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

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

Midlatitude Jet Position Spread Linked to Atmospheric Convective Types

Midlatitude weather is largely governed by bands of strong westerly winds known as the midlatitude jets, but what controls the jet properties, particularly their latitudes, remains poorly understood. Climate models show a spread of about 108 in their simulated present-day latitude of the Southern Hemisphere (SH) jet, and a related spread in its predicted poleward shift under global warming. We find that models with more poleward jets simulate more low-level moisture, a warmer upper troposphere, and different precipitation patterns than those with equatorward jets, potentially implicating intermodel differences in moist convection and microphysics. Accordingly, a suite of atmospheric model runs is performed where the deep or shallow convective parameterizations are individually turned off either globally or in specific latitude bands. These experiments suggest that models that produce more shallow convection in the midlatitudes tend to position the jet relatively poleward in SH summer, whereas those that favor deep convection tend to position it equatorward. This accounts for a spread 60% as large as that of the AMIP ensemble during the austral summer. Our results suggest that, in the boreal summer, similar biases appear in the Northern Hemisphere. The presence of shallow convection in the Northern Hemisphere midlatitudes reduces SH jet shift in a warmer climate in accordance to the correlation between jet positions and shift seen in this season. These results can help explain intermodel differences in the position and shift of the jet, and point to an unexpected role for atmospheric moist convection in the midlatitude circulation

Characterizing Convection Schemes Using Their Responses to Imposed Tendency Perturbations

Convection is usually parameterized in global climate models, and there are often large discrepancies between results obtained with different convection schemes. Conventional methods of comparing convection schemes using observational cases or directly in three-dimensional (3D) models do not always clearly identify parameterization strengths and weaknesses. In this paper we evaluate the response of parameterizations to various perturbations rather than their behavior under particular strong forcing. We use the linear response function method proposed by Kuang (2010) to compare 12 physical packages in five atmospheric models using single-column model (SCM) simulations under idealized radiative-convective equilibrium conditions. The models are forced with anomalous temperature and moisture tendencies. The temperature and moisture departures from equilibrium are compared with published results from a cloud-resolving model (CRM). Results show that the procedure is capable of isolating the behavior of a convection scheme from other physics schemes. We identify areas of agreement but also substantial differences between convection schemes, some of which can be related to scheme design. Some aspects of the model linear responses are related to their RCE profiles (the relative humidity profile in particular), while others constitute independent diagnostics. All the SCMs show irregularities or discontinuities in behavior that are likely related to threshold-related mechanisms used in the convection schemes, and which do not appear in the CRM. Our results highlight potential flaws in convection schemes and suggest possible new directions to explore for parameterization evaluation