Projections on projections: how do we know what we know about climate change?
We’ve developed increasingly accurate models for predicting climate shifts — and our knowledge and technology will only improve further. How will these projections advance in the near future?
We have known for years that the global climate is changing, though our understanding of the extent, the severity and regional differences has consistently improved. In the past year, two major United Nations (UN) reports have detailed risks associated with greenhouse gas emissions and ecosystem destruction with unprecedented force and clarity. Mainstream media, climate experts and political advisors are changing their terminology to be clearer, more precise and more forceful when discussing the “climate crisis” and “global heating” instead of “climate change” and “global warming.”
But how do we, as a society, know what we know about climate change? How are we getting a clearer understanding of future climate projections? How are our conversations about climate going to change?
Dr. Jamie Summers
Future Ready Program Consultant
Here are three areas in which we are advancing:
We are improving resolution and learning how to work on relevant scales. General Circulation Models (GCMs), which are considered to be the most advanced tools simulating global climate dynamics, are complex models that use three-dimensional grids over the globe to represent physical processes in the atmosphere, oceans, ice and land surface. These models are adept at allowing us to understand the global energy balance and broad-scale climate change. However, people and places feel and experience climate on smaller, more regional scales.
Modelling small-scale changes or highly variable systems requires parameterization, which is averaging local processes over larger areas. Through this downscaling, we lose accuracy. However, thanks to improving computing power, we’re getting better at including localized climate processes (e.g. air flow over mountains, local ocean currents and cloud effects) in models across finer scales. As we increase our capacity to represent and model regionally scaled processes, we sharpen our vision of future climate at a meaningful level.
We are improving how we understand relationships among multiple stressors and effects. Climate change is only one of the many stressors that affect environments and systems. Climate change is also multi-faceted, with different variables interacting synergistically or antagonistically – almost always yielding complicated consequences. Understanding the complex and sometimes confounding effects of interacting variables lays the foundation for effective management, planning and design.
With improved input data and computing power, we are getting better at exploring and understanding coupled systems, threshold responses and feedback loops. Accounting for interactions improves our ability to track cascading effects and accurately work within targets such as carbon budgets. For example, warming in parts of the Canadian Arctic spurs on permafrost degradation, which leads to surface instability, altered drainage and the release of sequestered greenhouse gases. Then, this release of greenhouse gases feeds back into a cycle of further temperature increases. While these dynamics will always be complex, ever-improving models and collaborations are providing more holistic answers to questions about non-linear, interacting systems and climate change effects.
We are improving how we work with uncertainty. It is not possible to flawlessly forecast the future. Therefore, tools and strategies that acknowledge the inevitable uncertainty and variability are valuable infrastructure for planning and management. For example, intensity-duration-frequency (IDF) curves are a commonly used tool in water infrastructure management (e.g., design and operation of sewers, basins, culverts, etc.) and are conventionally developed on the assumption that extreme rainfalls have constant averages over time (termed climate stationarity). Climate change challenges this assumption; yet, IDF curves remain useful tools for resilient water management when we reduce and acknowledge the uncertainty through the use of up-to-date observational data and climate models (read: our Insights article, “Predicting the unpredictable: innovative methods in flood risk management”). As we layer data, projections and tools, we build redundancy and verification points into our work.
As our improved ways of working with more resolution, complex interactions and uncertainty help us to get clearer on future climate conditions and related effects, our communication on the topic changes too. We’re seeing international bodies and mainstream media using more direct and urgent language. We expect tomorrow’s conversations and solutions on climate change to be more sophisticated and, hopefully, more empowered.
We know, from general advertising and specific studies on climate change communication, that motivating messages are personal, localized, focused on the present and positive. As we learn more about how and why our climate is changing, we not only have the opportunity to engineer ever-better responses, we have the chance to shape the dialogue and set the tone.
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Through Future Ready®, WSP brings clarity and vision to complex challenges. We see the future more clearly through key trends in climate change, society, technology and resources, and challenge staff to work with our clients to advise on solutions that are both ready for today and for this future. Future Ready delivers peace of mind, lower lifecycle costs and resilience.
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