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基于原理的对全球气候平均状态下全球变暖的熟练预测。

Principle-based adept predictions of global warming from climate mean states.

作者信息

Cai Ming, Hu Xiaoming, Sun Jie, Hu Yongyun, Liu Guosheng, Wu Zhaohua, Ding Feng, Kang Wanying

机构信息

Department of Earth, Ocean, and Atmosphere Science, Florida State University, Tallahassee, FL 32306, USA.

School of Atmospheric Sciences, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.

出版信息

Natl Sci Rev. 2024 Nov 30;12(2):nwae442. doi: 10.1093/nsr/nwae442. eCollection 2025 Feb.

Abstract

Distinguishing anthropogenic warming from natural variability and reducing uncertainty in global-warming projections continue to present challenges. Here, we introduce a novel principle-based framework for predicting global warming from climate mean states that is based solely on carbon-dioxide-increasing scenarios without running climate models and relying on statistical trend analysis. By applying this framework to the climate mean state of 1980-2000, we accurately capture the subsequent global warming (0.403 K predicted versus 0.414 K observed) and polar warming amplification patterns. Our predictions from climate mean states of individual models not only exhibit a high map-correlation skill that is comparable to that of individual Coupled Model Intercomparison Project Phase 6 models for the observed warming, but also capture the temporal pace of their warming under the 1% annual CO-increasing scenario. This work provides the first principle-based confirmation that anthropogenic greenhouse gases are the primary cause of the observed global warming from 1980-2000 to 2000-2020, independently of climate models and statistical analysis.

摘要

区分人为变暖与自然变率,并减少全球变暖预测中的不确定性,仍然是一项挑战。在此,我们引入了一个基于新原理的框架,用于从气候平均状态预测全球变暖,该框架仅基于二氧化碳增加情景,无需运行气候模型,而是依靠统计趋势分析。通过将此框架应用于1980 - 2000年的气候平均状态,我们准确捕捉到了随后的全球变暖(预测为0.403K,观测为0.414K)以及极地变暖放大模式。我们从各个模型的气候平均状态所做的预测,不仅展现出与耦合模式比较计划第六阶段单个模型对观测到的变暖情况相当的高地图相关性技能,还捕捉到了在每年1%的二氧化碳增加情景下它们变暖的时间节奏。这项工作首次提供了基于原理的确认,即人为温室气体是1980 - 2000年至2000 - 2020年观测到的全球变暖的主要原因,这一结论独立于气候模型和统计分析。

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