4.7 Article

Discrepant trends in global land-surface and air temperatures controlled by vegetation biophysical feedbacks

期刊

ENVIRONMENTAL RESEARCH LETTERS
卷 18, 期 12, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.1088/1748-9326/ad0680

关键词

land surface temperature; air temperature; Earth greening

向作者/读者索取更多资源

This study systematically analyzed the trend of difference between satellite-based land surface temperature and station-based air temperature from 2003 to 2022. The results showed that during daytime of summer, the satellite-based temperature exhibited slower warming rate compared to the station-based temperature, which was attributed to recent Earth greening. However, during summer nighttime and winter daytime and nighttime, the satellite-based temperature showed faster warming rate.
Satellite-based land surface temperature (Ts) with continuous global coverage is increasingly used as a complementary measure for air temperature (Ta), yet whether they observe similar temporal trends remains unknown. Here, we systematically analyzed the trend of the difference between satellite-based Ts and station-based Ta (Ts-Ta) over 2003-2022. We found the global land warming rate inffered from Ts was on average 42.6% slower than that from Ta (Ts-Ta trend: -0.011 degrees C yr(-1), p = 0.06) during daytime of summer. This slower Ts-based warming was attributed to recent Earth greening, which effectively cooled canopy surface through enhancing evapotranspiration and turbulent heat transfer. However, Ts showed faster warming than Ta during summer nighttime (0.015 degrees C yr(-1), p < 0.01), winter daytime (0.0069 degrees C yr(-1), p = 0.08) and winter nighttime (0.0042 degrees C yr(-1), p = 0.16), when vegetation activity is limited by temperature and solar radiation. Our results indicate potential biases in assessments of atmospheric warming and the vegetation-air temperature feedbacks using satellite-observed surface temperature proxies.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据