Divergent Pre-Storm Pathways: Moisture-Driven Precursors Distinguish Dry and Wet Severe Convective Wind events

1.surface:The file is the temporal evolution data of composite surface meteorological variables for dry and wet SCW events during 2020–2023 warm season.2.profile:The file is the mean thease,WKE and t-td of the lead time within 40min before the onset of SCW and the climatological mean WKE derived from all warm-season soundings across China during 2016–2023 for dry and wet SCW events. 3.verticalsection:The file is height-time cross section of thease,WKE and t-td during 2016–2023 warm season for dry and wet SCW events.The data matrix is minute(9) x level(50) for thease and WKE and minute(9) x level(100) for t-td.4.parameters.The 16 approximate Sounding Parameters Examined for dry and wet SCW events during 2016–2023 warm season.5. A 'nan' value in the data indicates a missing value.1. 地面数据集（surface）：该文件存储了2020-2023年暖季期间干、湿两类SCW事件的合成地面气象变量的时间演变序列数据。 2. 廓线数据集（profile）：该文件包含SCW发生前40分钟内提前时段的平均位温（theta）、WKE（Wave Kinetic Energy）及t-td（temperature minus dew point temperature），同时包含2016-2023年暖季期间基于中国全域所有探空资料计算得到的干、湿两类SCW事件的气候平均态WKE。 3. 垂直剖面数据集（verticalsection）：该文件包含2016-2023年暖季期间干、湿两类SCW事件的位温、WKE及t-td的高度-时间剖面数据，其数据矩阵维度为：位温和WKE为9分钟×50层，t-td为9分钟×100层。 4. 参数数据集（parameters）：该数据集包含2016-2023年暖季期间针对干、湿两类SCW事件所分析的16种近似探空参数。 5. 数据中的"nan"值代表缺失值。