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| 1 | Applying the WRF Double-Moment Six-Class Microphysics Scheme in the GRAPES_Meso Model: A Case Study显示文摘This study incorporated the Weather Research and Forecasting(WRF) model double-moment 6-class(WDM6) microphysics scheme into the mesoscale version of the Global/Regional Assimilation and Pr Ediction System(GRAPES_Meso). A rainfall event that occurred during 3–5 June 2015 around Beijing was simulated by using the WDM6, the WRF single-moment 6-class scheme(WSM6), and the NCEP 5-class scheme, respectively. The results show that both the distribution and magnitude of the rainfall simulated with WDM6 were more consistent with the observation. Compared with WDM6, WSM6 simulated larger cloud liquid water content, which provided more water vapor for graupel growth, leading to increased precipitation in the cold-rain processes. For areas with the warmrain processes, the sensitivity experiments using WDM6 showed that an increase in cloud condensation nuclei(CCN)number concentration led to enhanced CCN activation ratio and larger cloud droplet number concentration(Nc) but decreased cloud droplet effective diameter. The formation of more small-size cloud droplets resulted in a decrease in raindrop number concentration(Nr), inhibiting the warm-rain processes, thus gradually decreasing the amount of precipitation. For areas mainly with the cold-rain processes, the overall amount of precipitation increased; however, it gradually decreased when the CCN number concentration reached a certain magnitude. Hence, the effect of CCN number concentration on precipitation exhibits significant differences in different rainfall areas of the same precipitation event. | Meng ZHANG Hong WANG Xiaoye ZHANG Yue PENG Huizheng CHE | 2018 | Journal of Meteorological Research2018，32，2： | 3 |
| 2 | Ensemble-based diurnally varying background error covariances and their impact on short-term weather forecasting显示文摘背景场误差协方差在资料同化系统中具有非常重要的作用,目前业务变分同化系统中常采用静态背景场误差协方差,未考虑其具体的日变化特征.为构建更为合理且便于业务系统应用的日变化背景误差协方差,本文构建了高分辨率集合预报样本的日变化背景场误差协方差,揭示了其日变化特征,并应用到了CMA-BJ业务系统中,开展了基于业务框架的批量循环同化预报试验.结果表明,背景场误差存在明显的日变化特征,采用集合日变化背景场误差协方差能够改进模式的预报效果. | Shiwei Zheng Yaodeng Chen Xiang-Yu Huang Min Chen Xianya Chen Jing Huang | 2022 | Atmospheric and Oceanic Science Letters2022，15，6： | 0 |
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