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<p>As a critical climate variable with profound impacts on human society, land surface air temperature (LSAT) has been rising rapidly. Addressing the challenges posed by this warming demands a comprehensive evaluation of LSAT trends, which, however, is complicated by the multi-scale interactions in the climate system. In this study, we investigated LSAT changes on both global and regional scales (primarily based on the CRUTEM.5.0.1 dataset), utilizing two methods grounded in the cross-scale scaling behavior and the associated long-term memory (LTM) property of the LSAT records. The first method, based on Monte-Carlo simulations, estimates the distribution of natural trends arising from the LTM property. Results show that only in the recent period (1980–2022) have significant warming trends detected across most regions of the world, which appears to be conservative. Based on the Fractional Integral Statistical Model, we used the second method to further estimated the LTM-related variations and made Low-Order Approximations of Anthropogenic Trends (LOAATs) in LSAT records. Positive LOAATs were found in nearly all the regions during early periods (1900–1939, 1940–1979), and these trends have become much stronger recently, particularly in dry regions far from oceans. Simulations using CMIP6 models reveal that the models studied in this work generally struggle to replicate the regional LOAATs, highlighting the need for improved regional climate modeling. By 2022, the global LSAT warming level, as indicated by LOAAT, had increased by 1.47&#xa0;°C compared to the pre-industrial period (1880–1900), with more than half of the studied regions experiencing warming levels exceeding 1.5&#xa0;°C.</p>

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Exploring land surface air temperature changes: a detailed trend analysis through the lens of long-term memory

  • 期刊论文

  • 发表日期：

    2025年7月29日

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  • Chao Ma,
  • Naiming Yuan

摘要

As a critical climate variable with profound impacts on human society, land surface air temperature (LSAT) has been rising rapidly. Addressing the challenges posed by this warming demands a comprehensive evaluation of LSAT trends, which, however, is complicated by the multi-scale interactions in the climate system. In this study, we investigated LSAT changes on both global and regional scales (primarily based on the CRUTEM.5.0.1 dataset), utilizing two methods grounded in the cross-scale scaling behavior and the associated long-term memory (LTM) property of the LSAT records. The first method, based on Monte-Carlo simulations, estimates the distribution of natural trends arising from the LTM property. Results show that only in the recent period (1980–2022) have significant warming trends detected across most regions of the world, which appears to be conservative. Based on the Fractional Integral Statistical Model, we used the second method to further estimated the LTM-related variations and made Low-Order Approximations of Anthropogenic Trends (LOAATs) in LSAT records. Positive LOAATs were found in nearly all the regions during early periods (1900–1939, 1940–1979), and these trends have become much stronger recently, particularly in dry regions far from oceans. Simulations using CMIP6 models reveal that the models studied in this work generally struggle to replicate the regional LOAATs, highlighting the need for improved regional climate modeling. By 2022, the global LSAT warming level, as indicated by LOAAT, had increased by 1.47 °C compared to the pre-industrial period (1880–1900), with more than half of the studied regions experiencing warming levels exceeding 1.5 °C.