超调路径的空间分辨率模拟年温度预测。

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2024-11-21 DOI:10.1038/s41597-024-04122-1
Jonas Schwaab, Mathias Hauser, Robin D Lamboll, Lea Beusch, Lukas Gudmundsson, Yann Quilcaille, Quentin Lejeune, Sarah Schöngart, Carl-Friedrich Schleussner, Shruti Nath, Joeri Rogelj, Zebedee Nicholls, Sonia I Seneviratne
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引用次数: 0

摘要

由于过去十年气候行动不足,21 世纪全球升温超过 1.5 °C--至少是暂时超过 1.5 °C--的可能性越来越大。这种暂时性的温度超调会带来更多的气候风险,而人们对这些风险的了解还很不够。地球系统模式气候预测仅适用于数量非常有限的超调途径,因此无法对其影响进行全面分析。为了解决这个问题,我们在这里提供了一个针对不同超调途径的空间分辨率模拟年度温度预测的新数据集。该数据集是利用 FaIR 和 MESMER 仿真器创建的。首先,利用 FaIR 将十种不同的排放情景(包括七种以超调为特征的情景)转化为大量的受迫全球平均气温集合。然后,利用 MESMER 将这些全球平均气温转换为当地年气温场的随机集合。为了确保在精确描述集合分布和大型集合的存储要求之间取得最佳平衡,在进行这一程序的同时,还测试了样本数量级对不同集合规模的敏感性。由此产生的数据集为研究一系列超调情景对当地和区域气候变化的影响提供了独特的机会,包括温度阈值超标的时间和幅度。
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Spatially resolved emulated annual temperature projections for overshoot pathways.

Due to insufficient climate action over the past decade, it is increasingly likely that 1.5 °C of global warming will be exceeded - at least temporarily - in the 21st century. Such a temporary temperature overshoot carries additional climate risks which are poorly understood. Earth System Model climate projections are only available for a very limited number of overshoot pathways, thereby preventing comprehensive analysis of their impacts. Here, we address this issue by presenting a novel dataset of spatially resolved emulated annual temperature projections for different overshoot pathways. The dataset was created using the FaIR and MESMER emulators. First, FaIR was employed to translate ten different emission scenarios, including seven that are characterised by overshoot, into a large ensemble of forced global mean temperatures. These global mean temperatures were then converted into stochastic ensembles of local annual temperature fields using MESMER. To ensure an optimal tradeoff between accurate characterization of the ensemble spread and storage requirements for large ensembles, this procedure was accompanied by testing the sensitivity of sample quantiles to different ensemble sizes. The resulting dataset offers the unique opportunity to study local and regional climate change impacts of a range of overshoot scenarios, including the timing and magnitude of temperature thresholds exceedance.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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