Can We Use 1D Models to Predict 3D Model Response to Forcing in an Idealized Framework?. (15th April 2022) - Hwong, Y.‐L.; Sherwood, S. C.; Fuchs, D.
Abstract: Single‐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. Plain Language Summary: To study various climate processes, scientists often use 3D climate models, but these simulations use huge amounts of computing time and resources. One way to alleviate this problem is to use a single‐column model, which is a 1D vertical column extracted from a 3D model. Although these 1D simulations are very efficient, we cannot always be sure that their results are comparable to those of their parent 3D model. In this study, we find that when clouds are randomly spread across the sky (when convection is disorganized), results of 1D and 3D simulations are very similar. However, when clouds are clustered into clumps (when convection is organized), we cannot always trust the results of 1D simulations as they tend to be different from those of 3D simulations. Nevertheless, we find that when two models show very different behavior in their 1D setup, they will tend to also behave differently in their 3D setup. This tells us that 1D simulations can still be useful. We also discover that the way a model responds when it is lightly tickled (perturbed) can be used to predict its responses to a situation where the amount of carbon dioxide in the atmosphere is suddenly doubled. Key Points: Convective organization in large‐scale simulations depends on convection scheme, sometimes more so than on radiative feedback One‐dimensional and 3D behavior is very similar if convection is not organized in 3D A convection scheme's linear responses can be used to predict its tropospheric adjustments to doubled‐CO2 forcing