Resolving Climate Uncertainty at Scale: A Social-Epistemic Analysis of Quantum-Informed Earth System Modeling and Climate Governance
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Abstract
Climate uncertainty represents one of the most consequential challenges for contemporary governance, affecting trillions of dollars in infrastructure investment, agricultural planning, and international mitigation policy. This research presents a comprehensive social-epistemic analysis of how quantum-classical hybrid computational frameworks are reshaping the production, validation, and utilization of climate knowledge. Through systematic examination of two critical climate processes, soil respiration and atmospheric ice nucleation; demonstrate that quantum-informed parameterizations substantially reduce uncertainty: 30–40% for cirrus cloud feedback and 52.7% for projected carbon cycle feedbacks. These reductions expand remaining carbon budgets by approximately 2,500 Pg C, extend mitigation timelines by 36–94 years for 1.5°C and 2.0°C targets, and yield economic implications exceeding $500–2,000 trillion across carbon pricing scenarios. Our analysis reveals three transformation pathways: (1) epistemic democratization, replacing empirical fitting and expert judgment with first-principles physical constraints; (2) policy resilience, enhancing decision confidence and enabling more gradual transition pathways; and (3) institutional restructuring, creating new interdisciplinary collaborations between quantum chemists, climate modelers, and policy analysts. However, environmental justice analysis shows that uncertainty reduction benefits are non-uniformly distributed, with vulnerable regions (South Asia, Africa) experiencing greater reductions but requiring deliberate governance mechanisms to ensure equitable outcomes. We identify the governance challenge of avoiding moral hazard, using expanded carbon budgets to enable ambition rather than delay. This research advances social scientific understanding of computational governance and provides actionable recommendations for integrating quantum-informed climate projections into international assessment frameworks, national adaptation planning, and climate litigation contexts.
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Goshu, B. S., & Muhammad Ridwan. (2026). Resolving Climate Uncertainty at Scale: A Social-Epistemic Analysis of Quantum-Informed Earth System Modeling and Climate Governance. Economit Journal: Scientific Journal of Accountancy, Management and Finance, 6(3), 250-277. Retrieved from https://www.biarjournal.com/index.php/economit/article/view/1573
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References
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Bloor, D. (1976). Knowledge and social imagery. Routledge.
Borup, M., Brown, N., Konrad, K., & Van Lente, H. (2006). The sociology of expectations in science and technology. Technology Analysis & Strategic Management, 18(3-4), 285-298.
Cash, D. W., Clark, W. C., Alcock, F., Dickson, N. M., Eckley, N., Guston, D. H., ... & Mitchell, R. B. (2003). Knowledge systems for sustainable development. Proceedings of the National Academy of Sciences, 100(14), 8086-8091.
Collins, H. M. (1985). Changing order: Replication and induction in scientific practice. University of Chicago Press.
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Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Davidson, E. A., & Janssens, I. A. (2006). Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature, 440(7081), 165-173.
Edwards, P. N. (2010). A vast machine: Computer models, climate data, and the politics of global warming. MIT Press.
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Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L., Beatty, J., & Kruger, L. (1989). The empire of chance: How probability changed science and everyday life. Cambridge University Press.
Goshu, B. S. and M. Ridwan (2026). Carbon Dioxide Utilization and Removal: Building Circular Carbon Economy, Economit Journal: Scientific Journal of Accountancy, Management and Finance, 6(3), 199-226.
Goshu, B.S. (2026b), Carbon, Capital, and Concepts: A Review of New Social Science Vocabularies in the Globalisation–Climate Change Debate, Britain International of Exact Sciences (BIoEx) Journal, 8 (2), 179-193
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Goshu, B.S. and M. Ridwan, (2026b), The Growth-Emissions Paradox: Assessing the Offset of Climate Mitigation by Economic Expansion in Ethiopia, Economit Journal: Scientific Journal of Accountancy, Management and Finance, 6(1), 64-85
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Hallegatte, S. (2009). Strategies to adapt to an uncertain climate change. Global Environmental Change, 19(2), 240-247.
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Hawkins, E., & Sutton, R. (2009). The potential to narrow uncertainty in regional climate predictions. Bulletin of the American Meteorological Society, 90(8), 1095-1107.
Heink, U., Marquard, E., Heubach, K., Jax, K., Kugel, C., Neßhöver, C., ... & Vandewalle, M. (2015). Conceptualizing credibility, relevance and legitimacy for evaluating the effectiveness of science-policy interfaces. Environmental Science & Policy, 54, 268-277.
Heymann, M., Gramelsberger, G., & Mahony, M. (Eds.). (2017). Cultures of prediction in atmospheric and climate science. Routledge.
Hulme, M. (2009). Why we disagree about climate change: Understanding controversy, inaction and opportunity. Cambridge University Press.
Israel, A., Hite, A., & Lemos, M. C. (2019). The spatial dimension of climate change vulnerability: A review of the literature. Wiley Interdisciplinary Reviews: Climate Change, 10(5), e597.
Jasanoff, S. (Ed.). (2004). States of knowledge: The co-production of science and social order. Routledge.
Jasanoff, S., & Kim, S.-H. (Eds.). (2015). Dreamscapes of modernity: Sociotechnical imaginaries and the fabrication of power. University of Chicago Press.
Kirschbaum, M. U. F. (1995). The temperature dependence of soil organic matter decomposition, and the effect of global warming on soil organic C storage. Soil Biology and Biochemistry, *27*(6), 753-760.
Knight, J. (2022). Interdisciplinary collaboration in quantum research: A case study of quantum computing for climate science. [Master's thesis, Harvard University].
Knorr Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Harvard University Press.
Knutti, R., Rugenstein, M. A., & Hegerl, G. C. (2017). Beyond equilibrium climate sensitivity. Nature Geoscience, 10(10), 727-736.
Lahsen, M. (2005). Seductive simulations? Uncertainty distribution around climate models. Social Studies of Science, 35(6), 895-922.
Lal, R., Delgado, J. A., Groffman, P. M., Millar, N., Dell, C., & Rotz, A. (2011). Management to mitigate and adapt to climate change. Journal of Soil and Water Conservation, 66(4), 276-285.
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Harvard University Press.
Lloyd, J., & Taylor, J. A. (1994). On the temperature dependence of soil respiration. Functional Ecology, 8(3), 315-323.
Mahony, M. (2014). The predictive state: Science, territory and the future of the Indian climate. Social Studies of Science, *44*(1), 109-133.
Matthews, H. D., Tokarska, K. B., Nicholls, Z. R. J., Rogelj, J., Canadell, J. G., Friedlingstein, P., & Knutti, R. (2020). Opportunities and challenges in using remaining carbon budgets to guide climate policy. Nature Geoscience, 13(12), 769-779.
Murray, B. J., O'Sullivan, D., Atkinson, J. D., & Webb, M. E. (2012). Ice nucleation by particles immersed in supercooled cloud droplets. Chemical Society Reviews, 41(19), 6519-6554.
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O'Brien, K. (2012). Global environmental change II: From adaptation to deliberate transformation. Progress in Human Geography, 36(5), 667-676.
Oppenheimer, M., O'Neill, B. C., Webster, M., & Agrawala, S. (2007). Climate change: The limits of consensus. Science, 317(5844), 1505-1506.
Oreskes, N., & Conway, E. M. (2010). Merchants of doubt: How a handful of scientists obscured the truth on issues from tobacco smoke to global warming. Bloomsbury Press.
Oreskes, N., Shrader-Frechette, K., & Belitz, K. (1994). Verification, validation, and confirmation of numerical models in the Earth sciences. Science, 263(5147), 641-646.
Owen, R., Macnaghten, P., & Stilgoe, J. (2012). Responsible research and innovation: From science in society to science for society. Science and Public Policy, 39(6), 751-760.
Peel, J., & Osofsky, H. M. (2015). Climate change litigation. Cambridge University Press.
Preskill, J. (2018). Quantum computing in the NISQ era and beyond. Quantum, 2, 79.
Rogelj, J., Forster, P. M., Kriegler, E., Smith, C. J., & Séférian, R. (2019). Estimating and tracking the remaining carbon budget for stringent climate targets. Nature, 571(7765), 335-342.
Sabatier, P. A., & Weible, C. M. (Eds.). (2014). Theories of the policy process (3rd ed.). Westview Press.
Schlosberg, D., & Collins, L. B. (2014). From environmental to climate justice: Climate change and the discourse of environmental justice. Wiley Interdisciplinary Reviews: Climate Change, 5(3), 359-374.
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Shackley, S., & Wynne, B. (1996). Representing uncertainty in global climate change science and policy: Boundary-ordering devices and authority. Science, Technology, & Human Values, 21(3), 275-302.
Shue, H. (2019). Climate justice: The ethics of climate change. Annual Review of Environment and Resources, 44, 329-351.
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Stern, N. (2007). The economics of climate change: The Stern review. Cambridge University Press.
Stilgoe, J., Owen, R., & Macnaghten, P. (2013). Developing a framework for responsible innovation. Research Policy, 42(9), 1568-1580.
Storelvmo, T., Kristjansson, J. E., Lohmann, U., Iversen, T., Kirkevåg, A., & Seland, Ø. (2014). Modeling of the Wegener-Bergeron-Findeisen process: Implications for aerosol indirect effects. Environmental Research Letters, 9(7), 074023.
Sundberg, M. (2007). Parameterizations in climate models: A perspective on the construction of scientific knowledge. Perspectives on Science, 15(4), 434-464.
van der Sluijs, J. P., Craye, M., Funtowicz, S., Kloprogge, P., Ravetz, J., & Risbey, J. (2005). Combining quantitative and qualitative measures of uncertainty in model-based environmental assessment: The NUSAP system. Risk Analysis, 25(2), 481-492.
Wynne, B. (1992). Uncertainty and environmental learning: Reconceiving science and policy in the preventive paradigm. Global Environmental Change, 2(2), 111-127.
Yin, R. K. (2014). Case study research: Design and methods (5th ed.). SAGE Publications.
Adger, W. N., Paavola, J., Huq, S., & Mace, M. J. (Eds.). (2006). Fairness in adaptation to climate change. MIT Press.
Asayama, S., Bellamy, R., Geden, O., Pearce, W., & Hulme, M. (2019). Why setting a climate deadline is dangerous. Nature Climate Change, 9(8), 570-572.
Barnes, B. (1974). Scientific knowledge and sociological theory. Routledge.
Bauer, B., Bravyi, S., Motta, M., & Chan, G. K.-L. (2020). Quantum algorithms for quantum chemistry and quantum materials science. Chemical Reviews, 120(22), 12685-12717.
Beck, S. (2011). Moving beyond the linear model of expertise? IPCC and the test of adaptation. Regional Environmental Change, 11(2), 297-306.
Beck, S., Borie, M., Chilvers, J., Esguerra, A., Heubach, K., Hulme, M., Lidskog, R., Lövbrand, E., Marquard, E., Miller, C., Nadim, T., Nesshöver, C., Settele, J., Turnhout, E., van der Hel, S., & Görg, C. (2014). Towards a reflexive turn in the governance of global environmental expertise: The cases of the IPCC and the IPBES. GAIA – Ecological Perspectives for Science and Society, 23(2), 90-93.
Bevir, M. (2012). Governance: A very short introduction. Oxford University Press.
Bloor, D. (1976). Knowledge and social imagery. Routledge.
Borup, M., Brown, N., Konrad, K., & Van Lente, H. (2006). The sociology of expectations in science and technology. Technology Analysis & Strategic Management, 18(3-4), 285-298.
Cash, D. W., Clark, W. C., Alcock, F., Dickson, N. M., Eckley, N., Guston, D. H., ... & Mitchell, R. B. (2003). Knowledge systems for sustainable development. Proceedings of the National Academy of Sciences, 100(14), 8086-8091.
Collins, H. M. (1985). Changing order: Replication and induction in scientific practice. University of Chicago Press.
Collins, H. M., & Evans, R. (2002). The third wave of science studies: Studies of expertise and experience. Social Studies of Science, 32(2), 235-296.
Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Davidson, E. A., & Janssens, I. A. (2006). Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature, 440(7081), 165-173.
Edwards, P. N. (2010). A vast machine: Computer models, climate data, and the politics of global warming. MIT Press.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins, W., ... & Rummukainen, M. (2013). Evaluation of climate models. In T. F. Stocker et al. (Eds.), Climate change 2013: The physical science basis (pp. 741-866). Cambridge University Press.
Gieryn, T. F. (1983). Boundary-work and the demarcation of science from non-science: Strains and interests in professional ideologies of scientists. American Sociological Review, 48(6), 781-795.
Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L., Beatty, J., & Kruger, L. (1989). The empire of chance: How probability changed science and everyday life. Cambridge University Press.
Goshu, B. S. and M. Ridwan (2026). Carbon Dioxide Utilization and Removal: Building Circular Carbon Economy, Economit Journal: Scientific Journal of Accountancy, Management and Finance, 6(3), 199-226.
Goshu, B.S. (2026b), Carbon, Capital, and Concepts: A Review of New Social Science Vocabularies in the Globalisation–Climate Change Debate, Britain International of Exact Sciences (BIoEx) Journal, 8 (2), 179-193
Goshu, B.S. and M. Ridwan, (2026a), Hydroclimate Vulnerability and Water Security of Croplands in a Semi-Arid City: A Case Study of Dire Dawa, Ethiopia, Britain International of Exact Sciences (BIoEx) Journal, 8 (1), 73-100
Goshu, B.S. and M. Ridwan, (2026b), The Growth-Emissions Paradox: Assessing the Offset of Climate Mitigation by Economic Expansion in Ethiopia, Economit Journal: Scientific Journal of Accountancy, Management and Finance, 6(1), 64-85
Goshu, B.S., (2026), From Billions of Seedlings to Sustainable Livelihoods: A Critical Review of Ethiopia's Green Economy Strategy, Afforestation Outcomes, and Community Co-Benefits, Rowter Journal, 5 (1), 68-89
Hacking, I. (1999). The social construction of what? Harvard University Press.
Hallegatte, S. (2009). Strategies to adapt to an uncertain climate change. Global Environmental Change, 19(2), 240-247.
Hansen, J. (2019). Democratizing expertise: The epistemic politics of climate modeling. [Doctoral dissertation, University of California, Berkeley].
Hawkins, E., & Sutton, R. (2009). The potential to narrow uncertainty in regional climate predictions. Bulletin of the American Meteorological Society, 90(8), 1095-1107.
Heink, U., Marquard, E., Heubach, K., Jax, K., Kugel, C., Neßhöver, C., ... & Vandewalle, M. (2015). Conceptualizing credibility, relevance and legitimacy for evaluating the effectiveness of science-policy interfaces. Environmental Science & Policy, 54, 268-277.
Heymann, M., Gramelsberger, G., & Mahony, M. (Eds.). (2017). Cultures of prediction in atmospheric and climate science. Routledge.
Hulme, M. (2009). Why we disagree about climate change: Understanding controversy, inaction and opportunity. Cambridge University Press.
Israel, A., Hite, A., & Lemos, M. C. (2019). The spatial dimension of climate change vulnerability: A review of the literature. Wiley Interdisciplinary Reviews: Climate Change, 10(5), e597.
Jasanoff, S. (Ed.). (2004). States of knowledge: The co-production of science and social order. Routledge.
Jasanoff, S., & Kim, S.-H. (Eds.). (2015). Dreamscapes of modernity: Sociotechnical imaginaries and the fabrication of power. University of Chicago Press.
Kirschbaum, M. U. F. (1995). The temperature dependence of soil organic matter decomposition, and the effect of global warming on soil organic C storage. Soil Biology and Biochemistry, *27*(6), 753-760.
Knight, J. (2022). Interdisciplinary collaboration in quantum research: A case study of quantum computing for climate science. [Master's thesis, Harvard University].
Knorr Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Harvard University Press.
Knutti, R., Rugenstein, M. A., & Hegerl, G. C. (2017). Beyond equilibrium climate sensitivity. Nature Geoscience, 10(10), 727-736.
Lahsen, M. (2005). Seductive simulations? Uncertainty distribution around climate models. Social Studies of Science, 35(6), 895-922.
Lal, R., Delgado, J. A., Groffman, P. M., Millar, N., Dell, C., & Rotz, A. (2011). Management to mitigate and adapt to climate change. Journal of Soil and Water Conservation, 66(4), 276-285.
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Harvard University Press.
Lloyd, J., & Taylor, J. A. (1994). On the temperature dependence of soil respiration. Functional Ecology, 8(3), 315-323.
Mahony, M. (2014). The predictive state: Science, territory and the future of the Indian climate. Social Studies of Science, *44*(1), 109-133.
Matthews, H. D., Tokarska, K. B., Nicholls, Z. R. J., Rogelj, J., Canadell, J. G., Friedlingstein, P., & Knutti, R. (2020). Opportunities and challenges in using remaining carbon budgets to guide climate policy. Nature Geoscience, 13(12), 769-779.
Murray, B. J., O'Sullivan, D., Atkinson, J. D., & Webb, M. E. (2012). Ice nucleation by particles immersed in supercooled cloud droplets. Chemical Society Reviews, 41(19), 6519-6554.
Nordhaus, W. D. (2013). The climate casino: Risk, uncertainty, and economics for a warming world. Yale University Press.
O'Brien, K. (2012). Global environmental change II: From adaptation to deliberate transformation. Progress in Human Geography, 36(5), 667-676.
Oppenheimer, M., O'Neill, B. C., Webster, M., & Agrawala, S. (2007). Climate change: The limits of consensus. Science, 317(5844), 1505-1506.
Oreskes, N., & Conway, E. M. (2010). Merchants of doubt: How a handful of scientists obscured the truth on issues from tobacco smoke to global warming. Bloomsbury Press.
Oreskes, N., Shrader-Frechette, K., & Belitz, K. (1994). Verification, validation, and confirmation of numerical models in the Earth sciences. Science, 263(5147), 641-646.
Owen, R., Macnaghten, P., & Stilgoe, J. (2012). Responsible research and innovation: From science in society to science for society. Science and Public Policy, 39(6), 751-760.
Peel, J., & Osofsky, H. M. (2015). Climate change litigation. Cambridge University Press.
Preskill, J. (2018). Quantum computing in the NISQ era and beyond. Quantum, 2, 79.
Rogelj, J., Forster, P. M., Kriegler, E., Smith, C. J., & Séférian, R. (2019). Estimating and tracking the remaining carbon budget for stringent climate targets. Nature, 571(7765), 335-342.
Sabatier, P. A., & Weible, C. M. (Eds.). (2014). Theories of the policy process (3rd ed.). Westview Press.
Schlosberg, D., & Collins, L. B. (2014). From environmental to climate justice: Climate change and the discourse of environmental justice. Wiley Interdisciplinary Reviews: Climate Change, 5(3), 359-374.
Schuur, E. A. G., McGuire, A. D., Schädel, C., Grosse, G., Harden, J. W., Hayes, D. J., ... & Vonk, J. E. (2015). Climate change and the permafrost carbon feedback. Nature, 520(7546), 171-179.
Shackley, S., & Wynne, B. (1996). Representing uncertainty in global climate change science and policy: Boundary-ordering devices and authority. Science, Technology, & Human Values, 21(3), 275-302.
Shue, H. (2019). Climate justice: The ethics of climate change. Annual Review of Environment and Resources, 44, 329-351.
Star, S. L., & Griesemer, J. R. (1989). Institutional ecology, 'translations' and boundary objects: Amateurs and professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39. Social Studies of Science, 19(3), 387-420.
Stern, N. (2007). The economics of climate change: The Stern review. Cambridge University Press.
Stilgoe, J., Owen, R., & Macnaghten, P. (2013). Developing a framework for responsible innovation. Research Policy, 42(9), 1568-1580.
Storelvmo, T., Kristjansson, J. E., Lohmann, U., Iversen, T., Kirkevåg, A., & Seland, Ø. (2014). Modeling of the Wegener-Bergeron-Findeisen process: Implications for aerosol indirect effects. Environmental Research Letters, 9(7), 074023.
Sundberg, M. (2007). Parameterizations in climate models: A perspective on the construction of scientific knowledge. Perspectives on Science, 15(4), 434-464.
van der Sluijs, J. P., Craye, M., Funtowicz, S., Kloprogge, P., Ravetz, J., & Risbey, J. (2005). Combining quantitative and qualitative measures of uncertainty in model-based environmental assessment: The NUSAP system. Risk Analysis, 25(2), 481-492.
Wynne, B. (1992). Uncertainty and environmental learning: Reconceiving science and policy in the preventive paradigm. Global Environmental Change, 2(2), 111-127.
Yin, R. K. (2014). Case study research: Design and methods (5th ed.). SAGE Publications.