Aircraft Observations of Turbulence in Cloudy and Cloud‐Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development. Issue 19 (28th September 2022) - Brunke, Michael A.; Cutler, Lauren; Urzua, Rodrigo Delgado; Corral, Andrea F.; Crosbie, Ewan; Hair, Johnathan; Hostetler, Chris; Kirschler, Simon; Larson, Vincent; Li, Xiang‐Yu; Ma, Po‐Lun; Minke, Annalisa; et al.
Abstract: This study examines boundary layer turbulence derived from high temporal resolution meteorological measurements from 40 research flights over the western North Atlantic Ocean during the 2020 deployments of ACTIVATE. Frequency distributions of various turbulent quantities reveal stronger turbulence during the winter deployment than in summer and for cloud‐topped than in cloud‐free boundary layers during the summer deployment. Maximum turbulence kinetic energy (TKE) is most often within cloud from observations in winter and summer, whereas it is mostly below cloud in both seasons by a global model turbulence parameterization. Bivariate frequency distributions are consistent with the bivariate Gaussian probability distribution functions assumed for the closure of higher‐order turbulence/shallow convection parameterizations used by some global models. Turbulence simulated by the Community Atmosphere Model version 6 and the Energy Exascale Earth System Model Atmosphere Model version 2 using such parameterizations is not as strong as observed, with more TKE going into vertical wind perturbations rather than into zonal wind perturbations as observed, suggesting that the treatment of turbulence in Earth system models still needs to be further improved. Key Points: Maximum turbulence kinetic energy is most often within cloud in observations but mostly below cloud by a global model parameterization Observations are similar to bivariate normal probability distribution functions assumed to close higher‐order turbulence parameterizations Boundary layer turbulence simulated by global models is weaker than observed