GRAPES全球模式次网格对流过程对云预报的影响研究

Influences of sub-grid convective processes on cloud forecast in the GRAPES global model

50 km分辨率下的GRAPES全球模式对赤道及低纬度地区云水、云冰、云量和格点降水的预报较实际观测偏少。为解决这一问题,在模式原有的格点尺度云方案基础上,将次网格对流过程的影响作为源汇项,加入到云水、云冰和总云量的预报方程中。结合云和地球辐射能量系统(CERES)与热带降雨测量(TRMM)等卫星云观测资料,进行了改进后的云方案与原云方案预报结果的对比分析。结果显示,考虑了对流对格点尺度云含水量和云量预报的影响后,GRAPES全球模式预报的云和格点降水在赤道及低纬度地区有明显改善,水凝物含水量和总云量的预报结果与实况较为接近,格点降水在总降水中的比例由原来的5%提高到25%。研究进一步表明,次网格对流过程对格点尺度云和降水的影响取决于上升气流质量通量的分布和强度,上升气流的质量通量在对流活动强烈的低纬度热带地区较强,其最大值出现在650—450 hPa高度,因此,次网格对流的卷出过程对中云的影响最为明显。对高云和低云也有一定程度的影响,使云顶变高,云底变低。

The purpose of the research is to improve the prediction of the hydrometeors water content, cloud fraction and grid precipitation by the Global/Regional Assimilation and Prediction System （GRAPES） global model at 50 km spatial resolution for the low latitudes and equatorial regions. This study adopts a new scheme that considers the impact of this sub-grid convective process by adding source-sink terms in the prediction equations of cloud water/ice and cloud fraction. Distinct forecast results from the previous cloud scheme are obtained. The forecasts of cloud and precipitation in the low latitudes and equatorial regions have been significantly improved after consideration of the effect of the sub-grid convective process. Moreover, compared with the observational data from the Clouds and the Earth＇s Radiant Energy System （CERES） and Tropical Rainfall Measuring Mission （TRMM）, it is confirmed that the forecasting capability of the GRAPES global model has been promoted especially for the cloud and precipitation in the tropics, with the proportion of grid-scale precipitation enhances from 5% to 25%. Further analysis reveals that the influence of the sub-scale convective process on gird-scale cloud and precipitation depends on the distribution and intensity of updraft mass flux, which are larger from the new scheme in the tropics, leading to notable increases of cloud and precipitation there. In addition, the maximum updraft mass flux resides in the 450-650 hPa layer, resulting in more pronounced improvement in forecast of middle-level clouds than high clouds and low-level clouds, and causes cloud top to rise with cloud bottom dropping downward.