Future Warming Pattern Constraints from Internal Climate Variability
M. F. Stuecker, University of Hawai?i at Manoa (Principal Investigator)
The tropical Pacific – home to internal climate variability such as the El Niño-Southern Oscillation (ENSO) – has an outsized impact on the global climate system. Recent research has shown that both the historical and projected future pattern of warming in the tropical Pacific, i.e., if it is El Niño-like or La Niña-like, has not only pronounced impacts on regional climate hazards (such as tropical cyclone risks near Hawaii) but also a large effect on Earth’s overall warming rate as well as its equilibrium warming amplitude in response to increasing greenhouse gas concentrations. Two large uncertainties controlling the future warming pattern evolution across the latest generation of climate models are in (i) the Bjerknes feedback and (ii) cloud feedbacks; the former is a metric of how strong the tropical Pacific Ocean interacts with the atmosphere. To our advantage, these feedbacks not only operate for long-term forced changes in the climate system but are also fundamental components of ENSO dynamics.
Recent parallel advances in (i) our observations – which include the most recent strong 2023/24 El Niño – of clouds and air-sea coupling strength, (ii) high-resolution and large ensemble modeling capabilities (including with DOE models), (iii) our nonlinear theory for ENSO, and (iv) data-driven methods now provide us with the timely opportunity to robustly validate the models against the observed internal variability and test how the realism in capturing the complex processes causing internal climate variability affects their projections of the future warming pattern and hence also the overall rate of global warming. Finding observational constraints for the simulated warming patterns will be critical to reduce uncertainties in both global warming amplitude and regional climate projections, including how tropical cyclone activity will change around Hawaii and US-affiliated Pacific Islands. The project has the following objectives:
O1: Obtain observational constraints from internal variability on the Bjerknes feedback that shapes future tropical warming
O2: Obtain observational constraints from internal variability on cloud feedbacks that shape future tropical warming
O3: Use empirical data science methods to extract the climate patterns originating from internal variability and from the response to CO2 forcing and relate these patterns to the representation of the Bjerknes and cloud feedbacks
The proposed work will result in observational constraints on the future pattern and magnitude of warming and associated regional impacts, including for vulnerable Pacific Islands. All parts of the project are in close collaboration with the Pacific Northwest National Laboratory (PNNL). The team will also closely collaborate with international partners in South Korea and Germany and utilize state-of-the-art ultra-high resolution global warming projections to help improve the representation of the discussed climate feedbacks in the next generation of the DOE climate model.
