A global daily mesoscale front dataset from satellite observations (old version)

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

Please see the new dataset at: https://zenodo.org/records/20250353

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.

Recently, we have noticed that some papers have misunderstood our method and therefore reported incorrect frontal detection results. Readers are advised to interpret these results with caution and to refer to our dataset and code as the authoritative source.

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.