Rémy Bonnet, Didier Swingedouw, Guillaume Gastineau, Olivier Boucher, Julie Deshayes, Frédéric Hourdin, Juliette Mignot, Jérôme Servonnat & Adriana Sima
Climate sensitivity is a key part of climate model projections, helping define how much warming at the global scale we might expect to see in future. The latest models, dubbed CMIP6, generally show higher climate sensitivity than CMIP5, raising concerns about how to remain below key thresholds defined by the Paris Agreement. This study investigates the internal variability from a few large ensembles of simulations. In one of the models, the team found that the simulations that best matched observed temperatures in the historical period also had significant weakening of Atlantic Ocean currents due to internal multi-centennial variability. This may mask global warming and lead us to underestimate climate sensitivity when using recent observed global warming to constrain climate projections. These findings are important for informing the latest climate policies aimed at mitigating and adapting to the impacts of future climate.
Climate sensitivity, how much warming we can expect for a given level of greenhouse gas emissions, is a crucial part of our climate projections. The most recent generation of climate models, CMIP6, tend to show higher sensitivity than their CMIP5 predecessors, projecting larger changes in future temperature than previously thought. It is important to understand how realistic these models might be by using them to simulate the historical climate and comparing their simulations with observations made at the time. Various studies have attempted this, however the natural, internal variability in the climate has proven to be a confounding factor, complicating how well we can compare the model simulations with observations. This study addresses this issue by using a sensitive CMIP6 model with high internal variability, allowing factors influencing the simulations to be identified. Improving our understanding of these model simulations can help improve our future projections, which play a key role in planning for future climate change.
The team used a climate model with quite high sensitivity to run a large ensemble of historical simulations differing only by their initial conditions in 1850, capturing the range of possible climate development given the uncertainties in measurements and projections. They found that the ensemble members that best matched observed temperatures over the last 60 to 70 years, the ones with the lowest rates of global warming, also showed significant weakening in the Atlantic Meridional Overturning Circulation (AMOC). This large system of ocean currents has a strong influence on global climate, and its weakening in the simulations matches well with observed data. The weakening AMOC appears to have masked some global warming in these ensemble members. As it is a result of internal variability, this might mean that climate sensitivity has been somewhat underestimated in observational data thanks to this masking effect. When these ensemble members with a weakening AMOC were allowed to continue to run into the future, they experienced an AMOC strengthening and a slightly higher rate of warming as a result. These refinements to our understanding of future warming are important for informing climate policies aimed at reducing future climate impacts.
This study used the IPSL-CM6A-LR climate model, a member of the CMIP6 generation of models. 32 simulations made up the overall ensemble. Historical simulations ran from 1850 to 2014. The simulations were then extended to 2060 using forcings from the medium-emissions SSP245 scenario to capture future climate change. The historical simulations were compared with observational temperature data from the HadCRUT4-CW dataset to assess how well they simulated observed changes. Various AMOC indices were used to verify the weakened AMOC signal in the best-performing ensemble members.
Refinements to our understanding of past and future climate change, such as this study, help inform communities and climate policymakers tasked with implementing strategies to mitigate and adapt to the impact of climate change. The best-informed policies are important for limiting future climate impacts.
Some of the new generation CMIP6 models are characterised by a strong temperature increase in response to increasing greenhouse gases concentration. At first glance, these models seem less consistent with the temperature warming observed over the last decades. Here, we investigate this issue through the prism of low-frequency internal variability by comparing with observations an ensemble of 32 historical simulations performed with the IPSL-CM6A-LR model, characterized by a rather large climate sensitivity. We show that members with the smallest rates of global warming over the past 6-7 decades are also those with a large internally-driven weakening of the Atlantic Meridional Overturning Circulation (AMOC). This subset of members also matches several AMOC observational fingerprints, which are in line with such a weakening. This suggests that internal variability from the Atlantic Ocean may have dampened the magnitude of global warming over the historical era. Taking into account this AMOC weakening over the past decades means that it will be harder to avoid crossing the 2°C warming threshold.