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Can We Use 1D Models to Predict 3D Model Response to Forcing in an Idealized Framework?

Authors: Hwong, YL; Sherwood, SC; Fuchs, D;

Can We Use 1D Models to Predict 3D Model Response to Forcing in an Idealized Framework?

Abstract

AbstractSingle‐column models (SCMs) simulations are sometimes used to evaluate model physics and aid parameterization development. However, few studies have systematically compared SCM behavior—where column boundary conditions are specified—with that of corresponding 3D models, where columns interact dynamically. Here we address this by comparing forced responses of an SCM in radiative‐convective equilibrium (RCE) with those of a multi‐column model (MCM) where the model domain is in RCE but individual columns are not, examining what factors affect the models' comparability. We find that convective organization in the MCM depends at least as much on the convection scheme 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. Nevertheless, 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. However, our idealized RCE framework implies that these conclusions may not apply to situations with strong large‐scale forcing or encountered over land. Lastly, we demonstrate the practical value of linear responses by showing that they can accurately predict an SCM's tropospheric adjustment to doubled‐CO2 forcing.

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Australia
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Keywords

model evaluation, Physical geography, 610, GC1-1581, Oceanography, radiative‐convective equilibrium, anzsrc-for: 0401 Atmospheric Sciences, anzsrc-for: 3701 Atmospheric Sciences, atmospheric modelling, 13 Climate Action, anzsrc-for: 3704 Geoinformatics, linear response function, 37 Earth Sciences, anzsrc-for: 37 Earth Sciences, doubled-CO2, doubled‐CO2, convective organization, GB3-5030, convective parameterization, climate change, 3701 Atmospheric Sciences, single-column models, multi-column models, radiative-convective equilibrium

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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