Abstract
We introduce the concept of time of emergence of economic impacts (ToEI), which identifies the initial moment when the climate change impact signal exceeds a previously defined threshold of past economic output shocks in a given geographic area. We compute the ToEI using probabilistic climate change projections and impact functions from three integrated assessment models of climate change: DICE, RICE and CLIMRISK. Our results demonstrate that, in terms of the business-as-usual carbon emissions scenario, the global economy could reach its ToEI by 2095. Regional results highlight areas that are likely to reach the ToEI sooner, namely Western Europe by 2075, India by 2083, and Africa by 2085. We also explore local-scale variations in the ToEI demonstrating that, for example, Paris already reached the ToEI around 2020, while Shanghai will reach it around 2080. We conclude that the ToEI methodology can be applied to impact models of varying scales when sufficient historical impact data are available. Moreover, unprecedented impacts of climate change in the 21st century may be experienced even in economically developed regions in the US and Europe. Finally, moderate to stringent climate change mitigation policies could delay the extreme economic impacts of climate change by three decades in Latin America, the Middle East, and Japan, by two decades in India, Western Europe, and the US, and by one decade in Africa. Our results can be used by policymakers interested in implementing timely climate policies to prevent potentially large economic shocks due to climate change.
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Footnotes
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Only the original impact functions from the DICE and RICE models are used in this study, rather than the entire IAM framework.
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SI 3.
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Economic output can refer to total, sectoral, firm-level, or other output.
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The lists of countries (SI table 11) and missing data (SI table 10) are presented in SI 4.
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SI 7.
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A detailed example of the calculation using three case study regions is presented in SI 4.1.
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The reason is a similar % GDP shock would result in higher absolute GDP losses when future GDP levels are higher.
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There exist two special cases, where
(i.e. all values of ) and (i.e. all values of ). The first case implies that the ToEI was never reached within the specified horizon, and . In the latter case, the ToEI is exceeded in the first period of evaluation or before, and ToEI < t. In this paper, , meaning that we are evaluating the ToEI between 2010 and 2100. - 13
SI 1.
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SI 2.
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SI 3.
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For results using alternative climate scenarios, damage functions, and filters, please refer to SI 6.
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Shock values for all RICE regions are presented in SI table 3. For the full list of Maddison Project database countries belonging to each RICE region, see SI table 11.
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The lack of ToEI in the Eurasian region in the 21st century can be explained by the relatively low sensitivity of the RICE damage function to increases in global temperature (SI table 2).
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The relatively high ToEI value in China could be attributed to the 1960s Great Chinese Famine, which had severe impacts on the economy and is regarded as one of the greatest man-made disasters in human history.
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These SSP population projection scenarios are explained in full detail in SI 3.3.
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See also SI figures 4 and 5 for results under various temperature realizations as a measure of climate uncertainty.
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This potential mismatch in scale may be less serious than one might initially expect since our results demonstrate that most climate impacts occur in cities in which most (past and future) GDP is earned.
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SI figure 1.
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This also implies a low PoEI value, as the probability of any given run exceeding the threshold is low.
