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Climate Change Modeling and Prediction of Economic Impact

The reliability of predictions of future climate change is currently limited by the poorly constrained climate sensitivity (CS), which is still estimated to lie in the range of 1.5 - 4.5 °C, the same as in the Charney report (1979). The CS is a critical parameter for predictions of the economic consequences of climate change, which also currently calculate climate-related economic damage as a simplistic function of surface temperature alone. The primary objective of the project is to improve predictions of future climate and its economic impacts. This will be achieved through the secondary objectives of (i) reducing the uncertainty associated with Earth's climate sensitivity through a cross-disciplinary approach in which econometric analysis is applied to climate observations, and (ii) coupling a state-of-the-art global climate model with a recently developed gridded macroeconomic model of climate change that adopts a richer economic damage function.

About the project

Global warming is widely recognized as one of the defining issues of our time, presenting one of the biggest challenges facing humanity in the 21st century, affecting lives, communities, and countries worldwide. To address this challenge, estimates of the impact of greenhouse gas emissions on Earth's climate and predictions of the responding climatic impact on society are an imperative prerequisite to successfully guide governmental and inter-governmental policies. 

Global Climate Models (GCMs) and Integrated Assessment Models (IAM) are designed to simulate the physical climate system and the economic impacts of climate change, respectively. While both modeling tools have evolved tremendously in recent years, GCMs still rely on IAMs for future emission scenarios, while IAMs rely on GCMs for key properties of the climate system. Each modeling tool is thus incomplete and suffers from its own shortcomings. In the project, we seek to address the above issues, which currently preclude reliable estimates of future climate change and its economic impacts. Specifically, we aim to firstly constrain Earth's climate sensitivity (that is, the global mean surface temperature increase per doubling of atmospheric carbon dioxide) through a cross-disciplinary approach that applies time series analysis that is common in the field of economics to climate data, and confronts GCMs with observational data in a new and innovative way.

The goal is to reveal which models suffer from compensating errors that allow them to reproduce past observations for the wrong reasons. Secondly, we intend to couple a state-of-the-art GCM with a recently developed IAM, in order to create a new and more complete tool for simulations of future climate and its economic impacts, and ultimately calculate economic damage using functions that can take climate variables beyond surface temperature into account.


The main objectives of the project are to test the following two hypotheses:

H1: GCMs underestimate Earth’s climate sensitivity, mainly because of a misrepresentation of the cooling effect of aerosols.

H2:  IAMs underestimate the economic damage from climate change, because of their overly crude representation of the link between climate change and economic impacts.


The project is motivated by and centered around the following two research questions (RQs):

RQ1: How sensitive is Earth’s climate to greenhouse gas perturbations? Earth’s climate sensitivity has for almost half a century been estimated to 1.5 – 4.5 °C – is a more constrained estimate possible?   

RQ2: Current regional IAMs predict that within this century, Global Warming will be detrimental to the economies of countries at mid- and low-latitudes, but actually beneficial to countries located at high Northern latitudes. Is this result an artefact of a too conservative estimate of climate sensitivity and an overly crude damage function?

The research that will be carried out in order to address the above research questions and test the two hypotheses can be subdivided into two work packages; WP1 on Climate Econometrics, and WP2 on Climate Change and Macroeconomics.


The name of the project is “Climate Change Modeling and Prediction of Economic Impact”. The project is funded by the Research Council of Norway, with grant number 281071.

Project period: Date start: 2018-07-01. Deadline: 2021-06-30.



  • Leirvik, Thomas & Yuan, Menghan (2021). A Machine Learning Technique for Spatial Interpolation of Solar Radiation Observations. Earth and Space Science. ISSN 2333-5084. doi: 10.1029/2020EA001527.
  • Antoniuk, Yevheniia & Leirvik, Thomas (2021). Climate change events and stock market returns. Journal of Sustainable Finance & Investment. ISSN 2043-0795. doi: 10.1080/20430795.2021.1929804. Full text in Research Archive
  • Yuan, Menghan; Leirvik, Thomas & Wild, Martin (2021). Global trends in downward surface solar radiation from spatial interpolated ground observations during 1961-2019. Journal of Climate. ISSN 0894-8755. doi: 10.1175/JCLI-D-21-0165.1. Full text in Research Archive
  • Sarkodie, Samuel Asumadu; Owusu, Phebe Asantewaa & Leirvik, Thomas (2020). Global effect of urban sprawl, industrialization, trade and economic development on carbon dioxide emissions. Environmental Research Letters. ISSN 1748-9326. 15(3). doi: 10.1088/1748-9326/ab7640. Full text in Research Archive
  • Sarkodie, Samuel Asumadu; Adams, Samuel; Owusu, Phebe Asantewaa; Leirvik, Thomas & Ozturk, Ilhan (2020). Mitigating degradation and emissions in China: The role of environmental sustainability, human capital and renewable energy. Science of the Total Environment. ISSN 0048-9697. 719(1 June 2020). doi: 10.1016/j.scitotenv.2020.137530. Full text in Research Archive
  • Sarkodie, Samuel Asumadu; Adams, Samuel & Leirvik, Thomas (2020). Foreign direct investment and renewable energy in climate change mitigation: Does governance matter? Journal of Cleaner Production. ISSN 0959-6526. 263, p. 1–11. doi: 10.1016/j.jclepro.2020.121262. Full text in Research Archive
  • Bjordal, Jenny; Storelvmo, Trude; Alterskjær, Kari & Carlsen, Tim (2020). Equilibrium climate sensitivity above 5 °C plausible due to state-dependent cloud feedback. Nature Geoscience. ISSN 1752-0894. 13, p. 718–721. doi: 10.1038/s41561-020-00649-1. Full text in Research Archive
  • Phillips, Peter C. B.; Leirvik, Thomas & Storelvmo, Trude (2019). Econometric estimates of Earth's transient climate sensitivity. Journal of Econometrics. ISSN 0304-4076. 214(1), p. 6–32. doi: 10.1016/j.jeconom.2019.05.002. Full text in Research Archive
  • Storelvmo, Trude; Heede, Ulla; Leirvik, Thomas; Phillips, Peter; Arndt, Philipp & Wild, Martin (2018). Lethargic response to aerosol emissions in current climate models. Geophysical Research Letters. ISSN 0094-8276. 45(18), p. 9814–9823. doi: 10.1029/2018GL078298. Full text in Research Archive

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Published Aug. 20, 2018 1:17 PM - Last modified Mar. 23, 2022 4:35 PM