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The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

Active Dates 9/15/2020-9/14/2024
Program Area Earth & Environmental Systems Modeling
Project Description
This proposed project will analyze E3SM and other CMIP6 models to establish the physical pathways that link deep convection, large-scale circulation and low cloud feedback in present and future climate, and use observations to evaluate CMIP6 models including E3SM and to narrow the uncertainties in E3SM model physical parameters that are critical for the representation of deep convection, circulation and cloud feedback. Process-oriented model diagnostics will be used to characterize E3SM and other CMIP6 model representation of these pathways. Error decomposition in CMIP6 and perturbed physics experiments (PPEs) with E3SM will be conducted. Multiple observations will be applied throughout to constrain these pathways, with the ultimate goal of reducing the CMIP6 model spread in equilibrium climate sensitivity (ECS) and improving the accuracy of E3SM climate predictions. 

Based on a set of PPEs using the Community Earth System Model (CESM) in which deep convective parameters were altered (Schiro et al. 2019), we conjecture that there are three major pathways through which deep convection and large-scale circulation changes can modify low cloud fraction (LCF) in a warmer climate: (1) the temperature-stability pathway, through which tropospheric temperature anomalies propagated by wave dynamics subsequently modify lower tropospheric stability, (2) the moisture-mixing pathway that may depend on shallow ascent and subgrid-scale mixing of moisture between the free troposphere and the marine boundary layer (MBL), and (3) the radiation-stability pathway that involves longwave radiation mediated subsidence control on LCF. We hypothesize that the differences in deep convective parameterizations between climate models drive a significant fraction of inter-model spread in low cloud feedback and ECS through these pathways.

In this project, we will 1) characterize the representation of the three pathways in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) use process-oriented diagnostics to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs); 3) conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. Multiple satellite and ground-based observations and reanalyses will be applied throughout to assess CMIP6 model fidelity and constrain E3SM model physics. We will leverage existing metrics and benchmarking packages available at PCMDI and contribute new metrics and diagnostic tools to augment the diagnostic capabilities of RGMA. This work builds on the strong expertise of the proposal team in model-observation diagnostics and evaluation of climate models using observations especially for deep convection, circulation, clouds and precipitation.

  The proposed study targets the intimate linkage between deep convection and low cloud feedback through large-scale circulation and addresses one of the grand challenges put forward by the World Climate Research Program on “Clouds, Circulation and Climate Sensitivity”. It addresses one of the major thrusts of the RGMA, “Cloud Processes and Feedbacks.” It focuses on “Analysis of Earth System Processes, Interactions, and Feedbacks across scales using E3SM and other Earth System Models (ESMs) which are part of the CMIP6”. It will help answer “how do clouds respond to and interact with climatic, large-scale and local atmospheric, and surface-atmosphere changes; and what are the causes for the spread in Equilibrium Climate Sensitivity?” The proposed development of new metrics, diagnostics and benchmarks will help enhance the model evaluation capabilities of RGMA, and contribute to the RGMA’s objectives “to enhance a predictive and process level understanding of variability and change within the Earth system by advancing capabilities to design, evaluate, diagnose, and analyze global and regional Earth system model simulations informed by observations.
Award Recipient(s)
  • University of California, Los Angeles (PI: Su, Hui)