Characterizing Convection Schemes Using Their Responses to Imposed Tendency Perturbations. (4th May 2021) - Hwong, Y. L.; Song, S.; Sherwood, S. C.; Stirling, A. J.; Rio, C.; Roehrig, R.; Daleu, C. L.; Plant, R. S.; Fuchs, D.; Maher, P.; Touzé‐Peiffer, L.
Abstract: 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. Plain Language Summary: The transport of heat up and down the atmosphere, called atmospheric convection, is a complex process. To simplify the representation of convection in global climate models (GCMs) scientists use "parameterization, " which is essentially mathematical equations of physical processes. However, there are many different ways to formulate these equations, and no agreement on which is better. In this work we aim to understand a few popular ways to parameterize convection. We extract one vertical column from five different GCMs and lightly tickle (perturb) it and then observe its responses. We found that different models respond very differently to the same tickling, and this tells us a lot about the model. Importantly, the specific perturbation that we used can single out the responses of convection‐related equations from equations of other processes. All the models in our study have one thing in common: They are quite jumpy when tickled, especially at the top of the boundary layer where clouds start to form. We suspect the culprits are thresholds placed in the models that sometimes lead to sudden changes in their response. Our work highlights potentially problematic behavior that can give clues on how to make climate models better. Key Points: The linear response function method is applied in single‐column model (SCM) simulations and is able to isolate the behavior of convection schemes Linear responses of the models are related to the mean state relative humidity in both shape and magnitude All SCMs show discontinuities in their responses which are likely related to thresholds used in convective parameterization