Global-scale climate impact functions: the relationship between climate forcing and impact
Global-scale climate impact functions: the relationship between climate forcing and impact
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DOI：
10.1007/s10584-013-1034-7
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发表时间：
2016-02
期刊：
影响因子：
4.8
通讯作者：
N. Arnell;Sally Brown;S. Gosling;J. Hinkel;C. Huntingford;B. Lloyd‐Hughes;J. Lowe;T. Osborn;R. Nicholls;P. Zelazowski
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文献类型：
--
作者：
N. Arnell;Sally Brown;S. Gosling;J. Hinkel;C. Huntingford;B. Lloyd‐Hughes;J. Lowe;T. Osborn;R. Nicholls;P. Zelazowski
虽然在政策上对不同程度的气候变化所对应的气候变化影响有着强烈的兴趣，但迄今为止，气候强迫与影响之间的关系几乎没有一致的经验证据。这是因为，绝大多数影响评估使用基于排放的情景，并附带相关的社会经济假设，通过插值法推断其他温度变化的影响是不可行的。本文介绍了2050年气候变化的全球范围内的影响，相应的全球平均温度的增加，使用空间显式的影响模型代表水资源，河流洪水，沿海，农业，生态系统和建筑环境部门的影响进行评估。模式缩放用于构建与全球平均地表温度具体变化相关的气候情景，温度与海平面之间的关系用于构建海平面上升情景。气候情景由21个气候模式构成，以表明强迫和响应之间的不确定性。分析表明，全球平均气温上升的影响存在相当大的不确定性，主要原因是预测的区域降水变化存在不确定性。这具有重要的政策含义。有证据表明，由于气温和降水变化的相对重要性不断变化，全球平均气温变化与影响之间在某些部门存在非线性关系。在这里考虑的社会经济部门，如果以比例表示影响，则社会经济情景之间的关系是合理一致的，但绝对值可能存在很大差异。这一方法有一些需要注意的问题，包括使用模式缩放来构建情景，每个部门使用一个影响模型，以及强迫和反应之间关系的形状对影响指标定义的敏感性。
Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator.