Sustainability Atlas
Climate Tech & Data·12 min read··...

Deep dive: climate risk analytics & scenario modeling — the fastest-moving subsegments to watch (angle 4)

the fastest-moving subsegments to watch. Focus on a city or utility pilot and the results so far.

Deep Dive: Climate Risk Analytics & Scenario Modeling — The Fastest-Moving Subsegments to Watch

The climate risk analytics market reached an estimated $9.84 billion in 2024, growing at a compound annual rate of 17.5% according to Business Research Insights—a trajectory that positions this sector among the fastest-expanding domains in sustainability technology. Cloud-based deployments surged 44% between 2023 and 2025, while AI-assisted predictive models now represent 36% of new system implementations. Perhaps most striking: 14,000 small and medium enterprises globally integrated climate risk solutions in 2024 alone, signalling a democratisation of capabilities once reserved for multinational corporations and large financial institutions. For utilities and municipal governments, these analytics are no longer theoretical exercises but operational imperatives, with public sector demand rising 37% in the past year as climate adaptation moves from strategic planning documents to infrastructure investment decisions.

Why It Matters

Climate risk analytics and scenario modeling have evolved from compliance-driven exercises to core strategic functions across multiple sectors. The World Economic Forum estimates global climate change damages between $1.7 and $3.1 trillion annually by 2050, creating an economic imperative that transcends environmental stewardship. Financial institutions now represent 39% of global climate analytics users, driven by regulatory mandates including the UK's TCFD requirements and the European Union's SFDR and CSRD frameworks.

For UK utilities specifically, climate scenario modeling has become central to regulatory compliance. Ofwat mandates the use of Representative Concentration Pathways (RCPs) for Price Review 2024, requiring water companies to model infrastructure resilience across RCP2.6 (optimistic emission reduction) and RCP8.5 (high-emission pathway) scenarios through 2075. Thames Water's Water Resources Management Plan 2024 projects deployable output reductions of 1.03 to 4.54 megalitres per day depending on climate scenarios—figures that directly inform billions of pounds in infrastructure investment decisions.

The insurance sector expanded analytics usage by 32% in 2024, while government agencies adopted geospatial models in 26% of resilience initiatives. These statistics reflect a fundamental shift: organisations are moving from backward-looking historical data to forward-looking probabilistic models that integrate physical and transition risks across multiple time horizons.

Key Concepts

Understanding climate risk analytics requires familiarity with several interconnected frameworks and methodologies that underpin modern scenario modeling.

Physical Risk vs. Transition Risk: Physical risks encompass direct climate impacts including flooding, drought, extreme heat, and wildfire. Transition risks address policy changes, technological disruption, and market shifts associated with decarbonisation pathways. Leading analytics platforms now integrate both dimensions, though a 2024 survey found that 35% of organisations struggle to merge physical and transition risk metrics effectively.

Representative Concentration Pathways (RCPs): The Intergovernmental Panel on Climate Change developed RCPs as standardised greenhouse gas concentration trajectories. RCP2.6 represents aggressive mitigation achieving net-zero emissions by 2070, while RCP8.5 models continued high emissions. UK water utilities are required to model infrastructure against both scenarios for regulatory submissions.

CMIP6 Climate Models: The Coupled Model Intercomparison Project Phase 6 provides the scientific foundation for most commercial climate risk products. Jupiter Intelligence, for example, builds its ClimateScore Global platform on CMIP6 models with 90-metre grid resolution globally, enabling asset-level risk assessment.

Scenario-Based Load Forecasting: National Grid's Future Energy Scenarios framework exemplifies utility-scale scenario modeling, projecting electricity demand growth from electric vehicles, heat pumps, and data centres across multiple decarbonisation pathways to 2050.

KPI CategoryMetricTypical RangeLeading Threshold
Model ResolutionGrid cell size1km - 90m<100m
Time HorizonProjection period2030-20502100+
Hazard CoveragePhysical risk types3-5 hazards8+ hazards
Scenario DiversityRCP/SSP pathways modeled2 scenarios4+ scenarios
Update FrequencyModel refresh cycleAnnualQuarterly
Asset CoverageEntities modeled10,000+48,000+

What's Working and What Isn't

What's Working

Cloud-Based Platform Deployment: The shift to cloud infrastructure has accelerated accessibility dramatically. Over 3,200 enterprises transitioned to cloud-based climate risk platforms in 2024, with SME adoption growing 39% year-over-year. This democratisation enables smaller organisations to access sophisticated modeling capabilities previously requiring substantial in-house data science teams.

Regulatory-Driven Standardisation: The proliferation of disclosure requirements—including TCFD, SFDR, and the UK's Climate Change Adaptation Reporting—has created consistent demand signals for analytics providers. Over 60 nations adopted or announced mandatory climate risk disclosure regulations, establishing a baseline level of market demand that supports continued platform development.

Adaptation ROI Modeling: Jupiter Intelligence's MetricEngine exemplifies an emerging capability: calculating avoided losses versus adaptation costs for specific interventions such as flood protection infrastructure, wind retrofits, and cooling systems. This cost-benefit framing transforms climate analytics from risk identification to investment prioritisation.

UK Utility Integration: Thames Water's Climate Change Adaptation Report 2024 demonstrates mature integration of scenario modeling into operational planning. Climate change is now a Strategic Principal Corporate Risk sponsored at Board level, with a dedicated Climate Change Working Group established in 2022 and quarterly Executive Risk Committee reviews. National Grid's Future Energy Scenarios 2025 provides similarly rigorous pathway modeling, with 74% of Great Britain's electricity generation now sourced from low-carbon technologies.

What Isn't Working

Model Divergence and Comparability: A Bloomberg investigation in August 2024 revealed significant variation between climate risk models. Jupiter Intelligence and competitor XDI showed only 21% agreement on identifying vulnerable properties in New York City coastal flooding scenarios for 2100. This divergence creates substantial challenges for investors comparing assets analysed by different providers.

Internal Expertise Gaps: Despite platform accessibility improvements, 46% of organisations cite lack of internal expertise as a primary adoption barrier. Climate risk analytics require interpretation within specific business contexts—a capability that software alone cannot provide.

Physical-Transition Integration: While platforms increasingly offer both physical and transition risk metrics, 35% of organisations report difficulties merging these dimensions into coherent strategic frameworks. Physical risks manifest at asset level while transition risks operate at sector and policy scales, creating analytical challenges that current tools address imperfectly.

SME Capacity Constraints: Although 14,000 SMEs implemented climate risk solutions in 2024, implementation depth varies considerably. Many smaller organisations lack the governance structures to translate analytics outputs into investment decisions, limiting the practical impact of platform adoption.

Key Players

Established Leaders

Moody's Climate Solutions provides comprehensive physical and transition risk platforms with Climate Risk Scores for commercial real estate and economic forecast scenarios covering 70+ countries and 18,000 macroeconomic variables. Their integration with credit rating methodologies positions them strongly for financial sector applications.

Bloomberg Sustainable Finance offers physical risk coverage for 48,000+ companies using 1.1 million physical assets data through partnership with RiskThinking.AI. Their BNEF TRACT model assesses low-carbon transition revenue impact across 70,000 companies.

MSCI Climate Data and Metrics serves 43 of the top 50 global asset managers, providing climate risk measurement data integrated with their broader ESG research capabilities. Their partnership with Bloomberg for ESG/climate indices extends reach across fixed income and equity markets.

S&P Global Sustainable1 delivers climate analytics integrated with credit ratings and market intelligence, offering particular strength in transition risk assessment and carbon pricing scenarios.

Emerging Startups

Jupiter Intelligence offers ClimateScore Global with industry-leading 90-metre resolution globally and 8 physical hazards modeled through 2100. Their PwC UK partnership for Physical Climate Analytics positions them for enterprise deployment in regulated sectors.

Cervest (UK-based) provides Earth Science AI platform for asset-level physical risk assessment, with particular focus on agricultural and real estate applications.

Sust Global delivers climate risk scores for financial portfolios with emphasis on emerging market coverage and localised hazard modeling.

One Concern combines climate risk with seismic modeling for comprehensive natural catastrophe assessment, targeting insurance and municipal planning applications.

Key Investors & Funders

Breakthrough Energy Ventures has backed multiple climate analytics companies as part of their broader climate technology portfolio, recognising data infrastructure as foundational to decarbonisation.

Generation Investment Management (co-founded by Al Gore) maintains positions in climate data and analytics firms aligned with their long-term sustainable equity strategy.

UK Infrastructure Bank provides debt financing for climate-resilient infrastructure, creating demand for analytics that inform investment decisions.

Climate Policy Initiative tracks $147 billion annual urban adaptation needs through 2030 in emerging markets alone, highlighting the scale of investment requiring climate risk assessment.

Examples

  1. Thames Water Climate Adaptation Programme: Thames Water's 2024 Climate Change Adaptation Report integrates RCP2.6 and RCP8.5 scenarios across Water Resources Management Plan 2024 (horizon to 2075) and Drainage & Wastewater Management Plan (horizon to 2050). Climate modeling revealed deployable output reductions of 1.03-4.54 Ml/d, driving infrastructure investment prioritisation. The utility established a Board-level Climate Change Working Group in 2022, with quarterly Executive Risk Committee reviews embedding scenario modeling into governance structures. Their October 2023 Business Plan submission to Ofwat incorporated these scenarios directly into capital expenditure justifications.

  2. National Grid/NESO Future Energy Scenarios 2025: The National Energy System Operator publishes annual Future Energy Scenarios exploring credible decarbonisation pathways for Great Britain. Their 2024/2025 framework projects grid decarbonisation trajectories toward the government's 2035 zero-carbon electricity target, modeling technology growth for EVs, heat pumps, and distributed generation. In 2024, 74% of GB generation came from low-carbon sources, with renewables delivering 47% of total supply (152 TWh). The Distribution Future Energy Scenarios 2024 now covers 120 local authorities, incorporating approximately 8,000 local projects and extending analysis to maritime, aviation, rail, and agriculture sectors.

  3. NetZeroCities European Pilot Programme: The Climate-KIC NetZeroCities programme coordinates 104 cities across Europe testing rapid decarbonisation through science-based climate research integration. Cohort 3 (2024) deploys innovative technology, products, and policy models across water, food, energy, industry, housing, transport, and mobility sectors. The two-year programmes test business models, governance innovations, and funding mechanisms, providing real-world validation of scenario-based planning approaches. Cities receive capacity building through training and workshops for local government officials, addressing the expertise gaps that limit analytics adoption.

Action Checklist

  • Conduct baseline assessment of current climate risk data sources and identify gaps in physical and transition risk coverage
  • Evaluate platform options against resolution requirements, hazard coverage, and regulatory alignment (TCFD, SFDR, UK Climate Change Adaptation Reporting)
  • Establish governance structures for climate risk integration, including Board-level sponsorship and dedicated working groups following Thames Water model
  • Develop scenario selection framework incorporating both RCP pathways (2.6 and 8.5) and organisation-specific transition scenarios
  • Build internal interpretation capability through training programmes or advisory partnerships to translate analytics into investment decisions
  • Implement quarterly review cycles for climate risk monitoring, aligned with existing enterprise risk management frameworks
  • Engage with sector-specific initiatives (e.g., NetZeroCities for municipalities, NESO Future Energy Scenarios for energy sector) to benchmark approaches

FAQ

Q: How do organisations choose between competing climate risk analytics platforms given significant model divergence? A: Model selection should prioritise regulatory alignment, sector-specific hazard coverage, and resolution appropriate to asset types. Bloomberg's 2024 analysis revealed only 21% agreement between leading models on coastal flooding scenarios, suggesting that organisations should focus on consistency within their portfolio rather than absolute accuracy claims. Many sophisticated users deploy multiple platforms for cross-validation, particularly for high-value assets. Regulatory requirements (e.g., Ofwat's RCP mandate for UK water utilities) may constrain platform choices, making compliance alignment the primary selection criterion.

Q: What internal capabilities are required to translate climate analytics into actionable investment decisions? A: Effective implementation requires three capability layers: technical capacity to operate platforms and interpret outputs; business context knowledge to translate risk scores into operational implications; and governance structures to embed climate considerations in capital allocation processes. The 46% of organisations citing expertise gaps as adoption barriers underscores that platform subscription alone is insufficient. Successful implementations typically involve advisory partnerships during initial deployment, phased capability building, and integration with existing enterprise risk management frameworks rather than standalone climate functions.

Q: How are UK regulators shaping climate scenario requirements for utilities? A: Ofwat mandates RCP2.6 and RCP8.5 scenario modeling for Price Review 2024 covering 2025-2030, requiring water companies to demonstrate infrastructure resilience across climate pathways through 2075 for Water Resources Management Plans. The National Energy System Operator publishes Future Energy Scenarios annually, which effectively establish the analytical framework for energy sector planning submissions. Climate Change Adaptation Reporting requirements under the Climate Change Act create consistent demand for standardised scenario outputs. These regulatory frameworks increasingly reference CMIP6 climate models and IPCC AR6 scenarios as authoritative baselines.

Q: What distinguishes physical risk analytics from transition risk analytics, and why does integration remain challenging? A: Physical risk analytics assess direct climate impacts (flooding, heat stress, drought) at asset level using geospatial data and climate models. Transition risk analytics evaluate policy, technology, and market shifts associated with decarbonisation at sector and economy-wide scales. Integration challenges arise from different data sources (climate models vs. policy databases), time horizons (physical risks manifest over decades while transition risks can crystallise rapidly), and analytical methodologies. Leading platforms increasingly offer both dimensions, but 35% of organisations report difficulties creating coherent strategic frameworks that span physical and transition risk.

Q: How should organisations approach the cost-benefit analysis of climate adaptation investments? A: Jupiter Intelligence's MetricEngine represents emerging best practice, calculating avoided losses versus adaptation costs for specific interventions including flood protection, wind retrofits, and cooling systems. Effective cost-benefit frameworks require probabilistic damage functions, discount rate assumptions appropriate for long-horizon infrastructure investments, and co-benefit valuation (e.g., ecosystem services from nature-based solutions). UK Infrastructure Bank financing frameworks increasingly require climate risk assessment as part of investment due diligence, creating standardised expectations for adaptation ROI methodologies.

Sources

Topics

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