Variability and Clustering of Midlatitude Summertime Convection: Testing the Craig and Cohen Theory in a Convection-Permitting Ensemble with Stochastic Boundary Layer Perturbations

Abstract

The statistical theory of convective variability developed by Craig and Cohen in 2006 has provided a promising foundation for the design of stochastic parameterizations. The simplifying assumptions of this theory, however, were made with tropical equilibrium convection in mind. This study investigates the predictions of the statistical theory in real-weather case studies of nonequilibrium summertime convection over land. For this purpose, a convection-permitting ensemble is used in which all members share the same large-scale weather conditions but the convection is displaced using stochastic boundary layer perturbations. The results show that the standard deviation of the domain-integrated mass flux is proportional to the square root of its mean over a wide range of scales. This confirms the general applicability and scale adaptivity of the Craig and Cohen theory for complex weather. However, clouds tend to cluster on scales of around 100 km, particularly in the morning and evening. This strongly impacts the theoretical predictions of the variability, which does not include clustering. Furthermore, the mass flux per cloud closely follows an exponential distribution if all clouds are considered together and if overlapping cloud objects are separated. The nonseparated cloud mass flux distribution resembles a power law. These findings support the use of the theory for stochastic parameterizations but also highlight areas for improvement.

Relative contribution of soil moisture, boundary‐layer and microphysical perturbations on convective predictability in different weather regimes

“…The simulated diurnal cycle matches reasonably well with radar observations (EY product of DWD; details in Rasp et al . ), peaks at 1600 UTC, reveals a slight time shift of 2 hr too early (1 hr too late), and attains domain‐averaged intensities of 0.48 mm/hr (0.29 mm/hr) for strong (weak) forcing, respectively. Our experiments using the double‐moment microphysics scheme and driven with analysis data predict slightly more precipitation than the operational model, comparing better with domain‐averaged radar observations (Figure a,c).…”

“…An updated PSP description can be found in the appendix of Rasp et al . (). The basic motivation follows from the notion that convective triggering in situations of weak synoptic forcing depends crucially on boundary‐layer turbulence.…”

“…To test the impact of boundary-layer perturbations, we applied the physically based PSP scheme for boundary-layer turbulence (Kober and Craig, 2016). An updated PSP description can be found in the appendix of Rasp et al (2018). The basic motivation follows from the notion that convective triggering in situations of weak synoptic forcing depends crucially on boundary-layer turbulence.…”

“…Large parts of Europe were influenced by atmospheric blocking over almost two weeks at the end of May and the beginning of June 2016. Low thermal stability and low mid-tropospheric wind speed provided a convection-favouring weather situation that led to locally extreme rain accumulations of more than 100 mm/day (Piper et al, 2016;Rasp et al, 2018;Zeng et al, 2018 give detailed descriptions of the synoptic situation). From 29 May to 3 June an upper-level trough was responsible for synoptic lifting, whereas from 4 to 7 June the synoptic forcing was weak and precipitation was mostly triggered by local non-equilibrium convection across Germany.…”

“…These subgrid processes include, for instance, boundary-layer turbulence. The physically based stochastic perturbation scheme PSP is designed to re-introduce these missing effects in a physically consistent manner (Kober and Craig, 2016;Rasp et al, 2018). The aim of the PSP scheme is to improve the coupling between subgrid variability and convection initiation in km-scale models.…”