Case study: Climate scenario analysis for real estate — a startup-to-enterprise scale story

When Jupiter Intelligence launched its first climate risk analytics product for real estate in 2017, fewer than 5% of commercial real estate investors in the UK and North America systematically assessed physical climate risk at the property level. By 2025, that figure had risen to approximately 38%, driven by regulatory mandates, insurance market disruptions, and a growing body of evidence linking unassessed climate exposure to material financial losses. The journey from niche climate science startup to enterprise-scale risk platform illuminates both the enormous opportunity in climate scenario analysis for real estate and the formidable barriers that separate promising technology from market adoption.

Why It Matters

The global commercial real estate market represents approximately $36 trillion in assets under management, with the UK alone accounting for roughly $1.8 trillion. Physical climate risks, including flooding, coastal erosion, subsidence, extreme heat, and windstorm, threaten property values, insurance availability, and long-term investment returns across this entire asset class. Yet until recently, most real estate investment decisions relied on historical hazard data that fundamentally fails to capture how climate change is reshaping risk distributions.

The regulatory environment has transformed the demand landscape. The UK's Task Force on Climate-related Financial Disclosures (TCFD) requirements, mandatory for premium-listed companies since 2021 and extended to large private companies under the Companies Act 2006 amendments in 2022, require firms to assess and disclose climate-related risks using scenario analysis. The Bank of England's Climate Biennial Exploratory Scenario (CBES), completed in 2022, revealed that UK banks held approximately 30% of mortgage exposure in properties with material physical climate risk that had not been priced into lending decisions. The Financial Conduct Authority's Sustainability Disclosure Requirements (SDR), effective from 2024, further expanded climate risk reporting obligations for asset managers with UK real estate holdings.

In the European Union, the Corporate Sustainability Reporting Directive (CSRD) requires large companies to conduct double materiality assessments that include physical climate risk to property assets. The EU Taxonomy's "do no significant harm" criteria explicitly require climate scenario analysis for real estate investments claiming taxonomy alignment. In the United States, the SEC's climate disclosure rules finalized in 2024 mandate that registrants assess material physical climate risks, directly affecting REITs and real estate holding companies.

These regulatory drivers have created a market for climate scenario analysis that McKinsey estimated at $1.4 billion in 2025 and projects to reach $4.8 billion by 2030. However, the path from scientific capability to commercially viable product has proven far more complex than early entrants anticipated.

The Startup Phase: Building the Science Layer (2017-2020)

Jupiter Intelligence was founded in 2017 by Rich Sorkin, a serial technology entrepreneur, and a team of climate scientists from leading research institutions including MIT, Princeton, and the National Center for Atmospheric Research (NCAR). The founding thesis was straightforward: downscaled climate models could provide property-level physical risk assessments with sufficient resolution and accuracy to transform real estate investment decisions.

The initial product, ClimateScore Global, combined outputs from multiple general circulation models (GCMs) with statistical and dynamical downscaling techniques to generate property-level hazard projections at 90-meter resolution. The platform assessed flood risk (fluvial, pluvial, and coastal), extreme heat, wind, drought, and wildfire under Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5, spanning time horizons from 2030 to 2100.

Early technical challenges were substantial. Raw GCM outputs operate at 50-100 kilometer resolution, far too coarse for property-level analysis. Downscaling to actionable resolution required combining multiple statistical methods (bias correction with spatial disaggregation, or BCSD) with regional climate models, validation against observed historical hazard data, and integration of local topographic, hydrological, and land-use information. The computational requirements were enormous: generating property-level projections for a single metropolitan area consumed thousands of CPU-hours and required terabytes of intermediate data storage.

Jupiter raised a $23 million Series A in 2019 led by Energize Ventures with participation from Peter Thiel and other investors. At this stage, the company had approximately 15 paying customers, mostly large insurance companies and reinsurers seeking to supplement their existing catastrophe models with forward-looking climate projections. Annual recurring revenue was below $3 million.

The critical product-market fit challenge was translating climate science outputs into financial decision-relevant metrics. Property investors did not want probability distributions of flood depth under RCP 8.5 in 2070. They wanted to know: "What is the expected annual loss for this building over my investment horizon, and how does that compare to my underwriting assumptions?" Bridging this translation gap between climate science and financial utility defined the company's trajectory.

The Scaling Phase: From Science to Financial Product (2020-2023)

The period from 2020 to 2023 marked Jupiter's transition from a science-driven startup to an enterprise-grade financial technology provider. Several developments accelerated this shift.

First, regulatory mandates created urgent demand. When the UK made TCFD reporting mandatory in 2021, real estate investment trusts (REITs), pension funds, and asset managers suddenly needed climate scenario analysis capabilities they did not possess internally. The Bank of England's CBES exercise required participating banks to model physical climate risk across their mortgage portfolios, generating demand for property-level analytics at unprecedented scale.

Jupiter responded by developing FloodScore UK, a product specifically designed for the British market that integrated Ordnance Survey elevation data, Environment Agency flood maps, Met Office climate projections (UKCP18), and British Geological Survey subsidence data with Jupiter's proprietary downscaling methodology. The product provided property-level flood risk scores under multiple warming scenarios with 30-meter resolution, dramatically exceeding the capabilities of existing UK flood risk tools.

Second, the company restructured its sales approach around financial workflow integration. Rather than selling standalone risk reports, Jupiter developed APIs and data feeds that integrated directly with commercial real estate platforms (CoStar, MSCI Real Capital Analytics), portfolio management systems (Yardi, MRI Software), and enterprise risk management tools. This integration strategy reduced implementation time from months to weeks and enabled customers to incorporate climate risk into existing investment decision workflows without disrupting established processes.

Third, Jupiter raised a $54 million Series C in 2022, valuing the company at approximately $320 million. This capital enabled expansion of the sales team, development of sector-specific products for real estate, infrastructure, and agriculture, and investment in computational infrastructure to support portfolio-scale analysis.

By the end of 2023, Jupiter had over 100 enterprise customers including major UK institutional investors such as Legal & General Investment Management, Aviva Investors, and British Land. Annual recurring revenue had grown to approximately $25 million. The company was processing climate risk assessments for over 200 million properties globally.

Enterprise Adoption: Lessons from UK Market Penetration (2023-2025)

Jupiter's penetration of the UK real estate market between 2023 and 2025 provides instructive lessons about enterprise adoption patterns for climate risk analytics.

Lesson 1: Regulatory compliance drives initial adoption, but financial value drives retention. Early UK customers adopted climate scenario analysis primarily to satisfy TCFD and FCA reporting requirements. However, customer retention correlated strongly with the degree to which climate risk data influenced actual investment decisions rather than merely populating disclosure reports. Customers who integrated climate scores into acquisition due diligence, portfolio optimization, and asset management strategies renewed contracts at 94% rates, compared to 67% renewal rates for compliance-only users.

Lesson 2: Validation against observed events is the ultimate credibility test. Jupiter's reputation in the UK market was significantly enhanced by its performance during the July 2023 flooding in London and the January 2025 coastal surge events in eastern England. Properties flagged as high-risk in Jupiter's forward-looking scenarios experienced loss rates 3.8 times higher than properties rated low-risk, providing empirical validation that forward-looking climate models outperformed historical flood zone designations.

Lesson 3: Resolution and local calibration matter more than model sophistication. UK property investors consistently valued local data quality (accurate elevation models, drainage system data, historical subsidence records) over the sophistication of global climate model ensembles. Jupiter's most successful sales engagements involved demonstrations using specific properties that the client knew well, where the platform's risk assessment aligned with the client's operational experience. This grounding in local reality proved more persuasive than presentations about climate model methodology.

Lesson 4: Data governance and liability concerns delay enterprise procurement. Large UK institutional investors required extensive due diligence on data sourcing, model validation, and liability allocation before signing contracts. Average enterprise sales cycles extended from 3 months for compliance-driven deals to 9-14 months for investment-integration use cases. Key procurement concerns included: intellectual property ownership of generated risk data, liability for investment decisions informed by climate projections, data retention and privacy compliance under UK GDPR, and auditability of model outputs for regulatory examination.

Competitive Landscape and Market Dynamics

Jupiter was not alone in pursuing the climate risk analytics market for real estate. The competitive landscape by 2025 included several categories of providers.

Climate analytics specialists such as Jupiter Intelligence, Moody's (which acquired Four Twenty Seven in 2019), and XDI (Cross Dependency Initiative) offered proprietary climate models with property-level resolution. These providers differentiated on scientific rigor, geographic coverage, and hazard breadth.

Traditional catastrophe modelers including Verisk, CoreLogic, and Munich Re's Location Risk Intelligence expanded their existing property risk platforms to incorporate forward-looking climate scenarios alongside historical catastrophe models. These providers leveraged established relationships with insurance and banking customers.

Real estate data platforms such as CoStar, MSCI, and Londonmetric incorporated third-party climate risk data into their existing property analytics products, functioning as distribution partners rather than primary analytics providers.

Government and nonprofit initiatives including the UK Climate Projections (UKCP18), the Environment Agency's National Flood Risk Assessment, and the Coalition for Climate Resilient Investment (CCRI) provided open data and frameworks that both competed with and complemented commercial offerings.

Market consolidation accelerated between 2023 and 2025. Moody's invested over $200 million in integrating Four Twenty Seven's climate analytics into its ESG and credit risk platforms. MSCI acquired Carbon Delta's physical risk analytics and embedded them in its real estate benchmarks. These acquisitions signaled that climate scenario analysis was transitioning from a standalone product category to an embedded feature within broader financial data platforms.

Performance Metrics and Outcomes

By mid-2025, Jupiter Intelligence's UK operations demonstrated the following performance metrics:

Metric	Value
UK Enterprise Customers	78
Properties Assessed (UK)	14.2 million
Average Contract Value (UK)	$185,000/year
Customer Retention Rate	87%
Model Accuracy (Flood Risk Validation)	82% hit rate for observed loss events
Sales Cycle (Compliance Use Case)	3-4 months
Sales Cycle (Investment Integration)	9-14 months
Revenue Growth (UK, YoY)	45%

British Land, one of Jupiter's early UK customers, reported that integrating climate scenario analysis into its acquisition process led the company to adjust pricing assumptions on 23% of evaluated properties and decline 8% of potential acquisitions that had previously passed conventional due diligence screening. The company estimated that climate-informed acquisition decisions avoided approximately $45 million in potential write-downs based on subsequent observed climate events and insurance market repricing.

Legal & General Investment Management used Jupiter's analytics across its $35 billion UK real estate portfolio to identify $2.1 billion in assets requiring enhanced resilience investment and to prioritize $180 million in adaptation capital expenditure across 340 properties over a five-year program.

Action Checklist

• Assess whether your real estate portfolio requires climate scenario analysis under applicable regulations (TCFD, CSRD, SDR, SEC)
• Evaluate climate risk analytics providers based on hazard coverage, geographic resolution, and financial workflow integration
• Prioritize providers offering validation data showing model performance against observed climate events
• Integrate climate risk scores into acquisition due diligence checklists and investment committee materials
• Establish data governance protocols for climate risk data including retention, access controls, and audit trails
• Allocate budget for both analytics procurement and internal capability building (training analysts to interpret climate scenarios)
• Develop a portfolio-level climate risk dashboard connecting property-level assessments to aggregate exposure metrics
• Schedule annual reassessment as climate models, regulatory requirements, and physical risk profiles evolve

FAQ

Q: What is the minimum portfolio size that justifies investing in climate scenario analysis? A: For UK-focused portfolios, regulatory requirements apply regardless of portfolio size for in-scope entities. For non-regulated investors, the economic threshold is typically 20 or more properties or $100 million in assets under management, where the cost of analytics ($50,000 to $250,000 annually) is justified by risk-adjusted portfolio performance improvements. Smaller portfolios can access property-level climate risk data through platforms like Climate Risk Engines or the UK Environment Agency's free flood risk tools, though these provide less comprehensive scenario coverage.

Q: How reliable are 30-year climate projections for individual property investment decisions? A: Climate projections should be interpreted as ranges of possible futures rather than precise predictions. For real estate investment decisions with 5- to 15-year horizons, near-term projections (2030-2040) show relatively narrow uncertainty bands across emission scenarios, making them reasonably actionable. For longer horizons, scenario divergence increases significantly, and investors should stress-test portfolios against multiple pathways rather than relying on a single projection. The key value of scenario analysis lies in identifying properties where risk is directionally increasing rather than predicting exact loss magnitudes.

Q: What distinguishes enterprise-grade climate analytics from free government data sources? A: Government data sources (Environment Agency flood maps, UKCP18 projections) provide essential baseline information but typically lack the property-level resolution, multi-hazard integration, financial loss modeling, and workflow integration that enterprise users require. Commercial platforms add value through: higher spatial resolution (30 meters versus 1 kilometer), integration of multiple hazards into composite risk scores, translation of physical hazard data into financial metrics (expected annual loss, value-at-risk), API connectivity with portfolio management systems, and regular model updates incorporating new climate science and observed event data.

Q: How should investors weigh climate risk against other property investment factors? A: Climate risk should be treated as a material financial factor alongside location, tenant quality, lease structure, and capital expenditure requirements, not as a separate ESG consideration. Leading UK investors now incorporate climate risk into discounted cash flow models by adjusting insurance cost assumptions, capital expenditure reserves for resilience measures, and terminal value estimates based on long-term hazard trends. Properties with unmitigated high climate risk should be priced at appropriate discounts, not necessarily excluded from portfolios, provided the risk is properly valued and communicated to stakeholders.

Q: What role does insurance market data play in validating climate scenario analysis? A: Insurance market signals provide the most direct financial validation of climate risk assessments. Properties where insurers are withdrawing coverage, increasing premiums disproportionately, or imposing new mitigation requirements are experiencing market-validated climate risk repricing. Jupiter and other providers use historical insurance loss data to calibrate their models, and correlation between model-predicted risk and insurance market pricing serves as a key credibility metric. UK investors should monitor Lloyd's of London climate risk publications and the Association of British Insurers' flood risk data for market-level validation signals.

Sources

• Swiss Re Institute. (2025). Sigma: Natural Catastrophes and Man-Made Disasters in 2024. Zurich: Swiss Re.
• Bank of England. (2022). Results of the 2021 Climate Biennial Exploratory Scenario (CBES). London: Bank of England.
• McKinsey & Company. (2025). Climate Risk Analytics for Real Assets: Market Sizing and Growth Trajectories. London: McKinsey Global Institute.
• Financial Conduct Authority. (2024). Sustainability Disclosure Requirements and Investment Labels: Policy Statement PS23/16. London: FCA.
• Jupiter Intelligence. (2025). UK Physical Climate Risk Assessment: Methodology and Validation Report. San Mateo, CA: Jupiter Intelligence.
• British Land Company plc. (2025). Annual Report and Accounts 2024/25: Climate Risk and Resilience. London: British Land.
• Moody's Analytics. (2025). Physical Climate Risk in Real Estate: From Science to Financial Decision-Making. New York: Moody's Corporation.
• MSCI. (2025). Real Estate Climate Value-at-Risk: Methodology and Market Applications. London: MSCI Inc.