performance and integrity) and transition risk scenarios (how policy, technology, and market shifts affect asset economics). For infrastructure, both matter, and they often move in opposite directions. A world that fails to decarbonise faces lower transition risk but escalating physical damage. A world that transitions aggressively faces policy and market disruption but slower physical deterioration. For a deeper analysis of this dynamic, see physical climate risk vs transition risk.
Choosing the Right Scenario Framework
Three major scenario frameworks dominate climate risk analysis for financial institutions. Each serves a different purpose, and infrastructure investors often need elements from more than one.
NGFS Scenarios: The Financial Sector Standard
The Network for Greening the Financial System publishes six scenario pathways organised around two dimensions: the ambition of climate policy and the orderliness of the transition. The three broad categories are Orderly (early, gradual policy action), Disorderly (late, abrupt policy action), and Hot House World (insufficient policy action, high physical risk).
All NGFS scenarios are aligned with SSP2, the “Middle of the Road” socioeconomic pathway. The NGFS 2024/Phase V long-term scenario release introduced a new damage function that produces more substantial physical impacts and added the first vintage of short-term scenarios designed to capture near-term economic shocks. The NGFS Phase V technical documentation details the updated methodology.
NGFS scenarios are the default choice for regulatory compliance, LP reporting, and portfolio-level stress testing. Their limitation for infrastructure is resolution: they operate at a macroeconomic level and do not directly model what happens to a specific solar farm or transmission line.
IPCC SSP-RCP Framework: The Climate Science Standard
The IPCC’s Shared Socioeconomic Pathways (SSPs) paired with Representative Concentration Pathways (RCPs) provide the most granular physical climate projections available. SSP1-2.6 represents a sustainability-focused pathway with low emissions. SSP5-8.5 represents fossil-fuelled development with high emissions. Between them sit SSP2-4.5 (middle of the road) and SSP3-7.0 (regional rivalry).
For infrastructure, the SSP-RCP framework offers higher physical resolution than NGFS. Regional climate models downscaled from CMIP6 ensembles can project temperature, precipitation, wind speed, and extreme event frequency at spatial resolutions relevant to individual assets. This makes SSP-RCP the preferred framework for asset-level physical risk analysis and engineering threshold assessment. Munich Re’s comparison of IPCC and NGFS frameworks provides a useful technical overview of where they diverge.
IEA Scenarios: The Energy Transition Standard
The International Energy Agency publishes core scenarios used widely in energy system analysis, including Net Zero Emissions by 2050 (NZE), the Announced Pledges Scenario (APS), and the Stated Policies Scenario (STEPS). These are the most detailed scenarios for energy system transformation, covering generation mix, grid investment, demand patterns, and fuel prices.
For infrastructure investors focused on energy generation assets and grid infrastructure, IEA scenarios fill a gap that NGFS and IPCC do not: they model how the energy transition changes the demand for and economics of specific infrastructure types. A wind portfolio faces different transition dynamics under NZE (strong policy support, rising demand) versus STEPS (slower buildout, uncertain subsidy regimes).
Which Framework Should You Use?
The answer depends on what question you are trying to answer.
| Question | Best Framework |
|---|---|
| How does climate policy uncertainty affect our portfolio value? | NGFS |
| What physical hazards will this specific asset face in 2040? | IPCC SSP-RCP |
| How will energy transition reshape demand for our infrastructure type? | IEA |
| What should we disclose under IFRS S2 and CSRD? | NGFS as a common macro framing tool, with IPCC/CMIP-based physical risk detail at asset level |
| How do we adjust the financial model for a specific acquisition? | IPCC for physical, IEA for transition |
Most infrastructure funds will need a combination. NGFS for the macro frame and regulatory compliance. IPCC SSP-RCP for asset-level physical risk. IEA for energy transition assumptions. The discipline is in making these frameworks talk to each other within a single financial model.
How to Run Climate Scenario Analysis for Infrastructure: A Five-Step Process
Step 1: Define Scope and Calibrate Time Horizons
Start with the investment thesis, not the climate model. The most common mistake in infrastructure climate scenario analysis is treating it as a standalone exercise divorced from the fund’s actual decision cycle.
Scope should be defined by financial materiality. Which assets carry the highest value concentration? Which geographies face the most pronounced climate shifts? Which asset types have the narrowest engineering tolerances? These questions determine where detailed scenario analysis creates the most value and where a screening-level assessment is sufficient.
Time horizons must map to actual investment decision points, not generic categories. An energy trader at a European utility put it bluntly: “2050 is not super useful, just saying, but the next five years is very relevant.” For infrastructure funds, the practical calibration is:
- 1 to 5 years: Current hold period and operational budget cycle. What climate shifts affect near-term cash flows, maintenance costs, and availability rates?
- 5 to 15 years: Refinancing events, regulatory review cycles, and exit windows. How does a changing climate affect the asset’s value at these decision points?
- 15 to 40+ years: Full concession or asset life. What structural shifts in climate patterns could alter the fundamental viability of the asset?
The first horizon is where scenarios have the most immediate financial impact. The third is where physical risk diverges most dramatically between pathways. The second, often overlooked, is where scenario analysis most directly informs hold-versus-divest decisions.
Step 2: Select and Weight Scenarios
The TCFD Scenario Analysis Guidance remains a practical reference point and recommends at least two scenarios: one Paris-aligned pathway and one higher-warming pathway. For infrastructure, two scenarios are a minimum but not enough for sound decision-making, particularly where analysis is expected to support financially connected, decision-useful outputs under IFRS S2-style reporting.
A practical scenario set for infrastructure investors includes four pathways:
- Orderly transition (NGFS Net Zero 2050 / SSP1-2.6): Early, gradual policy action. Moderate transition risk, lowest physical risk trajectory. The optimistic baseline.
- Disorderly transition (NGFS Delayed Transition / SSP2-4.5): Late, abrupt policy action. High transition risk from sudden regulatory and market shifts. Moderate physical risk.
- Current policies (NGFS Current Policies / SSP3-7.0): No additional climate action beyond existing commitments. Low transition risk, escalating physical risk. The “business as usual” pathway.
- High physical risk (NGFS Hot House World / SSP5-8.5): Failed transition with severe physical consequences. Minimal transition risk but the most extreme physical damage trajectory.
Should you assign probabilities to these scenarios? The argument against is that scenarios are exploratory tools, not forecasts. The argument for is that investment committees need some basis for weighting outcomes when adjusting financial models. A pragmatic middle ground: present scenario results as unweighted ranges for strategic discussions, but use probability-weighted expected values when adjusting DCF models and bid pricing. Most infrastructure investors implicitly weight Current Policies highest, which means their financial models already embed a climate assumption, just not an explicit one.
Step 3: Translate Scenarios to Asset-Level Physical Impacts
This is where most climate scenario analysis breaks down for infrastructure. Global temperature pathways do not tell you what happens to a specific solar farm in Andalusia or a wind portfolio in the Baltic. The translation from global scenario to local, asset-level impact requires three layers of analysis.
Layer 1: Downscale global projections to local climate. CMIP6 ensemble models provide global and regional climate projections under each SSP-RCP pathway. Regional climate models (such as CORDEX) and statistical downscaling techniques translate these into local projections at resolutions relevant to individual assets. The difference matters: two solar farms 30 kilometres apart can face materially different flood exposure depending on elevation and drainage. For more on why resolution matters, see why static climate heatmaps are mispricing infrastructure assets.
Layer 2: Map projections against engineering thresholds. Climate projections become financially meaningful only when they cross the operating tolerances of specific equipment. Solar inverters begin thermal derating above 45 degrees Celsius, reducing output significantly at extreme temperatures. Wind turbines have cut-out speeds (typically around 25 metres per second) above which they shut down entirely. Transmission lines experience thermal sag in prolonged heat, reducing capacity and increasing clearance violations. The question is not “how much warmer will it get?” but “how many additional hours per year will this inverter operate in derating conditions under each scenario?” For a detailed explanation of how physics-based models handle this translation, see climate risk modelling for infrastructure.
Layer 3: Account for compounding degradation. Infrastructure investors consistently report that standard yield degradation assumptions do not match observed performance. An infrastructure investor with over 20 years of experience described the disconnect: “There’s the standard applied across, 4% or whatever percent yield degradation that’s usually applied kind of blanket. That’s not what we’re seeing.” The actual underperformance is more nuanced: equipment degrading faster under heat stress, inverters failing earlier than warranty curves predict, trackers losing accuracy in ways that standard models do not capture. Climate scenario analysis must layer forward-looking resource changes on top of these equipment-specific degradation curves, not treat them as independent variables.
One infrastructure finance professional captured the core problem: boards are asking “Why are our wind yields not hitting our P50s? Why are our solar yields not hitting our P50s?” and the teams responsible cannot explain it. The answer, in many cases, is climate resource degradation layered on top of standard material degradation, a compounding effect that backward-looking yield risk analysis does not capture.
Step 4: Quantify Financial Impact Across Scenarios
Physical impacts become decision-relevant only when expressed in financial terms. The goal of this step is to produce a valuation spread: what the same asset or portfolio is worth under each scenario pathway.
For each scenario, the financial translation should cover five impact channels. Revenue loss from reduced generation or availability. CapEx acceleration from earlier-than-planned equipment replacement or hardening investments. OpEx drift from increased maintenance frequency and rising cooling costs. Insurance repricing as carriers adjust premiums to reflect forward-looking risk. And exit valuation adjustment as buyers, increasingly running their own climate analysis, factor physical risk into bid pricing.
The mechanics of integrating scenario outputs into existing financial models follow a direct path. For each asset, the scenario-adjusted yield projection (from Step 3) feeds into the revenue line of the DCF model. The scenario-adjusted maintenance and replacement schedule feeds into CapEx and OpEx. The scenario-adjusted risk profile feeds into the discount rate or, preferably, into explicit cash flow adjustments rather than blanket discount rate increases that obscure the source of risk.
The output should be a set of scenario-conditioned IRRs: what the project returns under each pathway. The spread between the best-case and worst-case scenario IRR is itself a useful metric. A narrow spread suggests the investment holds up across climate futures. A wide spread signals that the investment thesis depends heavily on which climate pathway materialises. For a deeper treatment of the financial transmission mechanisms, see how climate risk affects infrastructure valuations.
Step 5: Aggregate to Portfolio Level and Stress Test
Individual asset scenarios must roll up to portfolio-level outcomes. This aggregation step reveals risks that asset-level analysis alone would miss: geographic concentration, correlated hazard exposure, and portfolio-wide sensitivity to specific scenario variables.
A portfolio with wind assets concentrated in Northern Europe and solar assets concentrated in Southern Europe might appear diversified. Under a high-warming scenario, both regions face material impacts, just different ones: declining wind resource in the north, escalating heat stress and inverter derating in the south. The correlation between these impacts under a shared climate pathway means the portfolio’s diversification benefit is lower than it appears.
Portfolio stress testing should answer three questions for each scenario: What is the portfolio-level IRR under this pathway? Which assets contribute most to downside risk? And what concentration thresholds are breached? The stress test results form the basis for strategic portfolio decisions: which assets to harden, which to divest, and where new acquisitions should be directed to improve portfolio resilience.
From Scenarios to Decisions: Closing the Operationalization Gap
The hardest part of climate scenario analysis is not running the models. It is embedding the results into the processes where investment decisions actually get made.
The accountability gap runs deep. When operators are asked about climate-adjusted modelling, they point to investors. When originators are asked, they say lenders control the assumptions. Lenders say insurers and regulators set the risk framework. Insurers say they are modelling the risk but the rest of the chain is not demanding the data. Each link in the value chain defers responsibility to the next.
Breaking this cycle requires embedding scenario outputs at three specific decision points.
Pre-deal: Scenario-adjusted bid pricing. Climate scenario analysis should inform the price an investor is willing to pay. If the spread between the orderly-transition IRR and the current-policies IRR is 300 basis points, that range should be reflected in the bid, either as a price adjustment or as a contingency built into the financial model. Presenting scenario-conditioned valuations to the investment committee forces the fund to make its climate assumptions explicit.
Hold period: Dynamic scenario monitoring. Scenarios are not static. As new climate data arrives, as actual weather patterns diverge from or converge with specific pathways, the active scenario set should be updated. Practical triggers for reassessment include: actual yields deviating from projected yields by more than a defined threshold, insurance premium increases exceeding expectations, or new regulatory requirements that shift the transition risk profile.
Exit: Scenario-disclosed valuations. Buyers are increasingly running their own climate analysis. A seller who can present a transparent, scenario-conditioned valuation, with explicit assumptions and methodology, is better positioned than one offering a single-point DCF with no climate adjustment. The transparency itself becomes a competitive advantage in the transaction.
Reverse scenario testing offers an additional layer of rigour. Rather than asking “what happens under each scenario?”, ask “what would have to change in climate conditions to make this investment thesis fail?” If the answer is a shift that falls within the range of plausible scenarios, the thesis has a climate vulnerability that needs to be addressed or priced.
Communicating Scenario Uncertainty to Investment Committees
Presenting climate scenario analysis to an investment committee requires a different approach than presenting it in a sustainability report. Investment committees want to understand three things: what does this mean for returns, how confident are we, and what should we do about it.
Lead with the valuation spread, not the climate science. Present the IRR range across scenarios first. If an asset returns 9.2% under orderly transition, 8.1% under current policies, and 6.4% under high physical risk, the committee can immediately see the stakes. The climate detail supports this headline rather than leading the conversation.
Use three charts. The first shows the base case: the scenario the fund considers most likely, with the scenario-adjusted financial projection. The second shows the upside: what happens if the transition proceeds more favourably than expected. The third shows the tail risk: the downside scenario with quantified financial impact. Three charts are enough to frame a decision. Thirty slides of hazard maps are not.
Frame scenario analysis as decision support, not prediction. The most effective framing is: “We don’t know which pathway the world follows. But we know what our portfolio is worth under each pathway, and we know which actions improve returns regardless of which pathway materialises.” This positions scenario analysis as a tool for identifying no-regret investments, actions that improve risk-adjusted returns under any plausible climate future, and scenario-dependent bets that require explicit risk appetite decisions.
Common LP questions and how to answer them:
- “What scenario do you think is most likely?” We use probability-weighted ranges for financial modelling, but we present all scenarios to the committee so that strategic decisions are not anchored to a single pathway.
- “Why should we trust these models?” We use ensemble climate projections from CMIP6, which represent the scientific consensus. The financial translation uses asset-specific engineering data and observed performance, not generic assumptions.
- “What are you doing about the downside?” We identify which adaptation investments deliver positive risk-adjusted returns under all scenarios (no-regret actions) and prioritise those. Scenario-dependent investments go through explicit risk committee approval.
Frequently Asked Questions
What is the difference between SSP and RCP scenarios in climate risk assessment?
RCPs (Representative Concentration Pathways) describe greenhouse gas concentration trajectories. SSPs (Shared Socioeconomic Pathways) describe the socioeconomic conditions, population growth, governance, and technology development, that produce those concentration levels. In current climate scenario practice, SSP narratives are combined with forcing levels, creating labels such as SSP1-2.6 and SSP5-8.5; the forcing levels (e.g., 2.6, 4.5, 8.5) are directly comparable to the radiative forcing logic used in the earlier RCP framework. For infrastructure investors, the pairing matters because SSPs influence not just the climate projections but the economic context in which assets operate, including energy demand, policy environment, and technology costs.
How many scenarios should an infrastructure fund run?
At minimum, two: one Paris-aligned pathway (1.5 to 2 degrees Celsius warming) and one higher-warming pathway (3 degrees Celsius or above). For thorough decision-making, four scenarios covering orderly transition, disorderly transition, current policies, and high physical risk provide a more complete picture. Running additional sub-scenarios adds diminishing value unless the fund has specific exposure to a narrow set of climate variables that warrant deeper sensitivity analysis.
How often should infrastructure investors update their climate scenario analysis?
Annual updates aligned with reporting cycles are the baseline. Beyond that, event-driven reassessment should be triggered by material changes: significant deviation of actual yields from projected yields, regulatory shifts that alter the transition risk profile, new IPCC or NGFS scenario vintages (the NGFS plans its next update for end of 2026), or insurance repricing events that signal a market reassessment of physical risk.
What time horizons should infrastructure funds use for climate scenario analysis?
Time horizons should align with the fund’s actual decision cycle, not generic categories. For most infrastructure funds, this means: 1 to 5 years (operational: near-term cash flow and maintenance planning), 5 to 15 years (strategic: refinancing, regulatory review, and exit windows), and 15 to 40+ years (structural: full asset life or concession period). The first two horizons have the most direct financial impact. The third is important for understanding the long-term trajectory but should not dominate decision-making for funds with shorter hold periods.
Can climate scenario analysis be automated with software tools?
Partially. The physical climate projection layer (downscaling, hazard modelling) is well suited to automation, and several platforms handle this step at scale. The financial translation layer, converting physical impacts into revenue, CapEx, and valuation adjustments, requires asset-specific engineering data and financial model integration that varies across portfolios. The strategic interpretation layer, deciding what to do with the results, remains a human judgement call. For a comparison of platforms that support different stages of the process, see best climate risk software for infrastructure investors.
What changed in the NGFS Phase V damage functions and why does it matter?
The NGFS Phase V scenarios, released in November 2024, introduced a new damage function that produces estimated global losses from chronic physical risk two to four times higher than previous versions. The new function extends beyond mean temperature increases to capture the effects of daily temperature variability, precipitation patterns, and extreme weather events. By 2050, loss projections under the Current Policies scenario increased from roughly 5% to 15% of GDP, and even the Net Zero 2050 pathway shows 2% to 7% losses. For infrastructure investors, this means that scenario analysis run on Phase IV assumptions materially understates physical risk. However, an important caveat: the academic paper underpinning Phase V’s physical risk estimates (Kotz et al., 2024) was retracted from Nature following post-publication review. The NGFS has acknowledged this and advised users to interpret Phase V physical risk results with caution. The next scenario vintage, expected in 2026, will likely incorporate a revised damage function. Infrastructure funds should treat Phase V physical risk estimates as directionally correct (higher than previously modelled) while monitoring updates to the underlying methodology.
How do you run reverse climate scenario testing for infrastructure assets?
Reverse scenario testing flips the standard question. Instead of asking “what happens to this asset under a 3-degree pathway?”, you ask “what climate conditions would cause this investment thesis to fail?” The methodology starts by defining failure thresholds: the point at which IRR drops below hurdle rate, debt service coverage ratios breach covenant levels, or insurance becomes commercially unavailable. Then work backward to identify which combination of climate variables (temperature increase, wind speed reduction, flood frequency) would trigger those thresholds. For a wind portfolio, the question might be: “At what sustained decline in average wind speed does the project IRR drop below 6%?” If the answer falls within the range of plausible scenarios (say, a 5% decline that SSP3-7.0 projects for the asset’s region by 2040), the investment has a climate vulnerability that needs to be priced or mitigated. Reverse stress testing is particularly valuable for infrastructure because it surfaces threshold effects that forward scenario analysis can miss, especially where damage functions are non-linear and small changes in climate variables produce outsized financial impacts.
How are insurers using climate scenarios to reprice infrastructure coverage?
Insurers are ahead of most infrastructure investors in applying climate scenario analysis to pricing decisions. Reinsurers raised rates by approximately 37% in 2023 partly to account for forward-looking climate risk, and D&O insurers now routinely examine how climate and environmental risks are disclosed during underwriting conversations. The repricing is most pronounced for what insurers call “secondary perils”: inland flooding, convective storms, and heat-driven wildfires that occur more frequently and often outside traditional high-risk zones. For infrastructure assets specifically, ageing facilities that lack flood elevation improvements, fire-resistant materials, or updated electrical redundancy face higher deductibles and coverage exclusions. The practical implication for investors: if your insurer is running climate scenarios and adjusting premiums accordingly, but your fund is not running equivalent analysis, you face an information asymmetry. The insurer’s scenario-informed pricing is a signal. When premiums rise faster than your internal risk models predict, it likely reflects climate risk that your financial models have not yet captured.
How do CMIP6 ensemble models get downscaled to asset-level resolution?
CMIP6 (Coupled Model Intercomparison Project Phase 6) global climate models typically operate at spatial resolutions of 100 to 250 kilometres, far too coarse for asset-level infrastructure risk analysis. Downscaling bridges this gap through two approaches. Statistical downscaling uses observed relationships between large-scale climate patterns and local conditions to translate coarse projections to finer resolution, often reaching 10 to 25 kilometre grids. Dynamical downscaling runs regional climate models (such as CORDEX) nested within global models to produce physically consistent high-resolution projections. For infrastructure, the choice matters. Statistical downscaling is computationally efficient and suitable for screening large portfolios. Dynamical downscaling better captures local topographic effects and extreme event characteristics, making it preferable for detailed analysis of specific high-value assets. Best practice uses an ensemble approach: running multiple CMIP6 models through the downscaling process and presenting results as ranges rather than single-point estimates. No single model performs best across all regions and climate variables, so the ensemble spread provides a more honest representation of projection uncertainty.