SciTransfer
Organization

THE CLIMATE DATA FACTORY

Paris-based SME transforming climate model outputs into actionable data products for energy forecasting, seasonal prediction, and extreme event detection.

Technology SMEenvironmentFRSME
H2020 projects
3
As coordinator
0
Total EC funding
€915K
Unique partners
35
What they do

Their core work

The Climate Data Factory is a Paris-based SME that transforms raw climate model outputs into usable, decision-ready climate data products. They specialize in downscaling and bias-correcting climate projections to make them actionable for energy sector planning, renewable energy forecasting, and seasonal-to-subseasonal prediction. Their work sits at the intersection of climate science and applied data services — turning complex climate simulations into products that energy managers, grid operators, and planners can actually use.

Core expertise

What they specialise in

Climate data processing and bias correctionprimary
3 projects

Core contributor across all three H2020 projects (CLARA, S2S4E, CLINT), consistently providing climate data transformation services.

Sub-seasonal to seasonal climate forecasting for energyprimary
2 projects

S2S4E focused directly on climate forecasting for energy applications; CLARA addressed climate forecast-enabled knowledge services.

Machine learning for climate extreme eventsemerging
1 project

CLINT (2021-2025) applies machine learning to extreme event detection and attribution — their largest funded project at EUR 462,477.

Energy demand and supply forecastingsecondary
1 project

S2S4E specifically addressed energy demand, supply, and market implications of climate variability.

Decision support tools for climate servicessecondary
2 projects

Both S2S4E and CLARA involved building decision support tools that translate climate data into actionable guidance.

Evolution & trajectory

How they've shifted over time

Early focus
Climate forecast services for energy
Recent focus
ML-driven climate extreme detection

The Climate Data Factory began with foundational climate services work — CLARA and S2S4E (both 2017-2020) focused on translating seasonal climate forecasts into usable knowledge products, particularly for energy management and renewable energy planning. Their most recent project, CLINT (2021-2025), marks a clear shift toward machine learning methods applied to climate extremes, with significantly larger funding. This progression shows a company moving from climate data processing toward AI-driven climate intelligence, adding computational sophistication to their core climate data expertise.

Moving toward AI and machine learning applications in climate science, with growing project budgets suggesting increasing trust and capability in this direction.

Collaboration profile

How they like to work

Role: specialist_contributorReach: European10 countries collaborated

The Climate Data Factory operates exclusively as a consortium participant, never as coordinator — typical for a specialized SME that provides a specific technical capability (climate data products) rather than managing large projects. With 35 unique partners across 10 countries in just 3 projects, they work within large consortia and bring their niche expertise to diverse teams. This pattern suggests they are easy to integrate into new consortia as a reliable specialist contributor.

Despite only three projects, they have built a network of 35 partners across 10 countries, indicating involvement in large, multi-national consortia typical of EU climate research. Their Paris base connects them to France's strong climate science ecosystem.

Why partner with them

What sets them apart

The Climate Data Factory occupies a specific niche: they are a private company that makes raw climate model data usable for non-climate-scientists. While research institutes produce climate projections and energy companies need them, few SMEs specialize in the translation layer between the two. Their combination of climate data processing expertise with growing machine learning capability makes them a practical bridge between climate science and industry applications.

Notable projects

Highlights from their portfolio

  • CLINT
    Their largest project (EUR 462,477) and most recent, applying machine learning to climate extremes — signals their strategic direction toward AI-climate integration.
  • S2S4E
    Directly connects sub-seasonal climate forecasting to energy sector applications, representing their core value proposition of making climate data actionable for industry.
Cross-sector capabilities
Energy — renewable energy forecasting and grid planningDigital — machine learning and probabilistic data productsTransport — climate impact assessment for infrastructure planningFood — seasonal climate forecasts for agricultural decision-making
Analysis note: Profile based on only 3 projects, all as participant. The company name and project themes give a reasonably clear picture of their niche, but the limited project count means expertise breadth may be understated. No website was available in the data to verify current services or capabilities beyond H2020 participation.