Optimization and Evaluation of Stochastic Unified Convection Using Single‐Column Model Simulations at Multiple Observation Sites

Abstract

Abstract We extend the previously developed stochastic unified convection scheme (UNICON) for shallow convection to deep convection by parameterizing the impact of mesoscale organized flow on updraft properties. The extended stochastic UNICON parameterizes thermodynamic properties of updrafts at the near‐surface as a multivariate Gaussian distribution, where the variances of the distribution are the summation of variances from non‐organized turbulence and mesoscale organized flow. The distribution of updraft radius is parameterized as a power‐law distribution with a scale break which is parameterized as a linear function of the strength of mesoscale organized flow. The proposed parameterization is validated using a series of large‐eddy simulations of deep convection. The free parameters introduced in the formulation of stochastic UNICON are optimized using 10 cases of single‐column model simulations over the ocean. Stochastic UNICON with the optimized parameters significantly reduces the biases of thermodynamic profiles and surface precipitation rates simulated in the original UNICON for tropical convection cases. The simulation of the variation in anomalies of temperature and moisture associated with the Madden‐Julian oscillation is also improved. The overall improvements in simulated thermodynamic profiles are found to be due to the increased heating and drying tendencies by convective processes in stochastic UNICON. An additional simulation of an idealized deep convection case shows that stochastic UNICON produces enhanced cloud variabilities with dependency on updraft radius, indicating its ability to represent the coexistence of shallow and deep convection.

Keywords

• convection parameterization
• single‐column model
• optimization
• stochastic parameterization
• Madden‐Julian oscillation