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Can We Use 1D Models to Predict 3D Physics?
  • Yi-Ling Hwong,
  • Steven Sherwood,
  • David Fuchs
Yi-Ling Hwong
Climate Change Research Centre, University of New South Wales

Corresponding Author:[email protected]

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Steven Sherwood
University of New South Wales
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David Fuchs
University of New South Wales
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Abstract

Single-column models (SCMs) are often used to evaluate model physics and aid parameterization development. However, few studies have systematically compared the results obtained using 1D setups with those of their corresponding 3D models, and examined what factors potentially impact their comparability. This paper addresses these questions. We focus on the application of SCMs under idealized RCE conditions and use a multi-column model (MCM) setup as stepping stone for a 3D model. We find that convective organization in the MCM depends at least as much on the convection scheme used as on other mechanisms known to organize convection (e.g., radiative feedback). Moreover, convective organization emerges as a robust factor affecting SCM-MCM comparability, with more aggregated states in 3D associated with larger behavior deviations from the 1D counterpart. This is found across five convection schemes and applies to simulated mean states, linear responses to small tendency perturbations, and adjustments to doubled-CO2 forcing. Applying a “model-as-truth” approach, we find that even when convection is organized, behavior differences between pairs of schemes in the SCM are largely preserved in the MCM. This indicates that when model physics produces accurate behavior in a 1D setup, it will be more likely to do so in a 3D setup. We also demonstrate the practical value of linear responses by showing that they can accurately predict an SCM’s tropospheric adjustment to doubled-CO2 forcing.