Climate Science and Control Engineering: Insights, Parallels, and Connections

Abstract

Climate science is the multidisciplinary field that studies the Earth's climate and its evolution. At the very core of climate science are indispensable climate models that predict future climate scenarios, inform policy decisions, and dictate how a country's economy should change in light of the changing climate. Climate models capture a wide range of interacting dynamic processes via extremely complex ordinary and partial differential equations. To model these large-scale complex processes, climate science leverages supercomputers, advanced simulations, and statistical methods to predict future climate. An area of engineering that is rarely studied in climate science is control engineering. Given that climate systems are inherently dynamic, it is intuitive to analyze them within the framework of dynamic system science. This perspective has been underexplored in the literature. In this manuscript, we provide a tutorial that: (i) introduces the control engineering community to climate dynamics and modeling, including spatiotemporal scales and challenges in climate modeling; (ii) offers a fresh perspective on climate models from a control systems viewpoint; and (iii) explores the relevance and applicability of various advanced graph and network control-based approaches in building a physics-informed framework for learning, control and estimation in climate systems. We also present simple and then more complex climate models, depicting fundamental ideas and processes that are instrumental in building climate change projections. This tutorial also builds parallels and observes connections between various contemporary problems at the forefront of climate science and their control theoretic counterparts. We specifically observe that an abundance of climate science problems can be linguistically reworded and mathematically framed as control theoretic ones.

Figures (10)

• Figure 1: Climate as a dynamic system. In this tutorial, we explain how the Earth’s climate can be viewed as a complex dynamical system with inputs, outputs, internal states, and external disturbances. We describe how the key components of the climate system---atmosphere, hydrosphere, cryosphere, biosphere, and land surface---interact and evolve over time. We cover the roles of natural and anthropogenic inputs (e.g., solar radiation, green infrastructure, and natural variability) and disturbances (e.g., emissions and deforestation), and how they influence the system’s trajectory. We delineate the different types and levels of climate models and highlight how those models map the climate inputs and disturbances to evolving states and observable outputs such as global average temperature, in the form of scenario-based simulations and projections. Throughout the tutorial, we highlight and examine these dynamic processes through a control-theoretic lens and discuss how control tools can provide structure for understanding, simulating, and potentially influencing climate dynamics. We note here, as a much-needed disclaimer, that jointly modeling all of the dynamic system components and inputs/outputs in this figure is virtually impossible as such models would not be practical computationally. Climate models wisely stick to subsets of these interactions rather than the whole kitchen sink, and we, too, respect that wisdom (mostly). This tutorial offers only some perspectives that are neither complete nor extraordinary. It just makes climate science more accessible to control system researchers and hopes for more cross-disciplinary learning and developments.
• Figure 2: Projected global mean surface temperature changes relative to 1850--1900 levels under five emissions scenarios: very low emissions (SSP1-1.9), low emissions (SSP1-2.6), midlevel emissions (SSP2-4.5), high emissions (SSP3-7.0), and very high emissions (SSP5-8.5), illustrating the impact of different policy and socioeconomic pathways on future warming. Shading indicates 5% to 95% confidence intervals. Figure adapted from the IPCC Sixth Assessment Report (AR6) calvinIPCC2023Climate2023. This tutorial shows how these (now culturally mainstream) figures are generated via dynamic models in climate science.
• Figure 3: Tutorial summary and paper organization.
• Figure 4: Climate system's main five components and selected interactions between them (illustrative, not exhaustive).
• Figure 5: Key transitional milestones in the history of climate science.