徐国强1, 赵晨阳2
Preliminary test and study on the application of satellite data to improve cloud computing process
(1.National Meteorological Center;2.Chinese Academy of Meteorological Sciences)
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投稿时间:2019-04-03    修订日期:2020-06-19
中文摘要: 利用GRAPES_Meso(Global/Regional Assimilation and Prediction System)模式对2018年5月5日一次西风槽降雨天气过程进行了数值模拟,对比分析了模式计算和卫星观测的相关云变量。结果指出,在GRAPES_Meso模式现用的云量计算方案中存在模拟的高云云量偏多、中低云密闭云区云量偏少,模式模拟的云顶温度明显偏低、云顶高度明显偏高的问题。针对模式云计算存在的问题,对云计算的原理和公式进行了解读,对计算公式进行了优化改进。采用改进的云计算方案后,高云云量偏多问题得到了明显改进;模式模拟的云顶温度明显偏低和云顶高度明显偏高问题也得到了极大缓解或优化改进。以卫星观测资料为基础对云量计算方案的优化进行的初步探索和试验,为研究和优化云计算方案提供了一种新的手段和方法。
Abstract:The GRAPES_Meso model was used to simulate the rainfall process of the westerly trough on May 5, 2018.The relevant cloud variables of model calculation and satellite observation were compared and analyzed. The results show that in the current cloud computing scheme of GRAPES_Meso model, there are excessive high cloud cover in some places and deficit cloud cover in the medium and low level dense closed cloud region. The cloud top temperature simulated by GRAPES_Meso model is obviously lower and the cloud top height is obviously higher. To address these issues, the principles and formulas of the cloud computing scheme are interpreted, and the calculation formula is optimized. After adopting the improved cloud computing scheme, the excessive high cloud cover has been greatly alleviated. Low cloud top temperature and high cloud top height has been greatly optimized.Based on satellite observation data, the preliminary exploration and test on the optimization of cloud computing scheme provides a new means and method for researching and optimizing cloud computing scheme.
文章编号:201904030138     中图分类号:    文献标志码:
徐国强,赵晨阳,0.[en_title][J].Meteor Mon,():-.
XU GUOQIANG,ZHAO Chenyang,0.Preliminary test and study on the application of satellite data to improve cloud computing process[J].Meteor Mon,():-.