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基于卫星遥感数据的全天云特性及出现概率数据集。

All-day cloud property and occurrence probability dataset based on satellite remote sensing data.

作者信息

Nie Longfeng, Chen Yuntian, Zhang Dongxiao

机构信息

Pengcheng Laboratory, Shenzhen, 518000, P. R. China.

School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, P. R. China.

出版信息

Sci Data. 2025 Mar 5;12(1):387. doi: 10.1038/s41597-025-04659-9.

DOI:10.1038/s41597-025-04659-9
PMID:40044760
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11882926/
Abstract

The cloud property database and different type cloud occurrence probability datasets are helpful for meteorological research and application, as well as climate comprehension. Building on the foundation of CldNet with all-day cloud type recognition capability, CldNet Version 2.0 (CldNetV2) is proposed. This enhanced version leverages transfer learning and model parameter sharing techniques to not only classify cloud types but also predict additional cloud properties. Datasets with multiple cloud properties obtained by CldNetV2 make up for the lack of current Himawari cloud product at nighttime. Meanwhile, the dataset of different cloud type occurrence probabilities is statistically obtained on three time scales including annual, seasonal, and monthly, and more importantly, the dataset distinguishes between all day, daytime, and nighttime. In addition, the reliability of our cloud product is independently validated by the cloud properties from CALIPSO trajectories, ERA5 cloud cover fraction and the visualization of cloud property distribution and typhoon eye track during typhoons. Further more, the all-day cloud property and occurrence probability dataset for meteorological environment assessment has been publicly released.

摘要

云属性数据库和不同类型云出现概率数据集有助于气象研究与应用以及气候理解。基于具有全天云类型识别能力的CldNet，提出了CldNet版本2.0（CldNetV2）。这个增强版本利用迁移学习和模型参数共享技术，不仅对云类型进行分类，还预测其他云属性。CldNetV2获得的具有多种云属性的数据集弥补了当前Himawari云产品在夜间的不足。同时，不同云类型出现概率的数据集是在年、季节和月三个时间尺度上通过统计获得的，更重要的是，该数据集区分了全天、白天和夜间。此外，我们的云产品的可靠性通过CALIPSO轨迹的云属性、ERA5云覆盖率以及台风期间云属性分布和台风眼轨迹的可视化进行了独立验证。此外，用于气象环境评估的全天云属性和出现概率数据集已公开发布。

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