基于对流尺度集合预报方法对一次暴雨过程预报的分析

对流尺度集合预报(Convection-allowing Ensemble Prediction，CAEP)是提高强对流天气预报能力的重要手段，构造合理的初始扰动是CAEP的关键问题。本文开展基于观测扰动初值法(Perturbed-observation，PO)的CAEP在内蒙古地区的试验，并以动力降尺度(Downscaling，DOWN)方法作为对比，分析PO方法在内蒙古地区CAEP的预报效果，以期为内蒙古地区CAEP的构建提供技术参考。结果表明：(1) PO方法构造的初始扰动能引入内蒙古地区观测资料从而减少背景场的不确定性，且扰动具有充分的增长能力。(2) 与DOWN方法相比，PO方法可以显著减少CAEP的短时预报误差，高空和地面要素的RMSE分别减小4%~43%和3%~9%，集合离散度略有减少。高空要素的CRPS评分最大可减少约53%，地面要素的CRPS评分平均减少6%，整体提高了对流尺度集合预报质量。(3) PO方法能够提高短时降水的预报能力，0.1 mm、4 mm和13 mm 3个量级的TS评分分别提升了0.015、0.003和0.001 5。且降水个例表明，PO方法对降水的落区和量级预报更准确。

Analysis of the forecast performance of a rainstorm process based on a convective scale ensemble prediction system

Convection-allowing ensemble prediction (CAEP) is an important approach to improve the capability of strong convective weather prediction, and how to construct reasonable initial disturbance is one of the key issues of CAEP. In this paper, the experiments of the per⁃ turbed-observation (PO) method in the CAEP system in the Inner Mongolia region were carried out and evaluated by comparing them with the downscaling (DOWN) method. The performance of the PO method in the CAEP system was then analyzed, which will provide a technical ref⁃ erence for the construction of the CAEP system in Inner Mongolia. The results are as follows. (1) The initial perturbation constructed by the PO method can effectively include the observations in the Inner Mongolia region, which can reduce the uncertainty of the background field and the perturbation has sufficient growth capacity. (2) Compared with the DOWN method, the PO method can significantly reduce the short-term forecast error of CAEP. The root mean square error (RMSE) of upper-level elements is reduced by 4% ~43%, and the RMSE of ground surface elements is reduced by 3% ~9%, suggesting a slightly decreased ensemble spread. The continuous ranked probability score (CRPS) of upper-level elements can be reduced by up to 53% and the CRPS of ground surface elements is reduced by an average of 6%, which generally indicates an improvement in the quality of convective scale ensemble forecasts. (3) The PO method can also improve the capability of short-term precipitation forecasts. The TS score for precipitation levels of 0.1 mm, 4 mm, and 13 mm increased by 0.015, 0.003, and 0.0015, re⁃ spectively. Furthermore, the case study shows that the PO method is more accurate in predicting the precipitation areas and intensity levels.