October 1, 2020
Journal Article

Assessing CLUBB PDF closure assumptions for a continental shallow-to-deep convective transition case over multiple spatial scales

Abstract

Assumed-PDF (probability density function) higher-order turbulence closures (APHOCs) are now widely used for parameterizing boundary layer turbulence and shallow convection in Earth system models (ESMs). A better understanding of the resolution-dependent behavior of APHOCs is essential for improving the performance of next-generation ESMs with intended horizontal resolutions finer than 10 km. In this study, we evaluate the PDF family of Analytic Double Gaussian 1 implemented in Cloud Layers Unified By Binormals (CLUBB) over a range of spatial scales (Dx) from 2 to 100 km. A large-domain (120 km wide) Large Eddy Simulation (LES) for a continental convection case during 2016 HI-SCALE field campaign serves as the benchmark to evaluate the PDF closure using an offline approach. We found that the CLUBB PDF closure tends to underestimate the cloud base height at all analysis scales (or grid spacing) mainly because the parameterized moisture skewness in CLUBB is overestimated near cloud base. The CLUBB PDF closure also tends to underestimate clouds near shallow cloud top for large Dx partly because parameterized moisture skewness is too small towards cloud top. But supplying larger observed moisture skewness leads to unrealizable solutions and invokes clipping. Overall the performance of the PDF closure is better for smaller Dx = 2-5 km than for larger Dx = 50-100 km; for a given grid spacing, it is better when the convective clouds become deeper in the late afternoon. Likely causes for the resolution dependence and implications for improving the PDF closure are discussed.

Revised: November 5, 2020 | Published: October 1, 2020

Citation

Huang M., H. Xiao, M. Wang, and J.D. Fast. 2020. Assessing CLUBB PDF closure assumptions for a continental shallow-to-deep convective transition case over multiple spatial scales. Journal of Advances in Modeling Earth Systems 12, no. 10:e2020MS002145. PNNL-SA-152632. doi:10.1029/2020MS002145