地球科学进展 ›› 2025, Vol. 40 ›› Issue (1): 57 -67. doi: 10.11867/j.issn.1001-8166.2025.006

大气海洋 上一篇    下一篇

从地球能量收支估算角度理解全球变暖
李煦骞1(), 李庆祥1,2,3()   
  1. 1.中山大学 大气科学学院,热带大气海洋系统科学教育部重点实验室,广东 广州 510275
    2.中国科学院中亚生态与环境研究中心,新疆 乌鲁木齐 830011
    3.广东省 南方 海洋科学与工程实验室(珠海),广东 珠海 519082
  • 收稿日期:2024-11-18 修回日期:2024-12-04 出版日期:2025-01-10
  • 通讯作者: 李庆祥 E-mail:lixq223@mail2.sysu.edu.cn;liqingx5@mail.sysu.edu.cn
  • 基金资助:
    国家自然科学基金项目(42375022);国家重点研发计划项目(2023YFC3008002)

Understanding Global Warming from the Perspective of Earth’s Energy Budget Estimation

Xuqian LI1(), Qingxiang LI1,2,3()   

  1. 1.School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, Guangzhou 510275, China
    2.Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
    3.Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai Guangdong 519082, China
  • Received:2024-11-18 Revised:2024-12-04 Online:2025-01-10 Published:2025-03-24
  • Contact: Qingxiang LI E-mail:lixq223@mail2.sysu.edu.cn;liqingx5@mail.sysu.edu.cn
  • About author:LI Xuqian, research area includes Earth’s energy balance. E-mail: lixq223@mail2.sysu.edu.cn
  • Supported by:
    the National Natural Science Foundation of China(42375022);The National Key Research and Development Program of China(2023YFC3008002)

追踪地球系统能量平衡性问题是研究人类活动对气候变化贡献的关键方法之一。能量不平衡直接反映了气候系统复杂的响应与反馈结果,是衡量气候变化的重要指标。然而,长期以来,准确估计地球能量收支一直是一个挑战。对于大气层顶与地表辐射通量的观测普遍存在较高的不确定性,且不同观测数据之间难以相互验证。这种较高的不确定性也导致地球系统能量收支通量变化的估算并不准确,同时由于缺乏高质量、高分辨率的观测数据约束,地表辐射通量的估算一直存在很大挑战。近年来通过海洋热容量/海平面高度数据进行间接估算地球能量收支的方法被广泛应用。利用大部分能量不平衡流向海洋热容量的特点,通过海洋数据观测可以得到不确定性较低的地球能量不平衡估算结果。此外,通过地球系统模式输出的多模式集合的方法,并辅以恰当的加权策略,也能得到地球能量收支的合理估算结果。通过数据整合水平能力的提升和相关技术的发展,气候科学家们正在不断提高对地球能量收支的理解,为理解和应对日益加剧的全球变暖提供了更为精确的科学依据。

Tracking the Earth’s energy imbalance is one of the key methods for studying the contribution of human activities to climate change. Energy imbalance directly reflects the complex responses and feedback of the climate system and is an important indicator of climate change. However, accurately estimating the Earth’s energy budget has long been a challenge. Observations of the top of the atmosphere and surface radiative fluxes have high uncertainties, and it is difficult to validate different observation datasets. In addition, these high uncertainties lead to inaccurate estimates of changes in Earth’s energy budget fluxes. Furthermore, estimating surface radiative fluxes is challenging because of the lack of high-quality, high-resolution observational data. Recently, methods using ocean heat content/sea-level height data for the indirect estimation of the Earth’s energy budget have been widely applied. Considering that most of the energy imbalance flows into the ocean heat content, ocean data observations can yield estimates of the Earth’s energy imbalance with lower uncertainty. Additionally, reasonable estimates of the Earth’s energy budget can be obtained through multi-model ensemble methods using Earth system model outputs, supplemented with appropriate weighting strategies. By improving data integration capabilities and developing related technologies, climate scientists continuously enhance their understanding of the Earth’s energy budget, providing more precise scientific evidence for understanding and addressing increasingly severe global warming.

中图分类号: 

表1 不同团队得到的 20002014年平均地表能量不平衡估计值及其不确定性范围 (W/m 2)
Table 1 Average surface Earth Energy ImbalanceEEIestimates and their uncertainty ranges from different teams for the years 2000-2014
图1 最新估算得到的 20062020年大气层顶人为驱动的地球能量不平衡的地球热量储量(据参考文献[ 20]修改)
括号内为1971—2020年的数据
Fig. 1 Updated estimates of anthropogenically driven Top of AtmosphereTOAEarth Energy ImbalanceEEIand Earth’s heat inventory for 2006-2020modified after reference20])
1971-2020 in parentheses
图2 19602023CMIP6模式地球能量不平衡数据及相关观测数据(据参考文献[ 11]修改)
SME和TOA-SME分别为地表EEI和大气层顶EEI的多模式平均值,阴影范围为95%不确定性范围
Fig. 2 Time series of CMIP6 model Earth Energy ImbalanceEEIdata and related observational data from 1960 to 2023modified after reference11])
SME and TOA-SME represent the multi-model mean of surface EEI and Top-Of-Atmosphere EEI, respectively, with the shaded area indicating the 95% uncertainty range
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