定量分析模式间气候态差异对气候敏感度不确定性的影响

Climate sensitivity is the key index for projecting the strength of climate response to the increase of CO2 concentration. The uncertainty of climate sensitivity is a prominent problem in current climate modeling and climate change projection studies. The range of global warming projections in response to doubling of CO2-from 1.5 ℃ to 4.5 ℃ or greater-remains largely unscathed by the onslaught of new scientific insights. Recent studies show that the inter-model spread in the climate mean state is one of the main sources responsible for uncertainty in estimating climate sensitivity. However, it remains challenging to fully understand the underlying mechanisms and processes through which climate mean state regulates climate sensitivity. Here we propose a new framework based on climate feedback-response analysis method that decomposes the effect of the inter-model spread in the climate mean state on model’s climate sensitivity diversity into two parts: one is through the diversity in climate mean state’s longwave absorption/emission ability and the other is through the dependency of energy flux perturbations of individual climate feedbacks on climate mean state. In the proposed study, we will quantify process-based contributions of the inter-model spread in the climate mean state to uncertainties in estimating climate sensitivity using CMIP5/CMIP6 climate model simulation outputs. The new framework will allow us to quantify the key sources and processes, as well as key geographic regions, for the large inter-model spread of climate sensitivity. The success of the proposed study may provide a principle-based reference for narrowing down the inter-model spread of climate sensitivity by reducing the inter-model spread in the models’ mean state.

气候敏感度是衡量全球变暖对温室气体浓度升高响应强弱的重要指标，对气候敏感度预估的不确定性是当前气候模拟和预估的突出问题。从1979年至今，多模式对气候敏感度的估计值始终在1.5-4.5℃之间。最新研究表明，模式间气候态差异是气候敏感度不确定性的主要来源之一。然而，对于气候态调制气候敏感度的物理机制尚未有清晰的认识。因此，本项目在气候反馈诊断分析方法的基础上，通过理论推导出气候态调制气候敏感度的两种途径：气候系统的大气长波辐射吸收能力和反馈过程相关的能量扰动强度。利用CMIP5/6数据，明确模式间气候态差异特征，定量计算模式间气候态差异通过两种途径对气候敏感度不确定性的贡献。进一步对比模式间气候态差异通过调制各反馈过程引起的温度变化差异，寻找模式间气候态差异引起气候敏感度不确定性的关键反馈过程、途径和区域。通过本研究，可望从模式间气候态差异的角度为缩小气候敏感度不确定提供理论依据。

项目针对多模式气候敏感度不确定性的来源进行定量分析，特别是针对模式间的气候态差异对气候敏感度不确定性的影响。为了揭示气候态差异对气候敏感度不确定性的影响，我们开展了以下研究：1）各气候反馈过程对气候敏感度不确定性的相对贡献；2）历史气候对北极增暖的影响；3）从大气层顶（TOA）和地表理解气候反馈对气候敏感度的贡献差异等。此外，考虑到气候敏感度在不同区域之间存在较大差异，针对各反馈过程对不同区域气候敏感度的贡献也进行了初步探索。对比了导致东亚地区、北极、青藏高原、南海及其周边地区增暖的主要反馈过程差异。.通过开展以上研究内容，取得了以下重要研究成果。第一，突破传统理论认知，揭示反照率反馈和水汽反馈对多模式预估增暖不确定性的主导作用，明确了气候态主要通过调制气候反馈过程影响气候敏感度不确定性。第二，阐明模式预估增暖强度对历史气候模拟的依赖途径，并利用观测资料显著减小增暖预估的不确定性。第三，阐明从不同视角出发的反馈过程诊断框架对理解反馈过程贡献带来的影响，特别是导致对云反馈过程的贡献理解差异。此外，阐明热力和动力过程对全球变暖敏感区温度变化的贡献，如东亚地区、北极、青藏高原、南海及其周边地区等。.以上取得的成果均已发表于国际知名学术期刊，部分成果写入专著出版。到目前为止，受本项目资助发表学术论文共6篇（全部为SCI论文，其中包含发表在Nature Communications上的论文1篇），出版专著2部，相关成果可为气候变化预估及应对提供科学参考。项目执行期间，项目负责人获得副高职称。鉴于项目负责人在气候反馈方面取得的成果，获得了2021谢义炳青年气象科技奖。