Uncertainty constraints on economic impact assessments of climate change simulated by an impact emulator
Uncertainty constraints on economic impact assessments of climate change simulated by an impact emulator
复制标题
影响模拟器模拟的气候变化经济影响评估的不确定性约束
DOI：
10.1088/1748-9326/aca68d
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发表时间：
2022
影响因子：
6.7
通讯作者：
Takahashi Kiyoshi
中科院分区：
文献类型：
--
作者：
Shiogama Hideo;Takakura Jun’ya;Takahashi Kiyoshi
由于许多新一代地球系统模型（ESM）被认为高估了未来全球变暖，政府间气候变化专门委员会的最新报告使用了全球变暖的约束范围而不是原始集合。然而，尚不清楚气候变化预测的制约因素如何可能减少影响评估的不确定性。在这里，我们表明，气候变化对世界经济影响的气候相关不确定性是可以限制的。通过应用影响模拟器，我们估计了9个部门的经济影响的基础上67个ESM的未来气候变化的预测，并发现在8个部门的影响是密切相关的最近过去的全球平均温度的趋势，这是用于约束全球变暖预测的度量。在中等温室气体浓度情景下，观测约束降低了单一模拟器模拟的总经济影响的上限，从世界国内生产总值的2.9%降低到2.5%（方差的相对减少为31%）。我们的研究结果表明，气候科学的进步如何有助于减少影响评估中与气候相关的不确定性，而我们没有研究模拟器和影响模型的不确定性。
Since many new generation Earth system models (ESMs) have been suggested to overestimate future global warming, the latest report of the Intergovernmental Panel on Climate Change used the constrained range of global warming instead of that in the raw ensemble. However, it is not clear how the constraints of climate change projections potentially reduce the uncertainty of impact assessments. Here, we show that the climate-related uncertainty of the economic impact of climate change in the world can be constrained. By applying an impact emulator, we estimate the economic impacts in nine sectors based on 67 ESMs' future climate change projections and find that the impacts in eight sectors are closely related to the recent past trend of global mean temperature, which is the metric used for the constraint of global warming projections. Observational constraints lower the upper bound of the aggregate economic impact simulated by the single emulator from 2.9% to 2.5% of the world gross domestic product (the relative reduction of variance is 31%) under the medium greenhouse gas concentration scenarios. Our results demonstrate how advances in climate science can contribute to reducing climate-related uncertainties in impact assessments, while we do not examine uncertainties of emulators and impact models.
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影响因子：
7.3
作者：
Nijsse, Femke J. M. M.;Cox, Peter M.;Williamson, Mark S.
通讯作者：
Williamson, Mark S.
影响因子：
5.1
作者：
Eyring, Veronika;Bony, Sandrine;Taylor, Karl E.
通讯作者：
Taylor, Karl E.
影响因子：
4.6
作者：
Iizumi T;Furuya J;Shen Z;Kim W;Okada M;Fujimori S;Hasegawa T;Nishimori M
通讯作者：
Nishimori M
DOI：
10.1016/j.jeem.2020.102360
发表时间：
2020-09-01
影响因子：
4.6
作者：
Kalkuhl, Matthias;Wenz, Leonie
通讯作者：
Wenz, Leonie
基于RCP/SSP情景的沿海地区适应有效性全球评估
影响因子：
4.8
作者：
M. Tamura;N. Kumano;Mizuki Yotsukuri;H. Yokoki
通讯作者：
H. Yokoki