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ECS in climate models: quantifying the uncertainties due to cloud feedback versus ocean heat uptake using a modeling hierarchy

Active Dates 9/1/2021-8/31/2024
Program Area Earth & Environmental Systems Modeling
Project Description
Equilibrium Climate Sensitivity (ECS), which characterizes the Earth’s surface temperature response to increased atmospheric CO2 concentration, is an important property of the climate system. The range of ECS diagnosed in comprehensive climate models has not been narrowed with the progress made in these models, leading to large uncertainties in Earth’s temperature projection and associated social-economic impacts. Uncertainties in cloud feedbacks have been identified as the main cause of the large range of ECS, but oceanic adjustments, especially those associated with ocean heat uptake (OHU) and the Atlantic Meridional Overturning Circulation (AMOC), also play an important role. In this proposed work, we will focus on understanding the individual and combined roles of cloud feedbacks and ocean adjustments on modulating the ECS. The proposed research is motivated by our overarching hypothesis that oceanic adjustment is a key source of uncertainty, in addition to that associated with the cloud feedbacks; further, the ocean adjustment and the associated OHU work through the cloud feedbacks to modulate the ECS. Our strategy is to combine existing model output diagnoses with a modeling hierarchy in which we systematically enable and disable cloud feedbacks in conjunction with perturbations to OHU. Specifically, our research will address the following working hypotheses:

H1. Across the CMIP6 multi-model ensemble, polar-amplified OHU efficacy pattern is weakly correlated with cloud feedbacks; subpolar to polar region OHU is negatively correlated with AMOC decline under CO2 forcing (ie, stronger AMOC decline corresponds to weaker OHU and larger ECS).

H2. Contribution from cloud feedback to ECS identified by the cloud-locking method differs from that identified by the conventional radiative kernel method; the identified cloud contribution depends on the spatial pattern and amplitude of the OHU, and are strongly time dependent.

H3. The diverse OHU patterns due to different ocean circulation adjustments across the CMIP6 models contribute to the large intermodel spread in ECS; cloud feedbacks also play a role in modulating the way that OHU contributes to ECS.

H4. OHU in the subpolar North Atlantic and that in the Southern Ocean affect ECS in different ways through local shortwave cloud feedbacks.

To address these hypotheses, we propose to, 1) compute cloud feedback factor, AMOC indices, OHU and other relevant metrics in the CMIP6 (including E3SM) control and quadrupled CO2 experiments and examine their relationships with ECS (address H1); 2) quantify the contributions from cloud feedbacks and OHU on ECS using a E3SM modeling hierarchy where we systematically enable and disable cloud feedbacks in conjunction with OHU perturbations (address H2-4).

Potential Impact The proposed effort is anticipated to help pinpoint the key ocean regions where the OHU contributes most significantly to the ESC uncertainty and therefore provide recommendations on improvements of presentation of ocean processes which may help narrow the ECS uncertainty. Similarly, quantification of the contributions from different cloud regions and cloud types to the ECS uncertainty through the “cloud locking” experiments also points to the directions for model development community (E3SM included) when prioritizing cloud processes for model improvement.
Award Recipient(s)
  • University of Washington Seattle (PI: Cheng, Wei)