Conflicts of interest at the IPCC: Twenty fossil fuel experts threaten the credibility of climate models
European media outlets have revealed that over twenty contributors to the IPCC maintain direct ties with the oil industry. This revelation reignites the debate on scientific independence and the risk of bias in global climate models.
At least twenty experts involved in IPCC reports maintain direct links with petroleum companies, according to an investigation by several European media outlets. This figure, representing a significant portion of contributors, reignites the thorny issue of conflicts of interest at the heart of the most influential synthesis on climate science.
The revelations: Who are the contributors linked to the fossil fuel industry?
Investigations have identified researchers and analysts working for consultancy firms or think-tanks funded by oil and gas majors. Some of them simultaneously hold co-author positions in IPCC chapters and advisory roles with companies like TotalEnergies or Shell. Although their contributions cover various topics – from emission modeling to regional impact assessment – simply receiving revenues from the fossil fuel industry raises doubts about their impartiality.
These experts often have access to exclusive databases, including hydrocarbon production records and internal studies on carbon capture technologies. This proximity may, even unintentionally, influence how they interpret atmospheric data or future emission scenarios. The IPCC, which relies on complex climate models, must therefore ensure that contributions are not colored by economic interests.
Why these conflicts of interest threaten the reliability of climate models
IPCC reports rely on predictive models developed by institutions like ECMWF or the Copernicus program. These models integrate satellite data, surface observations, and atmospheric data collected over several decades. The emergence of machine learning, via neural networks like GraphCast or Pangu-Weather, has allowed for refined forecasts and reduced prediction uncertainty in many scenarios.
When contributors have financial interests in industries that are the main sources of emissions, there is a risk that their evaluations of uncertainties or recommendations for mitigation scenarios may be biased. For example, an author linked to an oil company might underestimate the contribution of fossil fuels to radiative forcings, or emphasize carbon capture technologies as major solutions, even if scientific evidence remains limited. This type of bias, even subtle, can propagate in predictive models and affect global temperature or precipitation projections.
