An lightweight CNN-CBAM model for identifying remnant low systems from global reanalysis

This dataset includes samples of Normal Tropical Cyclones, Remnant Lows\uff08RL\uff09, and Non-Tropical-Cyclone (No-TC) conditions. The labels for Normal Tropical Cyclones and Residual Systems are derived from the China Meteorological Administration (CMA) best-track dataset, with lifecycle stage definitions referenced from IBTrACS.The No-TC samples are generated based on the CMA best-track records over coastal regions of China. Specifically, the coastal area is divided into three sub-regions: Region A (Guangdong, Guangxi, Hainan, Hong Kong, Macao, and adjacent seas), Region B (Fujian Province and the Xiamen offshore area), and Region C (Jiangsu, Zhejiang, Shanghai, and adjacent seas). For each month from 2000 to 2022, ten time points are randomly selected as candidate No-TC samples.The selection of No-TC samples follows two constraints. First, if a tropical cyclone occurs in Region A during a given period while no cyclone activity is detected in Region B, samples may be selected from Region B. Second, sampling is excluded within three days before the onset and three days after the termination of any tropical cyclone lifecycle. For example, if a cyclone occurs in Region A on 2 August 2001, no samples are generated from that region within the \u00b13-day window, and sampling is shifted to Region B or Region C.ERA5 reanalysis grid data are then retrieved for all selected samples. Six key meteorological variables representing the dynamical and thermodynamical structures of tropical cyclones are extracted: mean sea level pressure (MSL), maximum wind speed (i10fg), mean wind speed (10fg), 850-hPa relative vorticity (Vo850), 300-hPa temperature (t300), and 500-hPa temperature (t500). These variables are merged in the above order and stored in NumPy (.npy) format.The resulting dataset is suitable for studies on residual system identification, tropical cyclone lifecycle classification, and data-driven prediction of remnant low systems using reanalysis data.

本数据集包含正常热带气旋（Normal Tropical Cyclones）、残余低压系统（Remnant Lows，RL）以及非热带气旋（Non-Tropical-Cyclone，No-TC）三类样本。正常热带气旋与残余系统的标签源自中国气象局（China Meteorological Administration，CMA）最佳路径数据集，其生命阶段定义参考了IBTrACS数据库。非热带气旋样本基于中国沿海区域的中国气象局最佳路径记录生成。具体而言，该沿海区域被划分为三个子区域：A区（广东、广西、海南、香港、澳门及邻近海域）、B区（福建省及厦门近海区域）、C区（江苏、浙江、上海及邻近海域）。2000年至2022年的每个月中，随机选取10个时间点作为非热带气旋候选样本。非热带气旋样本的选取遵循两项约束条件：其一，若某时段A区域内有热带气旋生成且B区域未检测到气旋活动，则可从B区域选取样本；其二，任何热带气旋生命过程开始前3天与结束后3天的时段内均排除采样。例如，若2001年8月2日A区域内生成热带气旋，则该区域±3天窗口内不生成样本，采样将转移至B区或C区。随后为所有选中的样本调取ERA5再分析格点数据。提取6项表征热带气旋动力与热力结构的关键气象变量：海平面平均气压（mean sea level pressure，MSL）、最大风速（maximum wind speed，i10fg）、平均风速（mean wind speed，10fg）、850百帕相对涡度（850-hPa relative vorticity，Vo850）、300百帕气温（300-hPa temperature，t300）以及500百帕气温（500-hPa temperature，t500）。按上述顺序将这些变量合并后，以NumPy（.npy）格式存储。本数据集适用于基于再分析数据的残余系统识别、热带气旋生命阶段分类以及残余低压系统数据驱动预测相关研究。