the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A high-resolution (0.05°) global seamless continuity record (2002–2023) of near-surface soil freeze-thaw states via passive microwave and optical satellite data
Abstract. The global near-surface soil freeze-thaw (FT) states are crucial for understanding complex interactions with hydrological, ecological, and climatic processes. However, current remote sensing of FT states primarily relies on passive microwave remote sensing, which, despite its all-weather monitoring capabilities, suffers from low spatial resolution. This limitation restricts its application to hydroclimatological scales, precluding its use in finer-scale studies such as soil erosion and hydrometeorological applications. To address this, this study introduces a novel downscaling approach that integrates passive microwave and optical satellite data to generate a long-term (2002–2023), high-resolution (0.05°) dataset of global near-surface FT states, ensuring daily seamless continuity. The dataset was validated against in situ measurements, demonstrating that the high-resolution product maintains an overall accuracy of 83.78 %, consistent with the coarse-resolution microwave-based dataset, while offering enhanced spatial detail. Comprehensive global trend analyses provided new insights into the dynamics of freeze-thaw cycles, revealing that the average annual number of frost days in regions north of 45° N is 187.8 ± 12.7 days, with 14.35 % of the area showing a decreasing trend in frozen persistence. Additionally, the average annual number of freeze onset dates is 240.3 ± 7.2, and 9.10 % of the area exhibits a trend of delayed freeze onset. The high-resolution record enables accurately monitoring FT states and providing detailed information, for a refined understanding of hydrological and ecological effects globally. The global 0.05° near-surface soil FT state dataset is freely available at https://doi.org/10.11888/Cryos.tpdc.301551 (Zhao et al., 2024b).
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Global 0.05° near-surface freeze/thaw state dataset v2.0 (2002-2023) Tianjie Zhao, Defeng Feng, Pei Yu, and Ziqian Zhang https://doi.org/10.11888/Cryos.tpdc.301551
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