一次南方大暴雨过程的数值模拟及其误差的敏感性诊断分析
DIAGNOSTIC INVESTIGATION OF SIMULATION ERRORS WITH THE GRAPES-MESO MODEL FOR A TORRENTIAL RAIN CASE
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摘要: 选用0.18度(约20 km)分辨率中尺度大气非静力模式GARPES-Meso对2005年5月31日-6月1日发生在湖南省的大暴雨过程进行了数值模拟和敏感性试验,并用探空、地面加密实况资料和客观分析场资料等对模拟结果进行细致的误差分析和诊断研究。结果表明:此次暴雨过程发生的大尺度环流背景、尤其是500 hPa环流形势及其变化过程的模拟与实况非常接近;模式对暴雨过程累积降水总分布特征、大降水的主要落区等的模拟能力亦较强。从天气过程的角度看,模式可以对降水短期预报提供有较好参考和指导价值的可用数值产品。当然。本次暴雨过程细节特征的模拟还存在着一定偏差,如:模拟降水出现过早、降水峰值模拟偏弱、低层风速模拟偏大、高空急流核风速模拟偏小等。诊断分析显示,引起这些模拟误差的原因并不相同。模拟降水出现过早,主要是由模式初值误差引起,而非模式本身原因。处于暴雨区的初始低层风场偏差,在有利的环流条件下,积分前几个小时内不断增长并向对流层低层的上部扩展,引起模式低层风场和水汽发生异常辐合,进而激发出模式降水。而模拟降水峰值显著偏弱的可能原因,一是暴雨发生前高空急流核细节特征的模拟出现偏差,影响了高空强辐散与低层强辐合的垂直耦合,导致暴雨区高空辐散和垂直运动的模拟呈现出一种明显偏弱的连锁反应;二是模式次网格尺度和网格尺度降水方案的协调性不够,对流调整和对流对格点尺度温湿场的反馈似乎还不够有效,影响了模式格点尺度产生凝结至雨的温湿条件,进而影响显式降水方案作用的发挥。上述两方面因素的不断相互作用,对模拟降水构成一种负反馈影响,最终导致模拟降水峰值显著偏弱。要提升中尺度模式定量降水预报能力,还需特别关注模式物理过程的描述和提高模式降水物理过程方案之间的协调性。Abstract: In this paper, the numerical simulation errors of the non-hydrostatic version GRAPES-Meso (Mesoscale of the Global and Regional Assimilation and Prediction System) at the resolution of 0.18°for a torrential rain case, which happened in May 31st to June 1st 2005 over Hunan province, are diagnosed and investigated by using the radiosondes, intensive surface observation and the operational global analysis data, and the sensitivity experimental results as well. It is shown that the GRAPES-Meso could reproduce quite well the main features of large-scale circulations, especially the 500-hpa circulation patterns and their evolutions, while the distribution of the accumulated 24h precipitation and the key locations of the torrential rainfall are captured reasonably well by the model. Seeing from the viewpoint of the synoptic scale, the model could provide valuable numerical guidance for short-range weather forecasting. However, errors exist in the simulation of the mesoscale features of the torrential rain and details of the relevant systems, for example, the simulated rainfall that is too earlier in model integration and remarkable underprediction of the peak value of rainfall rates over the heaviest rainfall region, the weakness of the upper jet simulation and the overprediction of the south-west wind in the lower troposphere etc. The investigation reveals that the sources of the simulation errors are different. The erroneous model rainfall in the earlier integration stage over the heaviest rainfall region is induced by the model initial condition errors of the wind field at about 925 hPa over the torrential rainfall region, where the errors grow rapidly and spread upward to about 600 hPa level within the few hours into the integration and result in abnormal convergence of the wind and moisture, and thus the unreal rainfall over that region. The large bias on the simulated rainfall intensity over the heaviest rainfall region might be imputed to the following combined factors of (1) the simulation errors on the strength and detailed structures of the upper-level jet core which bring about significant underpredictions of the dynamic conditions (including upper-level divergence and the upward motion) for heavy rainfall due to unfavorable mesoscale vertical coupling between the strong upper-level divergence and lower-level convergence; and (2) the inefficient coupling of the cumulous parameterization scheme and the explicit moisture in the integration, which causes the failure of the explicit moisture scheme in generating grid-scale rainfall in a certain extent through inadequate convective adjustment and feedback to the grid-scale. In addition, the interaction of the combined two factors could form a negative feedback to the rainfall intensity simulation, and eventually lead to the obvious underprediction of the rainfall rate.
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Key words:
- GRAPES-Meso /
- torrential rainfall simulation /
- error diagnosis
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