Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

[摘要] Realistic simulation of the Earth's mean-state climate remains amajor challenge, and yet it is crucial for predicting the climate system intransition. Deficiencies in models' process representations, propagation oferrors from one process to another, and associated compensating errors canoften confound the interpretation and improvement of model simulations.These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing pastand future climate change. Here we show that a significantly improved globalatmospheric simulation can be achieved by focusing on the realism of processassumptions in cloud calibration and subgrid effects using the EnergyExascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). Thecalibration of clouds and subgrid effects informed by our understanding ofphysical mechanisms leads to significant improvements in clouds andprecipitation climatology, reducing common and long-standing biases acrosscloud regimes in the model. The improved cloud fidelity in turn reducesbiases in other aspects of the system. Furthermore, even though therecalibration does not change the global mean aerosol and totalanthropogenic effective radiative forcings (ERFs), the sensitivity ofclouds, precipitation, and surface temperature to aerosol perturbations issignificantly reduced. This suggests that it is possible to achieveimprovements to the historical evolution of surface temperature over EAMv1and that precise knowledge of global mean ERFs is not enough to constrainhistorical or future climate change. Cloud feedbacks are also significantlyreduced in the recalibrated model, suggesting that there would be a lowerclimate sensitivity when it is run as part of the fully coupled E3SM. Thisstudy also compares results from incremental changes to cloud microphysics,turbulent mixing, deep convection, and subgrid effects to understand howassumptions in the representation of these processes affect differentaspects of the simulated atmosphere as well as its response to forcings. Weconclude that the spectral composition and geographical distribution of theERFs and cloud feedback, as well as the fidelity of the simulated baseclimate state, are important for constraining the climate in the past andfuture.

[学科分类] 土木及结构工程学