Regional climate change: consensus, discrepancies, and ways forward

IF 3.3 Q2 ENVIRONMENTAL SCIENCES
Tiffany A Shaw, Paola A. Arias, Mat Collins, D. Coumou, A. Diedhiou, C. Garfinkel, Shipra Jain, M. Roxy, Marlene Kretschmer, L. R. Leung, S. Narsey, Olivia Martius, Richard Seager, Theodore G. Shepherd, Anna A. Sörensson, Tannecia S. Stephenson, Michael Taylor, Lin Wang
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引用次数: 0

Abstract

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.
区域气候变化:共识、差异和前进之路
许多地区都出现了气候变化。一些观测到的区域气候变化,如北极变暖加剧和海陆变暖对比,已被气候模型预测到。然而,其他许多观测到的区域性变化,如热带海洋表面温度和季风降雨量的变化,即使考虑到自然内部变异性和模型对人为辐射强迫响应的结构不确定性,气候模型集合也不能很好地模拟。这表明气候模式的预测可能并不能完全反映我们的未来。由于 "信噪比悖论 "和现实世界中打破纪录的极端现象超出了模型预测的可能范围等一些实际和明显的困惑和限制,人们对模型与观测数据之间的差异还不甚了解。解决这些差异、困惑和局限性至关重要,因为要想有效地宣传变化的根本原因,为利益相关者提供可靠的信息,使社会能够适应变化,并提高复原力和降低脆弱性,就必须了解并可靠地预测区域气候变化。要实现这一目标,全球南部地区面临的挑战更大,尤其是因为缺乏长时段的观测数据,以及缺乏对全球南部地区气候变化的科学关注。为了解决观测数据与模型之间的差异,必须优先考虑将资源用于了解区域气候预测,并通过使用观测数据和模型测试偏差驱动因素的假设,分析模型与观测数据在哪些方面存在差异及其原因。通过利用新工具,如人工智能/机器学习、高分辨率模型、模型层次中的新建模实验、更好地量化强迫和新观测,可以发现和填补认识上的差距。需要有意识地努力创造机会,让地区专家,特别是来自全球南部的专家在地区气候研究中发挥主导作用。这包括共同学习分析模拟的技术方面以及区域气候变化的物理学和动力学。最后,需要改进地区气候传播方法,考虑到潜在的不确定性,以便向利益相关方和媒体提供可靠和可操作的信息。
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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来源期刊
Frontiers in Climate
Frontiers in Climate Environmental Science-Environmental Science (miscellaneous)
CiteScore
4.50
自引率
0.00%
发文量
233
审稿时长
15 weeks
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