Scale-aware modeling of the ABL and its impact on deep convection (SCALABLe)

Picture rights: J. Schmidli.

The accurate representation of the atmospheric boundary layer (ABL) and deep convection across scales in numerical weather prediction (NWP) is important for skillful and seamless forecasts of weather and climate. In the current project we propose to contribute to this overarching goal by studying the scale-aware representation of turbulence, clouds, shallow and deep convection for convective conditions over land and cloud-topped marine boundary layers with a focus on regime transitions. First, our stochastic shallow convection (SSC) scheme is to be further developed for transient ABLs and different levels of terrain complexity. Second, our unified assumed-distribution higher-order closure (AD-HOC) scheme is to be coupled to the SSC scheme and further developed for a better representation of explicit deep convection and orographic flows. These model developments will be guided by fundamental research on the relevant atmospheric processes using large-eddy simulation (LES) and observations from recent and future field campaigns (e.g., FESSTVaL, TEAMx) and are expected to lead to better predictions of local weather and high-impact weather events.