Empirical values and assumptions in the convection schemes of numerical models

Abstract

Convection influences climate and weather events over a wide range of spatial and temporal scales. Therefore, accurate predictions of the time and location of convection and its development into severe weather are of great importance. Convection has to be parameterized in global climate models and Earth system models as the key physical processes occur at scales much lower than the model grid size. This parameterization is also used in some numerical weather prediction (NWP) models when convection is not explicitly resolved. The convection schemes described in the literature represent the physics by simplified models that require assumptions about the processes and the use of a number of parameters based on empirical values. These empirical values and assumptions are rarely discussed in the literature. The present paper examines these choices and their impacts on model outputs and emphasizes the importance of observations to improve our current understanding of the physics of convection. The focus is mainly on the empirical values and assumptions used in the activation of convection (trigger), the transport and microphysics (commonly referred to as the cloud model), and the intensity of convection (closure). Such information can assist satellite missions focused on elucidating convective processes (e.g., the INCUS mission) and the evaluation of model output uncertainties due to spatial and temporal variability of the empirical values embedded into the parameterizations.