Chapter 2: Intro to Climate Science and Modeling

As a user of the UTCDW Guidebook, you likely have expertise in engineering, ecology, or some other field of study that has elements sensitive to the state of the climate, and your goal is to study how changes to the climate will affect some system you’re deeply familiar with. This type of work is referred to as climate change impact analysis. Before you can start doing serious work on a climate change impact analysis study, you need to have some background in climate science. Users without any previous experience working with climate change projections or climate science in general should stop here and work through Module 1: Introduction to Climate Science and Modeling from the Engineering in a Changing Climate e-Learning resource. This chapter will discuss similar material to the e-Learning module, but with less detail and interactiveness that would be highly beneficial to someone brand new to climate science.

Section 2.1 will begin the chapter by answering some questions like “what is climate?” and “how does the climate vary naturally”. You may feel confident in your answers to these questions already, but it is important to ensure all users are on the same page regarding these basics. A key takeaway from this section will be the distinction between natural climate variability and anthropogenic climate change - changes on interannual or even decadal timescales do not necessarily constitute evidence for or against human influence on the climate, as they are often a result of natural fluctuations in the climate.

Next Section 2.2 will introduce the tools and methods climate scientists use to make climate change projections: numerical climate models, also commonly referred to as GCMs (Global Climate Models) or ESMs (Earth System Models). These models are incredibly complex systems, so we cannot possibly go through every detail and aspect of the climate system that these models aim to represent, but rest assured we will provide enough information for you to have more than a surface-level understanding of what these models do. This section will also discuss their limitations, which are important to understand in order to interpret model output.

Speaking of limitations, all representations of physical systems, and all predictions and projections of the future, come with some degree of uncertainty. Section 2.3 will lay out the different sources of uncertainty in climate projections, and how climate scientists quantify them. As much as we would all like our analyses to produce clean results and definitive answers, it is often the case that a climate impact study will produce a range of possible outcomes, which stakeholders must then use to assess risks and possible courses of action.