Comparison of microphysics parameterization schemes on cloud macrophysics forecasts for mixed convective-stratiform cloud events

Abstract

In this study, the performances and uncertainties of cloud microphysics parameterization (MP) schemes for simulating cloud macrophysics associated with mixed convective-stratiform cloud (MCSC) events are investigated. MCSC system is the primary object of cloud seeding for the purpose of rain enhancement in North China. Understanding the forecast uncertainties of cloud macrophysics, such as cloud top temperature (CTT), cloud base height (CBH), and cloud optical thickness (COT), is of great significance for cloud seeding operations. Simulations of cloud macrophysics are verified using cloud data retrieved from the Feng-Yun-2F geostationary meteorological satellite, radiosondes and Moderate Resolution Imaging Spectroradiometer (MODIS) products. The performances of several MP schemes to accurately simulate cloud macrophysics within ensemble forecasts is explored using both grid-wise and object-based metrics. Large differences are found among schemes in simulated cloud macrophysics compared with similar performances in simulated precipitation. In most cases, the ensemble mean simulates more realistically than each single scheme. The ensemble spread varies somewhat according to the simulated variables. For CBH, the ensemble shows adequate ensemble spread, while relative underdispersion occurs for CTT and COT. Detailed COT comparisons of reveal that COT bias mainly comes from the contribution of cloud droplets and snow. The causes of COT bias are further investigated by a detailed comparison of the cloud water path (CWP) and cloud effective radius (EFFR). The study establishes a baseline for ensemble forecasting of cloud macrophysics.