基于对流参数的西安机场雷暴潜势预报方法

Prediction of Thunderstorm Potential at Xi’an Airport Using Convective Parameters

摘要: 利用西安机场2019~2024年地面气象观测资料、每日08时和20时(北京时)的泾阳站(57131)探空资料，研究证明特定对流参数对预报西安机场雷暴天气有较好指示性。分析表明：西安机场2019~2024年在有无雷暴时的对流参数数值分布存在差异；包括整层比湿积分(IQ)、K指数(KI)、抬升指数(LI)、总指数(TT)、沙氏指数(SI)以及对流有效位能(CAPE)在内的各项参数与雷暴天气发生概率呈线性相关；将这些参数进行二值化处理后，发现其对雷暴天气有较好的指示能力；采用二值Logistic回归方程，建立雷暴天气概率模型，同时利用2025年的样本数据进行预报准确性检验，结果证明具备较好的应用价值，可辅助预报员用于雷暴天气的潜势预报。

Abstract: This study utilizes surface meteorological observation data from Xi’an Airport and upper-air sounding data from Jingyang Station (57131) at 08:00 and 20:00 Beijing Time (BJT) from 2019 to 2024. A statistical analysis was conducted to examine the relationship between thunderstorm events at Xi’an Airport and commonly used convective parameters. The results indicate significant differences in the distribution of convective parameter values between thunderstorm and non-thunderstorm days during the 2019~2024 period. Parameters including Integrated Whole-Layer Specific Humidity (IQ), K-index (KI), Lifted Index (LI), Total Totals Index (TT), Showalter Index (SI), and Convective Available Potential Energy (CAPE) show a linear correlation with the probability of thunderstorm occurrence. These parameters demonstrated a good indicative capability for thunderstorms after being converted into binary values. A binary logistic regression model was employed to develop a probabilistic forecasting equation for thunderstorms. The model was validated using convective parameter data from 2025, which confirmed its good forecasting performance, suggesting its utility as a supplementary tool for thunderstorm potential forecasting.