Evaluation of double-moment representation of ice hydrometeors in bulk microphysical parameterization: comparison between WRF numerical simulations and UND-Citation data during MC3E

Zhaoxia Pu,Chao Lin

doi:10.1186/s40562-015-0028-x

Abstract

The influence of double-moment representation of warm-rain and ice hydrometeors on the numerical simulations of a mesoscale convective system (MCS) over the US Southern Great Plains has been evaluated. The Weather Research and Forecasting (WRF) model is used to simulate the MCS with three different microphysical schemes, including the WRF single-moment 6-class (WSM6), WRF double-moment 6-class (WDM6), and Morrison double-moment (MORR) schemes. It is found that the double-moment schemes outperform the single-moment schemes in terms of the simulated structure, life cycle, cloud coverage, precipitation, and microphysical properties of the MCS. However, compared with UND-Citation observations, collected during the Midlatitude Continental Convective Clouds Experiment (MC3E), the WRF simulated ice hydrometeors with all three schemes do not agree well with the observations. Overall results from this study suggest that uncertainty in microphysical schemes could still be a productive area of future research from perspective of both model improvements and observations.

Highlights

Microphysical parameterization (MP) is an important source of uncertainty in the numerical prediction of mesoscale convective systems (MCSs) (Randall et al 2003)
Since a major difference between the partial and full 2M schemes is the representation of ice species, and it is well known that the uncertainty in microphysics parameterizations arises mainly from the treatment of ice processes, the important question to ask is: are the full 2M treatments of ice hydrometeors
The results suggest that 2M representations of ice hydrometeors in Morrison MP scheme help the Weather Research and Forecasting (WRF) model to reproduce a better forecast of MCS but does not seem to produce the realistic ice properties

Summary

Introduction

Microphysical parameterization (MP) is an important source of uncertainty in the numerical prediction of mesoscale convective systems (MCSs) (Randall et al 2003). Among these data collected during the field campaign, the University of North Dakota Citation (UND-Citation) dataset provides measurements of hydrometeor distributions with hydrometeor properties, such as ice particle number concentration in specific diameter bins and ice water content inferred from the particle distributions.

Results

Conclusion