New Parameterization Will Help Improve Convection in Global Models
New approach uses relationships between vertical motions and precipitation amount to improve small-scale vertical transport in models.
Vertical motions in the atmosphere are the primary drivers for cloud and precipitation formation, and they play an important role in redistributing condensed water in the vertical column. This vertical transport is difficult to represent in climate models because it happens primarily at scales smaller than a typical model grid size. To lessen the problem, a pair of researchers, including one at the U.S. Department of Energy’s Pacific Northwest National Laboratory, developed a new approach for computing the vertical fluxes of hydrometeors (e.g., rain, graupel, snow, ice) based on statistical relationships between cloud and precipitation properties and vertical motions.
Vertical transport of hydrometeors from the new representation closely matches the benchmark, high-resolution simulation. The new modeling approach will help improve the representation of convection in global models.
Researchers developed a new parameterization to represent the vertical transport of hydrometeors in global models and validated it with benchmark, high-resolution numerical simulations of continental and tropical convection driven by ARM observations. Scientists developed this approach by using probability density functions (PDFs) to treat subgrid-scale variability in coarse-resolution models. The new hydrometeor transport representation conditionally samples PDFs of vertical velocity and condensate amounts, and then scales the distributions to account for different correlations in regions of strong and weak vertical motions. The represented transport fluxes—tested for four episodes of deep convection—agreed well with benchmark fluxes computed directly from the cloud-resolving model output. The results demonstrated the potential use of the subgrid-scale hydrometeor transport formulation in an assumed PDF to represent the co-variances of vertical velocity and hydrometeor mixing ratios.
Pacific Northwest National Laboratory
The U.S. Department of Energy (DOE) Office of Science, Biological and Environmental Research supported this research as part of the Atmospheric System Research program. The National Energy Research Scientific Computing Center provided computing resources for the simulations. Data were obtained from the Atmospheric Radiation Measurement (ARM) Climate Research Facility, a DOE Office of Science user facility sponsored by the Office of Biological and Environmental Research.
M. Wong and M. Ovchinnikov, “A PDF-Based Parameterization of Subgrid-Scale Hydrometeor Transport in Deep Convection.” Journal of the Atmospheric Sciences 74, 1293-1309 (2017). [DOI: 10.1175/JAS-D-16-0146.1]