摘要
基于增长模繁殖法(BGM)思想,采用AREM(新一代区域η坐标模式),研究了暴雨过程中,初始随机扰动在繁殖循环中随时间的演变特征和发展机理。结果表明,初始扰动的演变决定于环流背景场的结构和大气中的湿物理过程。背景场不仅影响扰动的演变规律,而且决定了扰动发展的敏感区域。初始扰动随时间演变存在两个敏感区,一是背景场的大风速区,二是降水区附近。对流层高层,大风速区附近扰动得到最优发展;对流层中低层,扰动不仅沿大风速区发展,且与降水区配合较好。初始扰动发展的机理也有两种,一是大气湿物理过程引起的位势不稳定或第二类条件不稳定(CISK);二是由风切变引起的大气动力不稳定。高层扰动的增长,以干大气的动力不稳定占优,中低层扰动的发展主要是湿物理过程的贡献,初始扰动在模式中的发展与降水的发展是同"源"的,有利于降水发展的环境也有利于初始扰动的发展,从而影响了降水的可预报性。所以利用暴雨预报模式制作集合预报时,BGM仍是可用的方法。
Based on the concept of breeding growth modes, the evolvement characteristics of initial random errors and error growth mechanisms in precipitation prediction are studied by using the meso-scale numerical model of AREM. The results indicate that the evolvement of initial errors and error growth are dependent on the distribution of the basic flow pattern and moist physics. The basic flow can not only influence the error evolvement but also determine the sensitive area of error growth. Significant error growth exists in two sensitive areas. One is in the vicinity of a strong wind region and the other is near the rain belt. In the high troposphere, the initial errors grow significantly along the strong wind region while in the low and mid troposphere, the error growth happens near both the strong wind region and precipitation area. Two error growth mechanisms are the moist process（possibly related to geo-potential instability or convective instability）, which affects the error evolvement in low and mid troposphere, and the dynamic instability associated with wind shear, which decides the growth of perturbations in the high troposphere. It is concluded that the error growth and precipitation development have the same ＂energy source＂. This conclusion indicates that the basic flow which benefits the precipitation will also make initial errors grow significantly and thus lead to limited predictability. In addition, BGM is still useful in making ensemble forecast that involves with the precipitation prediction model.
出处
《热带气象学报》
CSCD
北大核心
2009年第5期571-575,共5页
Journal of Tropical Meteorology
基金
国家重点基础研究项目"我国南方致洪暴雨监测与预测的理论和方法研究"(2004CB418304)资助
关键词
BGM
集合预报
初始扰动
发展机理
数值模式
BGM
ensemble forecast
initial error
error growth mechanism
numerical model
