DOI: 10.5281/zenodo.14785322
title: A global daily mesoscale front dataset from satellite observations

description: A global daily mesoscale front dataset based on ESA CCI SST dataset spanning from 1982 to 2023

Our global front dataset from 1982 to 2023 is archived in NetCDF format under the variable name “front”, comprising 15,340 individual daily files. The daily “front” variable is stored as a two-dimensional numerical matrix with dimensions of 7200 in the zonal direction and 3600 in the meridional direction. The values of the “front” variable are unitless, where regions with values greater than 0 represent the warm sides of detected frontal zones, while those with values less than 0 indicate the cold sides. All positions where the “front” variable equals -10, 10, or 30 correspond to detected frontal lines, with these values respectively indicating frontal lines near cold sides, warm sides, and no-front zones (Not important and potentially confusing; regular users can ignore this sentence and refer to the one below). For most users, it is sufficient to use "front = –10, 10, or 30" as frontal lines, "front ~= 0 & front ~= -128" as frontal zones, with "front > 0" indicating the frontal warm side, "front < 0 & front ~= -128" indicating the frontal cold side, and "front = -128" indicating land or other missing values.

Due to the large number of data files, the following files provide only a three-year preview; however, the complete dataset from 1982 to 2023 can be downloaded as a single zip file from this website.

If you have any questions, please do not hesitate to contact Dr. Xing (Shanghai Ocean University) via email at qinwangxing@gmail.com or qwxing@shou.edu.cn.

The data for the most recent years can be obtained by contacting Dr. Xing.

If you use our dataset, please consider citing our algorithm and dataset papers.

Xing, Q., Yu, H., Wang, H., & Ito, S. I. (2023). An improved algorithm for detecting mesoscale ocean fronts from satellite observations: Detailed mapping of persistent fronts around the China Seas and their long-term trends. Remote Sensing of Environment, 294, 113627.

Xing, Q., Yu, H., Yu, W., Chen, X., & Wang, H. (2025). A global daily mesoscale front dataset from satellite observations: in situ validation and cross-dataset comparison. Earth System Science Data, 17(6), 2831-2848.

Xing, Q., Yu, H., & Wang, H. (2024). Global mapping and evolution of persistent fronts in Large Marine Ecosystems over the past 40 years. Nature Communications, 15(1), 4090.
description: Chinese Description:

该全球锋面数据集涵盖 1982–2023 年,以 NetCDF 格式存档,变量名为 “front”,共包含 15,340 个逐日文件。逐日的 “front” 变量存储为一个二维数值矩阵,经度为 3600,纬度为 7200。

“front” 变量的取值无量纲:





数值 大于 0 的区域表示所识别锋区的 暖侧;




数值 小于 0 的区域表示所识别锋区的 冷侧。



其中,当 “front” 变量取值为 –10、10 或 30 时,对应的是识别到的锋面线,分别表示:–10 → 靠近冷侧的锋面线;10 → 靠近暖侧的锋面线;30 → 无锋区的锋面线(不重要,并且容易引起歧义,普通用户可以忽略这句,参考下面这句)。

对于大多数用户而言,只需使用:"front = –10、10 或 30" 作为锋面线, "front ~= 0 & front ~= -128" 作为锋区; "front > 0" 表示锋区暖侧,"front < 0 & front = -128" 表示锋区冷侧。"front ~= -128" 是陆地或者其他缺失值。

由于数据文件较多,网站仅提供三年的数据预览,但完整的 1982–2023 年数据集 可通过下载该网站上的整个压缩包获取。

如对数据和代码有任何问题,或需要其他处理格式的数据,请随时通过电子邮件联系 邢博士(上海海洋大学): qinwangxing@gmail.com 或 qwxing@shou.edu.cn

最新几年的数据也可以联系邢博士获取。

如果您使用了该数据集,请考虑引用我们的算法和数据集相关论文:

Xing, Q., Yu, H., Wang, H., & Ito, S. I. (2023). An improved algorithm for detecting mesoscale ocean fronts from satellite observations: Detailed mapping of persistent fronts around the China Seas and their long-term trends. Remote Sensing of Environment, 294, 113627.

Xing, Q., Yu, H., Yu, W., Chen, X., & Wang, H. (2025). A global daily mesoscale front dataset from satellite observations: in situ validation and cross-dataset comparison. Earth System Science Data, 17(6), 2831-2848.

Xing, Q., Yu, H., & Wang, H. (2024). Global mapping and evolution of persistent fronts in Large Marine Ecosystems over the past 40 years. Nature Communications, 15(1), 4090.