the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A harmonized 2000–2024 dataset of daily river ice concentration and annual phenology for major Arctic rivers
Abstract. River ice plays a critical role in Arctic freshwater routing, navigation safety, and biogeochemical exchange. However, consistent, daily-resolved observations across the pan-Arctic remain scarce. Here we present a harmonized, multi-decadal dataset of daily river ice concentration (RIC) and annual phenology (freeze-up, breakup, and ice duration) for the six largest Arctic rivers—Yukon, Mackenzie, Ob, Yenisey, Lena, and Kolyma—covering hydrological years 2001–2024. Built from >590,000 MODIS Terra/Aqua scenes, our workflow integrates a scalable threshold-based classifier on Google Earth Engine with dual-satellite daily synthesis, temporal-window cloud reclassification, and a high-latitude dark-period correction. Technical validation against higher-resolution optical imagery shows a mean RIC accuracy of 0.83 across basins. Phenological metrics derived from MODIS agree with in situ records with mean absolute errors (MAE) of 10.8 days for freeze-up and 11.4 days for breakup (improving to 8.4 days relative to the onset of ice drift), and with Landsat-based river-section phenology with MAE of 10.5 days (freeze-up) and 16.0 days (breakup). RIC correlates strongly with surface air temperature (mean Pearson r = −0.91) and increases systematically with latitude. Trend analysis from 2001 through 2024 shows delayed freeze-up in over 66 % of river segments, earlier breakup in more than 65 %, and shorter ice seasons in over 65 %. On average, freeze-up is delayed by 9.0 days, breakup occurs 7.8 days earlier, and ice duration shortens by 14.1 days over the study period. These basin-consistent, temporally resolved records provide an open benchmark for diagnosing cryospheric change in Arctic river corridors and for constraining model–data intercomparisons. The river-ice dataset is available via Zenodo (https://doi.org/10.5281/zenodo.17054619, Qiu et al., 2025).
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Status: open (until 12 Jan 2026)
- CC1: 'Comment on essd-2025-607', Laurent de Rham, 05 Dec 2025 reply
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A harmonized 2000–2024 dataset of daily river ice concentration and annual phenology for major Arctic rivers Jiahui Qiu et al. https://doi.org/10.5281/zenodo.17054619
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Thank-you for this global scale work on river ice the transparency of methods and sharing data with the community. As reported in the abstract, the mean absolute error (MAE) values for the three metrics (freeze-up, breakup, duration) are larger numbers than the trend values. Some discussion of the results is warranted in-so-far as the robustness of reported trends within the modelling framework error. A colleague with a climate background refers to this as "signal versus noise" issue.