瑞典斯德哥尔摩大学Qiong Zhang团队研究了通过植被-气候反馈，协调东亚全新世中期温度差异。相关论文于2024年4月7日发表于《科学通报》杂志上。

研究人员探究了全新世中期(约6ka)植被—气候反馈对东亚地区温度异常模式的影响。通过利用完全耦合的地球系统模型EC-Earth，对有无耦合动态植被进行模拟，目的是分离植被变化对区域温度格局的影响。

研究结果表明，植被—气候反馈促进了东亚大部分地区的变暖，导致了全新世中期温度变化的空间多样性，并显著提高了模型数据的一致性。研究结果强调了植被—气候反馈在解决全新世温度难题中的关键作用，并强调了其对模拟准确气候情景的重要性。

据了解，“全新世温度难题”一词指的是基于代理的重建与瞬态模型模拟之间的不一致性，它挑战了人们对全新世全球温度演变的理解。气候重建表明，在全新世极热期之后出现了降温趋势，而模型模拟表明，由于冰盖退缩和温室气体浓度上升，气候变暖趋势持续不变。各种各样的因素，如季节性偏差和被忽视的反馈过程，被认为是造成这种差异的潜在原因。

附：英文原文

Title: Reconciling East Asia's mid-Holocene temperature discrepancy through vegetation-climate feedback

Author: Jie Chen, Qiong Zhang, Zhengyao Lu, Yanwu Duan, Xianyong Cao, Jianping Huang, Fahu Chen

Issue&Volume: 2024/04/07

Abstract: The term “Holocene temperature conundrum” refers to the inconsistencies between proxy-based reconstructions and transient model simulations, and it challenges our understanding of global temperature evolution during the Holocene. Climate reconstructions indicate a cooling trend following the Holocene Thermal Maximum, while model simulations indicate a consistent warming trend due to ice-sheet retreat and rising greenhouse gas concentrations. Various factors, such as seasonal biases and overlooked feedback processes, have been proposed as potential causes for this discrepancy. In this study, we examined the impact of vegetation-climate feedback on the temperature anomaly patterns in East Asia during the mid-Holocene (～6 ka). By utilizing the fully coupled Earth system model EC-Earth and performing simulations with and without coupled dynamic vegetation, our objective was to isolate the influence of vegetation changes on regional temperature patterns. Our findings reveal that vegetation-climate feedback contributed to warming across most of East Asia, resulting in spatially diverse temperature changes during the mid-Holocene and significantly improved model-data agreement. These results highlight the crucial role of vegetation-climate feedback in addressing the Holocene temperature conundrum and emphasize its importance for simulating accurate climate scenarios.

DOI: 10.1016/j.scib.2024.04.012

Source: https://www.sciencedirect.com/science/article/pii/S2095927324002469