Abstract

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

Highlights

  • Atmospheric general circulation models (AGCMs) simulate physical and chemical processes in the Earth’s atmosphere by solving a complex set of ordinary and partial differential equations

  • – The parameterizations of stratiform and shallow cumulus clouds include two elements: (1) a treatment of turbulence and shallow convection using a parameterization named Cloud Layers Unified By Binormals (CLUBB; Golaz et al, 2002; Larson et al, 2002; Larson and Golaz, 2005), which we refer to for brevity as cloud macrophysics in this paper, and (2) a treatment for aerosol activation and the further evolution of cloud condensate, which we refer to as cloud microphysics

  • Reductions in the various step sizes all lead to weakening of both LWCRE and SWCRE, the total cloud radiative effect (CRE) changes seen in Fig. 10g are dominated by the SW changes attributable to reduced low-cloud fractions associated with shorter time steps outside the cloud macrophysics and microphysics subcycles (Figs. 10f and 9f)

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Summary

Introduction

Atmospheric general circulation models (AGCMs) simulate physical and chemical processes in the Earth’s atmosphere by solving a complex set of ordinary and partial differential equations. Various studies have shown examples in which temporal discretization methods in AGCMs, especially those used in the parameterization of unresolved processes or the coupling between processes, can produce large errors that significantly affect key features of the numerical results (e.g., Wan et al, 2013; Gettelman et al, 2015; Beljaars et al, 2017; Donahue and Caldwell, 2018; Zhang et al, 2018; Barrett et al, 2019) These results are not surprising given the relatively short timescales associated with parameterized processes, such as clouds and turbulence, and the relatively long time steps (typically on the order of tens of minutes) used by current global atmospheric GCMs. This study attempts to take a first step towards assessing and addressing time integration issues associated with physics parameterizations in the atmospheric component of the U.S Department of Energy’s Energy Exascale Earth System Model version 1, hereafter referred to as EAMv1 (Rasch et al, 2019; Xie et al, 2018).

Model and simulation overview
Present-day climate simulations
Statistical tests
Impact of proportional step size reductions in all major processes
Time step sensitivities in EAMv1
Comparison with observations and EAMv0
Attributing time step sensitivities in cloud fraction and CRE
Stratiform cloud parameterizations versus the rest of EAMv1
Dynamic versus thermodynamic responses of the subtropical climate
Further attribution of subtropical low-cloud changes
Resolved dynamics and radiation
Coupling between cloud macrophysics–microphysics and other processes
Deep convection
Findings
Conclusions
Full Text
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