| 摘 要： |
As the amplifier of global climate change, climate warming exerts an important impact on the freezing/thawing cycles of soil over the Tibetan Plateau, and it shapes the trend of permafrost degradation. Intensified frozen soil collapse causes severe effects on ecosystem water and energy balance as well as on carbon cycle. Previous studies have focused on the direct effects of climate change on permafrost degradation. However, there is also growing evidence showing vegetation growth can affect regional climate system, and consequently we hypothesize that vegetation autumn phenology (i.e., the end of the growing season, EOS) may influence the start date of frozen (SOF) through feedbacks to regional climates. Using satellite greenness data derived EOS and the microwave remote sensing generated SOFESDR (freeze-thaw Earth system data record) over 2001-2018, we showed a dominant-negative (13.1% vs. 0.9%) relationship between SOFESDR and EOS, suggesting an earlier SOFESDR with a delayed EOS. We found that biogeophysical indicators served as potential connections, including surface al-bedo, soil temperature, soil water content, and evapotranspiration, for the observed relationship. We therefore proposed a new site-level SOFf(EOS)xESDR algorithm based on the EOS-SOF relationship. With ground SOFALT observed from the active layer thickness at 63 sites over Tibetan Plateau, the new model provided significantly improved estimates of SOF with Pearson's correlation coefficient (R) of 0.84 and root mean square error (RMSE) of 7.63 days, comapred with current remote sensing-based SOF product (R = 0.26, RMSE = 22.60 days). We further proposed a look-up table approach to map the SOF over TP and found an overall earlier SOF (24.0 +/- 15.8) than current SOFESDR products. Therefore, our results identified a significant correlation between the autumn phenology and the SOF variability, highlighting the importance of feedbacks of autumn phenology on climate change. |
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