Climate change in Europe and most other regions in the world can unambiguously attributed to human influence
Artist’s interpretation of the concept of the human fingerprint in the climate system.
© Yvonne Schrader, Max-Planck-Institut für Meteorologie
To the point:
- Regional climate changes: Global warming has clearly emerged as the dominant signal amid natural climate fluctuations. Nevertheless, there are regional differences and, in some cases, discrepancies between model predictions and observations.
- Human Fingerprint: Researchers have derived the human “fingerprint” directly from observations. This allows them to attribute regional climate changes to human-induced climate change. The concept is based on the “detection and attribution” method developed by Nobel laureate Klaus Hasselmann, the founding director of the Max Planck Institute for Meteorology.
- Emergence Timescale: The time it takes for the human signal to emerge from the climate noise varies by region and is often underestimated in models. The current period of satellite observations is sufficient to provide purely empirical evidence of human-induced warming in most regions like in Europe for example.
- Detailed analysis of regional climate change: The results improve our understanding of regional climate change with relevance for adaptation planning and climate litigation.
There is no question that the current global temperature increase is human-made. Global warming has long since emerged as the dominant signal amid natural climate fluctuations. However, identifying how this warming manifests itself regionally remains a key challenge. Observations do not always align with climate model predictions. For example, the southeastern Pacific and parts of the Southern Ocean have cooled, and the subpolar North Atlantic hasn’t warmed as much as expected. This raises the question: Are expectations regarding the typical warming pattern associated with rising greenhouse gas levels equally accurate everywhere? Or put differently, how reliable is the model-based ‘fingerprint’ of human activity in the climate system at the regional level?
Researchers at the Max Planck Institute for Meteorology have developed an empirical tool to answer these questions. Aruhasi, Dirk Olonscheck, Jochem Marotzke and Chao Li identified the fingerprint in observational data by using global datasets of measured surface temperatures from 1850 to 2022 and linking the regional observed temperature with the globally averaged temperature increase-a value where models and observations are in very good agreement. Analyzing this ‘observed fingerprint’ allows scientists to attribute climatic changes at a regional level to human-induced climate change. Thus the human influence can be shown in most regions in the world, as in Europe for example.
Observed pattern versus model prediction
Furthermore, by comparing the observed fingerprint with its model-based counterpart, the researchers can investigate the uncertainties of climate models in more detail. They focused on four regions where this uncertainty is particularly high: Aside from the southeastern Pacific, the Southern Ocean, and the subpolar North Atlantic, where models and observations exhibit the aforementioned discrepancies, this includes the Arctic as an example of a region severely affected by climate change.
Warming proceeded very rapidly there from the mid-20th century onwards and temporarily slowed from the late 1990s to the early 2010s. The study shows that this slowdown is due to natural variability, yet the human influence is nevertheless evident. The same applies to the southeastern Pacific. However, in parts of the Southern Ocean and the subpolar North Atlantic, human-induced warming has not clearly emerged from the ‘background noise’ of natural climate fluctuations.
“The time it takes for the human signal to emerge from the noise varies by region,” explains lead author Aruhasi. “This ’emergence timescale’ is often underestimated by models.” With regard to climate observations, this metric also allows to define time periods in each region that are required to demonstrate the human influence beyond a doubt. “The current period of satellite observations, at around 45 years, is sufficient to provide purely empirical evidence of human-induced warming in most regions,” says Chao Li, group leader at the max Planck Institute for Meteorology.
Human influence-primarily through CO2 emissions-is already clearly detectable in large parts of the world. The “emergence timescale” refers to the period prior to 2022 during which the human fingerprint became clearly detectable in natural climate fluctuations. In the hatched regions, the observed period is not long enough to provide such evidence.
© MPG nach CC BY 4.0 Aru et al. 2026, DOI: 10.1126/sciadv.aed1506
Background: The method of detection and attribution
In climate research, detecting climatic changes and attributing them to a cause is a routine task. The ‘detection and attribution’ method, which is also used by the Intergovernmental Panel on Climate Change (IPCC), is based on the work of Nobel laureate Klaus Hasselmann, founding director of the Max Planck Institute for Meteorology. The first step is to demonstrate that a climatic change is statistically distinct from natural climate fluctuations (detection). The second step involves identifying the cause (attribution). To achieve this, researchers traditionally use climate models to determine the characteristic pattern of change produced by a specific influencing factor. For instance, an increase in greenhouse gases in the atmosphere causes the troposphere to warm while the stratosphere cools. Furthermore, warming is more pronounced over land than over the oceans, and the Arctic is warming particularly fast. Since the observed climate change generally bears this fingerprint, its cause is unequivocal.
The observed fingerprint, presented in the new study, builds on Hasselmann’s concept: It allows for a more detailed diagnosis of the regional expression of human-induced climate change and helps to assess the consistency between observed changes and model-based expectations, with relevance for adaptation planning and climate litigation.
