Mathematics 2021, 9, 2920. https://doi.org/10.3390/math9222920 www.mdpi.com/journal/mathematics Article Mathematical Modelling of Climate Change and Variability in the Context of Outdoor Ergonomics Sergei Soldatenko *, Alexey Bogomolov and Andrey Ronzhin St. Petersburg Federal Research Center of the Russian Academy of Sciences; Russia, 199178 St. Petersburg, Russia; a.v.bogomolov@gmail.com (A.B.); ronzhin@iias.spb.su (A.R.) * Correspondence: soldatenkol@iias.spb.su; Tel.: +7‐(931)‐354‐0598 Abstract: The current climate change, unlike previous ones, is caused by human activity and is characterized by an unprecedented rate of increase in the near‐surface temperature and an increase in the frequency and intensity of hazardous weather and climate events. To survive, society must be prepared to implement adaptation strategies and measures to mitigate the negative effects of climate change. This requires, first of all, knowledge of how the climate will change in the future. To date, mathematical modelling remains the only method and effective tool that is used to predict the climate system’s evolution under the influence of natural and anthropogenic perturbations. It is important that mathematics and its methods and approaches have played a vital role in climate research for several decades. In this study, we examined some mathematical methods and ap‐ proaches, primarily, mathematical modelling and sensitivity analysis, for studying the Earth’s climate system, taking into account the dependence of human health on environmental conditions. The essential features of stochastic climate models and their application for the exploration of cli‐ mate variability are examined in detail. As an illustrative example, we looked at the application of a low‐order energy balance model to study climate variability. The effects of variations in feedbacks and the climate system’s inertia on the power spectrum of global mean surface temperature fluc‐ tuations that characterized the distribution of temperature variance over frequencies were esti‐ mated using a sensitivity analysis approach. Our confidence in the obtained results was based on the satisfactory agreement between the theoretical power spectrum that was derived from the energy balance model and the power spectrum that was obtained from observations and coupled climate models, including historical runs of the CMIP5 models. Keywords: outdoor ergonomics; climate change; climate variability; mathematical modelling; sensitivity analysis; dynamical systems; stochastic models 1. Introduction Mathematics represents a very effective and powerful instrument for comprehend‐ ing the world and solving complex problems in various sciences, engineering and tech‐ nologies (e.g., [1–4]). In this aspect, one cannot underestimate the essential role of mathematics in solving planetary problems, among which, the problem of the interaction between society and nature stands out [5,6]. Humans live and execute their diverse and multifaceted activities in interaction with the environment. On the one hand, humans affect the environment, changing its properties; on the other hand, environmental con‐ ditions affect humans, in particular, their health and even their ability to survive. At the turn of the millennium, humankind is clearly faced with a new pressing challenge posed by climate change. Current climate change, unlike previous ones, is human‐induced [7,8] and characterized by an unprecedented rate of increase in the global mean surface tem‐ perature (GMST). A report [9] stated that since 1880, the GMST has increased by an av‐ erage of 0.07 °C per decade. Meanwhile, the growth rate of the GMST in the first two Citation: Soldatenko, S.; Bogomolov, A.; Ronzhin, A. Mathematical Modelling of Climate Change and Variability in the Context of Outdoor Ergonomics. Mathematics 2021, 9, 2920. https://doi.org/10.3390/math9222920 Academic Editor: Arturo Hidalgo Received: 26 October 2021 Accepted: 13 November 2021 Published: 16 November 2021 Publisher’s Note: MDPI stays neu‐ tral with regard to jurisdictional claims in published maps and insti‐ tutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses /by/4.0/).