Do we need cloud microphysics parameterization to simulate convection?

 

Authors

Peter J. Lamb — University of Oklahoma
Zewdu Tessema Segele — CIMMS/University of Oklahoma
Lance Leslie — Ohio University

Category

Modeling

Description

Contributions (%) of individual hydrometeor species to total simulated cloud radar (Ka-band) reflectivity for eight WRF microphysics CNTRL simulations at five representative altitudes (1, 3, 5, 7, and 9 km) for May 27–31, 2001. For Eta microphysics, snow and ice are not differentiated. WRF single/double-moment five-category scheme (WSM5/WDM5) provides explicit treatment of cloud water, rain water, snow, and ice species. Lin, WSM6, WDM6, Goddard, and Thompson microphysics schemes predict the additional graupel species. Black, green, and red arrows at top indicate the timing of three organized convective storms that passed over the SGP CF.
This study evaluates the ability of the Weather Research and Forecasting model to reproduce the observed cloud and convection characteristics in the vicinity of the Southern Great Plains Central Facility (SGP CF). Eight microphysics simulations were conducted for the warm season heavy precipitation case of May 27–31, 2001. For validation, we used cloud observations at the ARM Facility and the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity data over the SGP. The timing of convection and vertical structure of the microphysical properties of simulated storms were assessed by analyzing the contributions of individual water species to total simulated cloud radar (Ka-band) reflectivity . All microphysics schemes produced ice that accounted for much of the simulated cloud radar reflectivity, but simulated cloud water and rain are much less frequent and less abundant. Importantly, there is a vertical misalignment in the production of frozen water in the upper troposphere and liquid water in the lower troposphere at the time of observed deep convection. This misalignment is the main reason for the inability of the model to reproduce the observed large precipitation rate at the SGP CF. To correct this model deficiency, a simulation was performed without activating any microphysics scheme. From this no-microphysics simulation, the large-scale convection was estimated from the 900–400 hPa layer average of the product of grid-scale ascending velocity and grid-scale water vapor mass deficit. The maximum radar reflectivity (mm6 m-3) was estimated using the WSR-88D radar-precipitation rate empirical formula. An EOF analysis was then performed on the resulting reflectivity field for the entire innermost simulation domain. Inspection of the simulated (no microphysics) and observed (WSR-88D) EOF1 modes shows improvements in the simulation of large-scale convection compared to the results of microphysics-enabled simulations. In particular, the dynamically estimated reflectivity for the no-microphysics simulation reproduced reasonably well the observed large-scale convection in the innermost domain, especially the most dominant first and third convection events that all microphysics-enabled experiments failed to simulate. The correlation between the EOF1 score time series of simulated and WSR-88D composite reflectivity is +0.54, which is a significant improvement compared to the near-zero correlations for the eight microphysics CNTRL simulations.