LGM climate forcing and ocean dynamical feedback and their implications for estimating climate sensitivity

Jiang Zhu, C. Poulsen
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引用次数: 2

Abstract

Abstract. Equilibrium climate sensitivity (ECS) has been directly estimated using reconstructions of past climates that are different than today’s. A challenge to this approach is that temperature proxies integrate over the timescales of the fast feedback processes (e.g. changes in water vapor, snow, and clouds) that are captured in ECS as well as the slower feedback processes (e.g. changes in ice sheets and ocean circulation) that are not. A way around this issue is to treat the slow feedbacks as climate forcings and independently account for their impact on global temperature. Here we conduct a suite of Last Glacial Maximum (LGM) simulations using the Community Earth System Model version 1.2 (CESM1.2) to quantify the forcing and efficacy of land ice sheets (LIS) and greenhouse gases (GHG) in order to estimate ECS. Our forcing and efficacy quantification adopts the effective radiative forcing (ERF) and adjustment framework and provides a complete accounting for the radiative, topographic, and dynamical impacts of LIS on surface temperatures. ERF and efficacy of LGM LIS are −3.2 W m−2 and 1.1, respectively. The larger-than-unity efficacy is caused by the relatively larger temperature changes over land and the Northern Hemisphere subtropical oceans than those in response to a doubling of atmospheric CO2. The subtropical SST response is linked to LIS-induced wind changes and feedbacks in ocean-atmosphere coupling and clouds. ERF and efficacy of LGM GHG are −2.8 W m−2 and 0.9, respectively. The lower efficacy is primarily attributed to a smaller cloud feedback at colder temperatures. Our simulations further demonstrate that the direct ECS calculation using the forcing, efficacy, and temperature response in CESM1.2 overestimates the true value in the model by 25 % due to the neglect of slow ocean dynamical feedback. This is supported by the greater cooling (6.8 °C) in a fully coupled LGM simulation than that (5.3 °C) in a slab ocean model simulation with ocean dynamics disabled. The majority (67 %) of the ocean dynamical feedback is attributed to dynamical changes in the Southern Ocean, where interactions between ocean stratification, heat transport, and sea-ice cover are found to amplify the LGM cooling. Our study demonstrates the value of climate models in the quantification of climate forcings and the ocean dynamical feedback, which is necessary for an accurate direct ECS estimation.
LGM气候强迫和海洋动力反馈及其对气候敏感性估算的意义
摘要平衡气候敏感性(ECS)已经通过对不同于今天的过去气候的重建直接估算出来。这种方法面临的一个挑战是,温度代理在ECS中捕获的快速反馈过程(如水蒸气、雪和云的变化)的时间尺度上与较慢的反馈过程(如冰盖和海洋环流的变化)的时间尺度上相结合。解决这个问题的一个方法是将缓慢的反馈视为气候强迫,并独立地解释它们对全球温度的影响。本文利用社区地球系统模型1.2版(CESM1.2)进行了一套末次盛冰期(LGM)模拟,以量化陆地冰盖(LIS)和温室气体(GHG)的强迫和效力,从而估算ECS。我们的强迫和效力量化采用有效辐射强迫(ERF)和调整框架,提供了LIS对地表温度的辐射、地形和动态影响的完整解释。LGM LIS的ERF和疗效分别为- 3.2 wm - 2和1.1。这种大于一的效应是由于陆地和北半球副热带海洋的温度变化比大气CO2加倍的温度变化更大。副热带海温响应与lis诱导的风变化和海气耦合和云的反馈有关。LGM温室气体的ERF和效能分别为−2.8 wm−2和0.9 wm−2。较低的效率主要归因于较冷温度下较小的云反馈。我们的模拟进一步表明,由于忽略了缓慢的海洋动力反馈,使用CESM1.2中的强迫、效率和温度响应进行的直接ECS计算将模型中的真实值高估了25%。在完全耦合的LGM模拟中,比在禁用海洋动力学的平板海洋模式模拟中(5.3°C)更大的冷却(6.8°C)支持了这一点。大多数(67%)的海洋动力反馈归因于南大洋的动力变化,在那里发现海洋分层、热输送和海冰覆盖之间的相互作用放大了LGM冷却。我们的研究证明了气候模式在量化气候强迫和海洋动力反馈方面的价值,这是准确直接估计ECS所必需的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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