Under climate warming, atmospheric heatwave duration has increased substantially across the Tibetan Plateau (TP). However, differences between soil and atmospheric heatwave duration and the vertical structure of soil heatwaves remain poorly understood. Progress in this field has been constrained by the lack of high-accuracy and high-resolution soil temperature datasets. Here, we developed an integrated framework combining data evaluation, Triple Collocation data fusion, and LightGBM spatial downscaling with residual correction, and produced a daily multi-layer (10, 20, and 40 cm) soil temperature dataset at 1/30° resolution of for the TP during 2001–2022. The dataset achieved RMSE values of 3.15, 2.97, and 3.28 °C for daily maximum soil temperature at the 10, 20, and 40 cm depths, respectively. Using this dataset, we characterized the vertical patterns of soil heatwave duration and investigated their association with thermal memory. The results show that soil heatwaves are more persistent and their duration increases more rapidly than atmospheric heatwaves; both heatwave duration and its increasing trend strengthen from 10 to 40 cm depth. At 40 cm depth, soil heatwave duration reached 6.10–6.44 d, 34–45% longer than atmospheric heatwaves, while its increasing trend was approximately three times greater. This vertical amplification was more pronounced in permafrost regions and exhibited a cold season enhancement effect. Further analysis revealed that the autocorrelation of temperature anomalies, representing the thermal memory effect, and its increasing trend, became progressively stronger with soil depth and was more pronounced in permafrost regions and during the cold season. These patterns were consistent with the spatiotemporal patterns of heatwave duration. Our findings extend heatwaves research into the subsurface dimension and reveal a strong statistical association between thermal memory and the vertical amplification of soil heatwave persistence across the TP, although process-based modeling is needed to further test the underlying causal mechanisms.
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Zhang et al. (2026) studied this question.
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