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马雅楠, 陈静, 徐致真, 等. 2023. GRAPES对流尺度集合预报模式中不同尺度初始扰动能量的演变特征[J]. 大气科学, 47(5): 1541−1556. doi: 10.3878/j.issn.1006-9895.2202.21242
引用本文: 马雅楠, 陈静, 徐致真, 等. 2023. GRAPES对流尺度集合预报模式中不同尺度初始扰动能量的演变特征[J]. 大气科学, 47(5): 1541−1556. doi: 10.3878/j.issn.1006-9895.2202.21242
MA Yanan, CHEN Jing, XU Zhizhen, et al. 2023. Evolution Characteristics of Initial Perturbation Energy at Different Scales in Convection-Permitting Ensemble Prediction of GRAPES [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(5): 1541−1556. doi: 10.3878/j.issn.1006-9895.2202.21242
Citation: MA Yanan, CHEN Jing, XU Zhizhen, et al. 2023. Evolution Characteristics of Initial Perturbation Energy at Different Scales in Convection-Permitting Ensemble Prediction of GRAPES [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(5): 1541−1556. doi: 10.3878/j.issn.1006-9895.2202.21242

GRAPES对流尺度集合预报模式中不同尺度初始扰动能量的演变特征

Evolution Characteristics of Initial Perturbation Energy at Different Scales in Convection-Permitting Ensemble Prediction of GRAPES

  • 摘要: 对流尺度数值预报对初始场的微小扰动非常敏感,且初始扰动的演变具有模式依赖、环流依赖和尺度依赖特征,如何构建合理的初始扰动场是国内外对流尺度集合预报领域尚未解决的难点问题和研究前沿。本文基于中国气象局3 km水平分辨率的GRAPES(Global/Regional Assimilation and Prediction Enhanced System)对流尺度模式,利用其同化分析系统的背景误差和一个二维随机型,构建大、中、小三个尺度的初始扰动场,并选取中国夏季一次典型的多区域强降水天气个例,开展对流尺度集合预报试验,对比分析了大、中、小尺度初始扰动能量的时空演变和谱分解特征,以期为构建适用于GRAPES对流尺度集合预报的初始扰动场提供依据。研究结果表明,在GRAPES 3 km对流尺度模式中:(1)大、中、小尺度初始扰动总能量的增长过程具有明显差异。大尺度初始扰动总能量随着模式积分呈增长趋势,尤以对流层中高层的持续增长为甚;而中、小尺度初始扰动总能量随着模式积分以日变化为主,表现为下午至傍晚(夜晚至清晨),扰动总能量显著增加(减小),且扰动总能量小尺度分量的日变化占主导,这可能是由于太阳辐射引起地表加热,使得白天的对流活动比夜晚活跃,且对流直接影响了扰动总能量小尺度分量的变化。此外,大、中、小尺度初始扰动总能量增长均以扰动动能增长为主,扰动位能在对流层低层的增长不可忽略。(2)大、中、小尺度初始扰动总能量增长具有环流依赖特征。对北支气流控制的中高纬天气区,在斜压不稳定较强的低槽区,大尺度初始扰动总能量增长突出,而在槽后西北气流区,大、中、小尺度初始扰动总能量均不增长;对南北气流交汇区,仍以大尺度初始扰动总能量增长最为明显;对南海夏季风影响区,大、中、小尺度初始扰动总能量发展均较弱,扰动位能增长与区域降水大值率演变有较好的对应关系。(3)大、中、小尺度初始扰动总能量的谱分析结果显示,不同积分时段扰动总能量的多尺度串级特征有差异。积分前3 h主要为扰动总能量的大尺度分量向小尺度分量降尺度串级,积分6 h后则为中、小尺度分量的升尺度串级。上述研究结果表明,在天气系统复杂、动力不稳定时空分布不均匀的区域(如中国区域)发展对流尺度集合预报时,有必要针对不同的不稳定天气区,构建具有尺度依赖和环流依赖的初始扰动结构。

     

    Abstract: Convective-scale numerical weather prediction is sensitive to minor IPs (initial perturbations), and the evolution of these perturbations is model-, flow-, and scale-dependent. Constructing reasonable IPs for convection-permitting ensemble prediction systems has always been challenging. The authors use GRAPES (Global/Regional Assimilation and Prediction System) 3-km convective-scale model from the Center for Earth System Modeling and Prediction of the China Meteorological Administration. The authors employ a two-dimensional random function and background error of assimilation system in GRAPES 3-km to construct large-, meso-, and small-scale stochastic initial perturbation fields. Using these different-scale IPs, the authors conduct three convective-scale ensemble forecast experiments on a typical multiregional heavy precipitation weather process during summer in China. The authors analyze the spatiotemporal evolution and spectral decomposition characteristics of perturbation energy in these three experiments to elucidate the evolution characteristics of different-scale initial perturbations in a convective-scale model. This analysis provides a reference for constructing optimal initial perturbations in GRAPES convection-permitting ensemble prediction systems. The results reveal the following: (1) There are significant differences in the evolution of DTE (difference total energy) among the three IP experiments. The DTE of the large-scale IP increases with model integration, particularly in the middle and upper troposphere. However, the DTE evolution of the meso- and small-scale IP experiments exhibits an apparent diurnal cycle characteristic. In particularly, it exhibits a significant increase (decrease) during the period ranging from afternoon to evening (from night to morning) when convection is active (passive). The diurnal cycle is primarily caused by the small-scale component of DTE. The diurnal cycle of DTE may be due to the surface heating caused by solar short-wave radiation, which facilitates more active convection during the daytime than at night, and the convection directly affects the small-scale component of the DTE. In addition, the DTE of three IP experiments increases primarily due to the development of DKE (difference kinetic energy), whereas DPE (difference potential energy) cannot be neglected in the lower troposphere. (2) The DTE evolution of the large-, meso-, and small-scale IP experiments is flow dependent. In the mid-high latitudes, the increase in DTE for the large-scale IPs is dominant in regions with strong baroclinic instability (e.g., trough regions), whereas it does not develop in regions with relatively weak baroclinic instability (e.g., the northwest flow behind troughs). In the confluence region of north and south airflows, the DTE increases for the large-scale IPs are still dominant. However, the DTE of all three IP experiments hardly develops in the region affected by the South China Sea summer monsoon. A consistent relationship exists between the development of DPE and the ratio of large precipitation rates in this region. (3) The DTE spectrum reveals that the multiscale cascade characteristics of DTE change with integration periods. The downscaling cascade of DTE from the large-scale to the small-scale component is strong during the initial 3 h. However, for lead times after 6 h, the upscale growth of DTE from meso- and small-scale components becomes the main characteristic of the DTE spectrum. In conclusion, it is necessary to construct a scale-dependent and flow-dependent initial perturbation structure for different unstable weather regions, particularly when building convection-permitting ensemble predictions in regions with complex weather systems and nonuniform spatiotemporal distribution of dynamic instability, such as China.

     

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