首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Modeling convective-stratiform precipitation processes on a Mei-Yu front with the Weather Research and Forecasting model: Comparison with observations and sensitivity to cloud microphysics parameterizations
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Modeling convective-stratiform precipitation processes on a Mei-Yu front with the Weather Research and Forecasting model: Comparison with observations and sensitivity to cloud microphysics parameterizations

机译:使用气象研究和预报模型对梅雨锋对流层状降水过程进行建模:与观测值的比较以及对云微物理参数化的敏感性

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Deep convective-scale simulations of the linear mesoscale convective systems (MCSs) formed on a Mei-Yu front over the Huai River basin in China on 7-8 July 2007 were conducted using the Advanced Research Weather Research and Forecasting model to investigate impacts of cloud microphysics parameterizations on simulated convective-stratiform precipitation processes. Eight simulations were performed with identical configurations, except for differences in the cloud microphysics parameterizations. Measurements from rain gauges, ground-based weather radars, and the Tropical Rainfall Measuring Mission satellite Precipitation Radar were used to quantitatively evaluate the model results. While all of the simulations largely capture the observed large-scale characteristics of the precipitation event, notable differences among the simulations are found in the morphology and evolution of the MCSs at mesoscale and cloud scale. Significant influences on the coupling between dynamical and microphysical processes at the resolved deep convective scale by the various microphysical parameterizations are evident. On the one hand, the different microphysical schemes produce not only substantial differences in intensity of convective precipitation but also distinguishable vertical distributions of latent heating and condensate loading in the deep convective regions, which in turn results in significant differences in the vertical distributions of vertical air velocity and in the heights and strength of detrainment from deep convective regions. Consequently, detainment of hydrometeors and positively buoyant air from the deep convective regions to the stratiform regions is significantly different, which impacts the formation and growth of ice-phase hydrometeors at the upper levels and thus surface rainfall rates in the stratiform regions. On the other hand, prediction of rain size distribution significantly impacts the simulated rain evaporation rates and mass-weighted rain fall speeds, and hence rain flux. Improper determination of the intercept parameter of rain size distribution can result in unrealistic features in the morphology of the storm and can have substantial impacts on precipitation distribution and evolution.
机译:利用高级研究天气研究和预报模型,对2007年7月7日至8日在中国淮河流域梅雨锋上形成的线性中尺度对流系统(MCS)进行了深对流尺度模拟,以研究云的影响对流层状降水过程的微观物理参数化。除了云微物理学参数设置的差异外,使用相同的配置执行了八次仿真。来自雨量计,地面气象雷达和热带降雨测量任务卫星降水雷达的测量被用来定量评估模型结果。尽管所有模拟都充分捕捉到了观测到的降水事件的大规模特征,但在中尺度和云尺度下,MCS的形态和演化却发现了显着的差异。明显的是,各种微物理参数化对解析的深对流尺度上的动力学过程和微物理过程之间的耦合产生了重大影响。一方面,不同的微物理方案不仅在对流降水强度上产生实质性差异,而且在深对流区域内潜热和凝结水负荷的垂直分布也明显不同,从而导致垂直空气垂直分布的显着差异速度,以及来自深对流区域的减摩高度和强度。因此,从深对流区到层状区的水凝物和正浮力空气的截留是明显不同的,这影响了高层冰相水凝物的形成和生长,从而影响了层状区的表面降雨率。另一方面,降雨大小分布的预测会显着影响模拟的降雨蒸发速率和质量加权的降雨速度,进而影响降雨通量。雨量分布的截距参数的不正确确定可能导致风暴形态的特征不切实际,并且可能对降水量的分布和演变产生重大影响。

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