Causes of Climate Models Uncertainty and Implications for Economic Policy

Alfred Greiner

doi:10.1515/ev-2025-0019

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Causes of Climate Models Uncertainty and Implications for Economic Policy

Alfred Greiner

Published/Copyright: July 22, 2025

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From the journal The Economists’ Voice

Abstract

In this paper the causes of climate models uncertainty are shown and policy implications are discussed. It is well known that a higher greenhouse gas concentration raises the radiative forcing of the earth and the physics behind it is well understood. However, regarding the feedback effects of higher temperatures, parameter uncertainty, model uncertainty and the chaotic nature of the climate system give rise to a considerable degree of ignorance regarding the climate system. Given this uncertainty costly CO₂ abatement measures are difficult to justify with the currently available technology. But, due to technical progress more efficient technologies are expected to reduce abatement costs in the future such that a net zero emission policy could be justified to avoid possible, but uncertain, climate damages. However, fixing a deadline by which the net zero goal must be met is not welfare maximizing and more flexibility is needed to avoid prohibitive costs.

Keywords: global warming; uncertainty; technology; policy implications

JEL Classification: E61; Q54

Corresponding author: Alfred Greiner, Department of Business Administration and Economics, Bielefeld University, P.O. Box 100131, 33501 Bielefeld, Germany, E-mail: agreiner@uni-bielefeld.de

I thank the editor Friedrich Heinemann and two referees for useful comments on an earlier version.

Conflict of interest: The author declares that he has no competing interest that could have influenced the outcome of this research.
Research funding: The author did not receive any direct funding for this study.

Appendix 1

Considering 2 countries, the costs of reducing CO₂ emissions K_i in country i, i = 1, 2, and of deviating from an optimal CO₂ level C ¯ are specified as follows,

(1) K i = ( u i + b i ) − 1 + δ 1 ( C ¯ − C ) 2 + δ 2 ( C ¯ − C ) 2 , i = 1,2 , δ 1 = 1 , δ 2 = 0 ,

with b_i ∈ IR, i = 1, 2, reflecting the state of the technology. The variable u_i, i = 1, 2, denotes the share of anthropogenic emissions in country i relative to non-anthropogenic emissions E a ¯ . The costs of the CO₂ concentration are strictly positive in country 1 when the CO₂ concentration deviates from a certain value, i.e. for C ≠ C ¯ , whereas country 2 does not incur costs, δ₂ = 0. The evolution of the CO₂ concentration is given by,

(2) C ̇ = β E a ¯ 1 + u 1 + u 2 − μ C ,

with β that part of emissions not absorbed by the earth and μ the decay rate of CO₂.

Denoting the discount rate by ρ > 0, the intertemporal optimization problem reads as max u 1 , u 2 − ∫ 0 ∞ e − ρ t ( K 1 + K 2 ) d t subject to (2) and with the costs given by (1). Forming the current-value Hamiltonian (for a short introduction see e.g. Greiner and Fincke 2015, Appendix B),

H ( ⋅ ) = − u 1 + b 1 − 1 − u 2 + b 2 − 1 − C ¯ − C 2 + λ β E a ¯ ( 1 + u 1 + u 2 ) − μ C ,

with λ the shadow price of the atmospheric CO₂ concentration, the necessary and sufficient^[7] optimality conditions are obtained as,

(3) u i = − b i + 2 ( − λ ) β E a ¯ − 2 / 3 , i = 1,2

(4) λ ̇ = λ ( ρ + μ ) − 2 ( C ¯ − C )

The first equation states that the marginal costs of abatement, ( 1 / 2 ) ( u i + b i ) − 3 / 2 , equals its marginal benefits, ( − λ ) β E a ¯ , in the two countries. For C > ( < ) C ¯ the shadow price of CO₂ is negative (positive) stating that a rise (decline) causes costs, where we only consider the case C > C ¯ . At the steady state C ̇ = λ ̇ = 0 holds.

Equation (3) shows that the higher the level of technology, the lower the emissions. To illustrate that result, numerical values for the parameters are specified. The discount rate is set to 3.5 %, i.e. ρ = 0.035, the share of emissions entering the atmosphere is 45 % and the decay rate is 2.5 %, β = 0.45, μ = 0.025. According to IPCC (2001) the 1/e time is between 200 and 5 years giving a value for μ between 0.184 % and 7.36 %. Harde (2019) and Manning et al. (1990) report the 1/e time of (radioactive) ¹⁴CO₂ as 15 and 17 years, respectively, giving a value for μ of 2.5 % and 2.2 %. The parameter C ¯ is set to β E a ¯ / μ , i.e. to the value with zero anthropogenic emissions without loss of generality. The following Table 4 gives the optimal steady state abatement rates u_1,st and u_2,st for different values of the abatement costs modelled by b_i, i = 1, 2. For example, setting b_i = 0 implies that the marginal costs of abatement converge to infinity when abatement is set such that net zero is achieved, i.e. for u_i → 0.

Table 4:

Optimal u_1,st, u_2,st for different values of abatement costs b_i, i = 1, 2.

	b₁ = 0	b₁ = 0.1	b₁ = −0.1
b₂ = 0	u_1,st = 0.0612	u_1,st = −0.0136	u_1,st = 0.1455
	u_2,st = 0.0612	u_2,st = 0.0864	u_2,st = 0.0455
b₂ = 0.1	u_1,st = 0.0864	u_1,st = −0.0218	u_1,st = 0.1612
	u_2,st = −0.0136	u_2,st = −0.0218	u_2,st = −0.0388
b₂ = −0.1	u_1,st = 0.0455	u_1,st = −0.0388	u_1,st = 0.1359
	u_2,st = 0.1455	u_2,st = 0.1612	u_2,st = 0.1359

Table 4 shows that the outcome is symmetrical stating that the abatment is identical when both countries have the same marginal costs, independent of the fact that there is no damage in country 2. Setting b₁ = 0.2, b₂ = 0.21817 the optimal abatement rates are u_1,st = 0.0182, u_2,st = 1.2 × 10⁻⁶, i.e. country 2 pursues a net zero policy and country 1 emits 1.8 % of non-anthropogenic emissions.

References

Alimonti, G., and L. Mariani. 2023. “Is the Number of Global Natural Disasters Increasing?” Environmental Hazards 23 (2). https://doi.org/10.1080/17477891.2023.2239807.Search in Google Scholar

Allan, R. P., K. M. Willett, V. O. John, and T. Trent. 2022. “Global Changes in Water Vapor 1979–2020.” Journal of Geophysical Research: Atmospheres 127 (12): e2022JD036728, https://doi.org/10.1029/2022JD036728.Search in Google Scholar

Barker, D. 2022. “Temperature and U.S. Economic Growth: Comment on Colacito, Hoffmannn, and Phan.” Econ Journal Watch 19 (2): 176–89.Search in Google Scholar

Barker, D. 2023. “Temperature Shocks and Economic Growth: Comment on Dell, Jones, and Olken.” Econ Journal Watch 20 (2): 234–53.Search in Google Scholar

Barker, D. 2024. “Global Non-Linear Effect of Temperature on Economic Production: Comment on Burke, Hsiang, and Miguel.” Econ Journal Watch 21 (1): 35–68.Search in Google Scholar

Barker, D. 2024a. “Temperature and Economic Growth: Comment on Kiley.” Econ Journal Watch 20 (1): 69–84.Search in Google Scholar

Bondarev, A., and A. Greiner. 2025. “Non-Smooth Climate Change and Emergent Novel Equilibria in an environmental-economic System.” Communications in Nonlinear Science and Numerical Simulation 145: 108686. https://doi.org/10.1016/j.cnsns.2025.108686.Search in Google Scholar

Colorado State University. 2025. Modtran Web Interface. Boulder. https://biocycle.atmos.colostate.edu/shiny/modtran/ (accessed June 25, 2025).Search in Google Scholar

Colorado State University. 2025a. Tropical Meteorology Project. Boulder: Department of Atmospheric Science. https://tropical.atmos.colostate.edu/Realtime/index.php?arch&loc=global (accessed June 25, 2025).Search in Google Scholar

Earth System Science Center. 2025. Global Temperature Report. The University of Alabama in Huntsville. https://www.nsstc.uah.edu/climate/ (accessed June 25, 2025).Search in Google Scholar

EFI – Commission of Experts for Research and Innovation. 2014. Research, Innovation and Technological Performance in Germany. EFI-Report 2014. Berlin. https://ideas.repec.org/b/zbw/efigut/2014e.html (accessed June 25, 2025).Search in Google Scholar

Etminan, M., G. Myhre, E. J. Highwood, and K. P. Shine. 2016. “Radiative Forcing of Carbon Dioxide, Methane, and Nitrous Oxide: a Significant Revision of the Methane Radiative Forcing.” Geophysical Research Letters 43 (12): 614–12,623. https://doi.org/10.1002/2016GL071930.Search in Google Scholar

Frigg, R., L. A. Smith, and D. A. Stainforth. 2015. “An Assessment of the Foundational Assumptions in high-resolution Climate Projections: the Case of UKCP09.” Synthese 192 (12): 3979–4008, https://doi.org/10.1007/s11229-015-0739-8.Search in Google Scholar

Greiner, A. 2024. “Uncertainty of Climate Models and Policy Implications: a European Perspective.” List Forum für Wirtschafts- und Finanzpolitik 50 (4): 339–53. https://doi.org/10.1007/s41025-024-00266-5.Search in Google Scholar

Greiner, A. 2024a. “Climate Change and Economic Growth: Some Critical Reflections.” Sustainable Economies 2 (4): 304. https://doi.org/10.62617/se.v2i4.304.Search in Google Scholar

Greiner, A. 2025. Causes of Climate Models Uncertainty and Implications for Economic Policy. Bielefeld Working Papers in Economics and Management No. 02-2025. https://doi.org/10.2139/ssrn.5187034.Search in Google Scholar

Greiner, A., B. Bökemeier, and B. Owusu. 2025. “Climate Change and Economic Growth: Evidence for European Countries.” The American Journal of Economics and Sociology 82 (4): 323–59. https://doi.org/10.1111/ajes.12605.Search in Google Scholar

Greiner, A., and B. Fincke. 2015. Public Debt Sustainability and Economic Growth. Theory and Empirical Evidence. Cham, Heidelberg, New Yok, Dordrecht, London: Springer.10.1007/978-3-319-09348-2Search in Google Scholar

Greiner, A., L. Grüne, and W. Semmler. 2010. “Growth and Climate Change: Threshold and Multiple Equilibria.” In Dynamic Systems, Economic Growth, and the Environment, edited by J. Crespo Cuaresma, T. Palokangas, and A. Tarasyev, 63–78. Berlin: Springer Verlag.10.1007/978-3-642-02132-9_4Search in Google Scholar

Greiner, A., and F. Kugler. 1994. “A Note on Competition Among Techniques in the Presence of Increasing Returns to Scale.” In Evolutionary Economics and Chaos Theory. New Directions in Technology Studies, edited by L. Leydesdorff, and P. van den Besselaar, 44–52. London: Pinter Publishers.Search in Google Scholar

Greiner, A., and W. Semmler. 2005. “Economic Growth and Global Warming: A Model of Multiple Equilibria and Thresholds.” Journal of Economic Behavior and Organization 57 (4): 430–47, https://doi.org/10.1016/j.jebo.2005.04.007.Search in Google Scholar

Hansen, J., R. Ruedy, M. Sato, and K. Lo. 2010. “Global Surface Temperature Change.” Review of Geophysics 48 (4): RG4004. https://doi.org/10.1029/2010RG000345.Search in Google Scholar

Harde, H. 2019. “What Humans Contribute to Atmospheric CO2: Comparison of Carbon Cycle Models with Observations.” Earth Sciences 8 (3): 139–59. https://doi.org/10.11648/j.earth.20190803.13.Search in Google Scholar

Heal, G. 2017. “The Economics of the Climate.” Journal of Economic Literature 55 (3): 1046–63. https://doi.org/10.1257/jel.20151335.Search in Google Scholar

Heuzé, C., H. Zanowski, S. Karam, and M. Muilwijk. 2023. “The Deep Arctic Ocean and Fram Strait in CMIP6 Models.” Journal of Climate 36 (8): 2551–84. https://doi.org/10.1175/JCLI-D-22-0194.1.Search in Google Scholar

Hourdin, F., Mauritsen, T., Gettelmann, A., Golaz, J.-C., Venkatramani, B., Duan, Q., et al.. 2017. “The Art and Science of Climate Model Tuning.” Bulletin of the American Meteorological Society 98 (3): 589–602. https://doi.org/10.1175/bams-d-15-00135.1.Search in Google Scholar

IPCC. 2001. Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, edited by J. T. Houghton, Y. Ding, D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, et al.. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press.Search in Google Scholar

IPCC. 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. Geneva, Switzerland: IPCC.Search in Google Scholar

Irving, D., W. Hobbs, J. Chruch, and J. Zika. 2021. “A Mass and Energy Conservation Analysis of Drift in the CMIP6 Ensemble.” Journal of Climate 34 (8): 3157–70, https://doi.org/10.1175/jcli-d-20-0281.1.Search in Google Scholar

Jaeger, C. C., and J. Jaeger. 2011. “Three Views of Two Degrees.” Regional Environmental Change 11 (Suppl 1): S15–S26. https://doi.org/10.1007/s10113-010-0190-9.Search in Google Scholar

Kay, J. E., C. Deser, A. Phillips, A. Mai, C. Hannay, G. Strand, et al.. 2015. “The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability.” Bulletin of the American Meteorological Society 96 (8): 1333–49, https://doi.org/10.1175/BAMS-D-13-00255.1.Search in Google Scholar

Kolstad, C. D., and F. C. Moore. 2020. “Estimating the Economic Impacts of Climate Change Using Weather Observations.” Review of Environmental Economics and Policy 14 (1): 1–24. https://doi.org/10.1093/reep/rez024.Search in Google Scholar

Lan, X., P. Tans, and K. P. Thoning. 2025. Trends in globally-averaged CO2 Determined from NOAA Global Monitoring Laboratory Measurements. Version Monday, 06-Jan-2025 10:06:16 MST.Search in Google Scholar

Lewis, N. 2023. “Objectively Combining Climate Sensitivity Evidence.” Climate Dynamics 60 (9–10): 3139–65, https://doi.org/10.1007/s00382-022-06468-x.Search in Google Scholar

Loeb, N. G., G. C. Johnson, T. J. Thorsen, J. M. Lyman, F. G. Rose, and S. Kato. 2021. “Satellite and Ocean Data Reveal Marked Increase in Earth’s Heating Rate.” Geophysical Research Letters 48 (13): e2021GL093047, https://doi.org/10.1029/2021GL093047.Search in Google Scholar

Lorenz, E. N. 1963. “Deterministic Nonperiodic Flow.” Journal of the Atmospheric Sciences 20 (2): 130–44.10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2Search in Google Scholar

Ma, N., Y. Zhang, and Y. Yang. 2025. “Recent Decline in Global Ocean Evaporation due to Wind Stilling.” Geophysical Research Letters 52 (4): e2024GL114256, https://doi.org/10.1029/2024GL114256.Search in Google Scholar

Manning, M. R., D. C. Lowe, W. H. Melhuish, R. J. Sparks, G. Wallace, C. A. M. Bernninkmeijer, et al.. 1990. “The Use of Radiocarbon Measurements in Atmospheric Studies.” Radiocarbon 32 (1): 37–58. https://doi.org/10.1017/s0033822200039941.Search in Google Scholar

Mauritsen, T., B. Stevens, E. Roeckner, T. Crueger, M. Esch, M. Giorgetta, et al.. 2012. “Tuning the Climate of a Global Model.” Journal of Advances in Modeling Earth Systems 4 (3): M00A01, https://doi.org/10.1029/2012MS000154.Search in Google Scholar

Mears, C. A., and F. J. Wentz. 2017. “A Satellite-Derived Lower Tropospheric Atmospheric Temperature Dataset Using an Optimized Adjustment for Diurnal Effects.” Journal of Climate 30 (19): 7695–718. https://doi.org/10.1175/jcli-d-16-0768.1.Search in Google Scholar

Meinshausen, M., N. Meinshausen, W. Hare, S. C. B. Raper, K. Frieler, R. Knutti, et al.. 2009. “Greenhouse-Gas Emission Targets for Limiting Global Warming to 2 °C.” Nature Letters 458: 1158–63.10.1038/nature08017Search in Google Scholar

Meinshausen, M., S. C. B. Raper, and T. M. L. Wigley. 2011. “Emulating Coupled Atmosphere-Ocean and Carbon Cycle Models with a Simpler Model, MAGICC6-Part 1: Model Description and Calibration.” Atmospheric Chemistry and Pyhsics 11 (4): 1417–56, https://doi.org/10.5194/acp-11-1417-2011.Search in Google Scholar

Nordhaus, W. D. 1977. “Strategies for the Control of Carbon Dioxide.”. Cowles Foundation Discussion Papers. 675. Connecticut: Yale University. https://elischolar.library.yale.edu/cowles-discussion-paper-series/675.Search in Google Scholar

Nordhaus, W. D. 1994. Managing the Global Commons: The Economics of the Greenhouse Effect. Cambridge, MA: MIT Press.Search in Google Scholar

Pindyck, R. S. 2013. “Climate Change Policy: What do the Models Tell Us?” Journal of Economic Literature 51 (3): 860–72, https://doi.org/10.1257/jel.51.3.860.Search in Google Scholar

Pindyck, R. S. 2017. “The Use and Misuse of Models for Climate Policy.” Review of Environmental Economics and Policy 11 (1): 100–14. https://doi.org/10.1093/reep/rew012.Search in Google Scholar

Popp, D. 2004. “ENTICE: Endogenous Technological Change in the DICE Model of Global Warming.” Journal of Environmental Economics and Management 48 (1): 742–68, https://doi.org/10.1016/j.jeem.2003.09.002.Search in Google Scholar

Ranasinghe, R., A. C. Ruane, R. Vautard, N. Arnell, E. Coppola, F. A. Cruz, et al.. 2021. “Climate Change Information for Regional Impact and for Risk Assessment.” In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Pean, S. Berger, et al.., 1767–926. Cambridge, New York: Cambridge University Press.Search in Google Scholar

Schmalensee, R., and R. N. Stavins. 2017. “Lessons Learned from Three Decades of Experience with Cap and Trade.” Review of Environmental Economics and Policy 11 (1): 59–79. https://doi.org/10.1093/reep/rew017.Search in Google Scholar

Scientific Advisory Board at the Ministry of Economics and Labor. 2004. Zur Förderung erneuerbarer Energien. Dokumentation Nr. 534. Berlin: Bundesministerium für Wirtschaft und Arbeit.Search in Google Scholar

Sherwood, S. C., M. J. Webb, J. D. Annan, K. C. Armour, P. M. Forster, and J. C. Hargreaves, et al.. 2020. “An Assessment of Earth’s Climate Sensitivity Using Multiple Lines of Evidence.” Review of Geophysics 58 (4): 1–92, https://doi.org/10.1029/2019RG000678.Search in Google Scholar

Simpson, I. R., K. A. McKinnon, D. Kennedy, D. M. Lawrence, F. Lehner, and R. Seager. 2024. “Observed Humidity Trends in Dry Regions Contradict Climate Models.” PNAS 121 (1): e2302480120. https://doi.org/10.1073/pnas.2302480120.Search in Google Scholar

Tol, R. S. J. 2021. “Europe’s Climate Target for 2050: an Assessment.” Intereconomics, Review of European Economic Policy 56 (6): 330–5. https://doi.org/10.1007/s10272-021-1012-7.Search in Google Scholar

Tol, R. 2023. “Costs and Benefits of the Paris Climate Targets.” Climate Change Economics 14 (4): 2340003. https://doi.org/10.1142/S2010007823400031.Search in Google Scholar

United Nations. 2016. The Paris Agreement. New York. https://unfccc.int/sites/default/files/resource/parisagreement_publication.pdf (accessed June 25, 2025).Search in Google Scholar

Wijngaarden, W. A., and Happer, W. 2020. “Dependence of Earth’s Thermal Radiation on Five Most Abundant Greenhouse Gases.” Atmospheric and Oceanic Physics arXiv:2006.03098.Search in Google Scholar

Wijngaarden, W. A., and Happer, W. 2023. “Atmosphere and Greenhouse Gas Primer.” Atmospheric and Oceanic Physics arXiv:2303.00808.Search in Google Scholar

Winkelbauer, S., M. Mayer, and L. Haimberger. 2024. “Validation of Key Arctic Energy and Water Budget Components in CMIP6.” Climate Dynamics 62 (5): 3891–926, https://doi.org/10.1007/s00382-024-07105-5.Search in Google Scholar

Yurak, V. V., and S. A. Fedorov. 2025. “Review of Natural and Anthropogenic Emissions of Carbon Dioxide into the Earth’s Atmosphere.” International Journal of Environmental Science and Technology 22 (4): 2719–36, https://doi.org/10.1007/s13762-024-05896-y.Search in Google Scholar

Zhang, J., S. Trück, C. Truong, and D. Pitt. 2023. “Time Trends in Losses from Major Tornadoes in the United States.” Weather and Climate Extremes 41: 100579. https://doi.org/10.1016/j.wace.2023.100579.Search in Google Scholar

Received: 2025-04-17

Accepted: 2025-07-06

Published Online: 2025-07-22

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https://doi.org/10.1515/ev-2025-0019

Keywords for this article

global warming; uncertainty; technology; policy implications