Cybernetic Approach to Problem of Interaction Between Nature and Human Sosiety in Context of Unprecedented Climate Change
Keywords:
Geophysical Cybernetics, Global Warming, Climate Change Economics, Geoengineering, Climate Engineering, Feedbacks, Optimal ControlAbstract
In this paper, from a cybernetic perspective, the human-nature interactions are considered in the context of modern climate change, unprecedented in its scale and rate caused by anthropogenic activity. The developed structure of the “climate-economy” cybernetic system is presented, the weaknesses of the global governance bodies are analysed, and the main causes of the uncertainties in assessing climate change and the economic damage caused by this change are discussed. It is noted that adaptation measures and strategies developed and implemented by governments of different countries and intergovernmental organizations do not eliminate the causes of global warming and, therefore, have limited capacities, since humans and nature can exist only under specified environmental conditions. Going beyond these conditions, due to climate change, can lead to a global biological catastrophe. Climate policy decisions are made under uncertainty due to the ambiguity of estimates of the future climate, which, in turn, is the result of an insufficiently adequate description of feedbacks in the climate system models. Using low-parametric models of the Earth's climate system, the influence of system’s feedbacks on tangible inter-model differences of climate change estimates obtained using modern climate models of a high degree of complexity is illustrated. Since the climate change adaptation measures proposed by experts are not the struggle with causes, but the fight with consequences, we see geoengineering as a radical adaptation strategy. In contrast to previous studies, we consider the problem of purposefully modifying climatic conditions, implemented by geoengineering methods, within the framework of optimal control theory with mathematical formalization of geoengineering objectives and methods for achieving them. In this paper, an example of the formulation and solution of the optimization problem for stabilizing the Earth’s climate through the injection of finely dispersed sulfate aerosol into the stratosphere is presented.
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30. Rozenwasser E., Yusupov R. Sensitivity of automatic control systems // CRC Press. 2019. 456 p.
31. Soldatenko S.A., Yusupov R.M. Estimating the influence of thermal inertia and feedbacks in the atmosphere–ocean system on the variability of the global sur-face air temperature // Atmospheric and Oceanic Physics. 2019. vol. 56. pp. 591–601.
32. Soldatenko S., Colman R. Climate variability from annual to multi-decadal timescales in a two-layer stochastic energy balance model: analytic solutions and implications for general circulation models // Tellus A: Dynamic Meteorol-ogy and Oceanography. 2019. vol. 71. no. 1. pp. 1–15.
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35. Pindyck R.S. Climate change policy: What do the models tell us? // Journal of Economic Literature. 2013. vol. 51. pp. 860–872.
36. Lazo J.K., Lawson M., Larsen P.H., Waldman D.M. United States economic sensitivity to weather variability // Bulletin of the American Meteorological So-ciety. 2011. vol. 92. no. 6. pp. 709–720.
37. Crepin A.S., Karcher M., Gascard J.C. Arctic climate change, economy and society (ACCESS): Integrated perspectives // Ambio. 2017. vol. 46. no. 3. pp. 341–354.
38. Катцов В.М., Порфирьев Б.Н. Оценка макроэкономиеских последствий изменений климата на территории Российской Федерации на период до 2030 г. и дальнейшую перспективу (резюме доклада) // Труды Главной геофизической обсерватории им. А.И. Воейкова. 2011. № 563. С. 7–59.
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42. Kopp R.E. et al. Probabilistic 21st and 22nd century sea‐level projections at a global network of tide‐gauge sites // Earth Future. 2014. vol. 2. no. 8. pp. 383–406.
43. Taylor K.E., Stouffer R.J., Meehl G.A. An overview of CMIP5 and the experi-ment design // Bulletin of the American Meteorological Society. 2011. vol. 93. pp. 485–498.
44. Colman R.A., Power S.B. What can decadal variability tell us about climate feedbacks and sensitivity? // Climate Dynamics. 2018. vol. 51. pp. 3815–3828.
45. Soldatenko S.A. Estimated impacts of climate change on eddy meridional mois-ture transport in the atmosphere // Applied Sciences. 2019. vol. 9. no. 23. pp. 4992.
46. Ginzburg A.S., Demchenko P.F. Anthropogenic meso-meteorological feed-backs: A review of recent research // Atmospheric and Oceanic Physics. 2019. vol. 55. pp. 573–590.
47. Hasselmann K. Stochastic climate models. Part I. Theory // Tellus. 1976. vol. 28. pp. 473–485.
48. Middlemas E., Clement A. Spatial patterns and frequency of unforced decadal scale changes in global mean surface temperature in climate models // Journal of Climate. 2016. vol. 29. no. 17. pp. 6245–6257.
49. Geoffroy O. et al. Transient climate response in a two-layer energy-balance model. Part I: Analytical solution and parameter calibration using CMIP5 AOGCM ex¬periments // Journal of Climate. 2013. vol. 26. no. 6. pp. 1841–1857.
50. Demchenko P.F., Semenov V.A. Estimation of uncertainty in surface air tem-perature climatic trends related to the internal dynamics of the atmosphere // Doklady Earth Sciences. 2017. vol. 476. pp. 1105–1108.
51. Охтилев М.Ю. и др. Концепция и технологии проактивного управления жизненным циклом изделий // Известия высших учебных заведений. При-боростроение. 2020. Т. 63. № 1.
52. Ронжин А.Л. и др. Применение технологии радиочастотной идентифика-ции для построения системы контроля оборота бортового кухонного обо-рудования // Вопросы радиоэлектроники. Серия: Техника телевидения. 2020. Вып. 1. C. 3–10.
Published
2020-02-14
How to Cite
Soldatenko, S., Yusupov, R., & Colman, R. (2020). Cybernetic Approach to Problem of Interaction Between Nature and Human Sosiety in Context of Unprecedented Climate Change. SPIIRAS Proceedings, 19(1), 5-42. https://doi.org/10.15622/sp.2020.19.1.1
Section
Robotics, Automation and Control Systems
Copyright (c) 2020 Сергей Анатольевич Солдатенко, Юсупов Рафаэль Мидхатович Yusopov, Колман Роберт Colman
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