Michael Morris, Paul J. Kushner, and Karen L. Smith
Version 1.1.0 -- Last updated 3 July 2024
Welcome to the Guidebook for the University of Toronto Climate Downscaling Workflow. If you're accessing these resources, it means you are interested in using data to study how climate change may affect a particular domain in the built or natural environment. The purpose of the UTCDW Guidebook is to help you develop the skills and knowledge needed to design and conduct a climate change impact analysis study and perform your own statistical downscaling of climate model data. This Guidebook takes advantage of the Jupyter Book format to intermix text explaining concepts and methods with code that demonstrates application.
The target audience for the UTCDW Guidebook is a researcher with little or no foundation in climate science, who studies a system that is sensitive to weather and climate. This could be, for example, an engineer who studies building energy use, which depends on climatic variables such as temperature and humidity. In order to quantitatively study how climate change might affect the system you study and properly interpret the results, you need some basic knowledge of the climate system and climate modeling.
We start with basic background on the climate system and climate modeling, before developing skills in climate impacts analysis. This includes background on how climate change projections are produced, sources of uncertainty and limitations of climate projections, and the type and structure of available data from the projections. We will learn why raw data from climate model projections is usually unsuitable for regional climate impact assessment, and why post-processing (downscaling) must be applied to account for systematic biases and coarse spatial sampling.
The UTCDW Guidebook illustrates these concepts through hands on coded examples in which you, the audience, will access and analyze climate data. It will then guide you through the process of downscaling, explaining both the theoretical background and many examples of how downscaling works in practice. Through this process, and using our UTCDW Survey tool on the website, you will be learn how to develop your own climate downscaling workflow for your system of interest.
The UTCDW Guidebook provides educational material to help you design and conduct your own analyses, but does not give detailed guidance on any specific research problem. It provides general guidance and a few examples, but there are too many possible applications of climate downscaling to be exhaustive. Notably, we cannot tell you how your domain application is sensitive to climatic factors. As the expert on the system you study, it's up to you to have a sense of the important climate variables for your application, and how you might quantify the way weather and climate affect your study system. If you require climate data as inputs to a model (for example, a model that calculates building energy use as a function of outside temperature and humidity), then you should be familiar with which input variables are required, and at what spatial and temporal sampling. The survey on the UTCDW website will guide you through the factors that must be condsidered when designing a climate downscaling study. We call the quantity which depends on climate variables, and is relevant for your domain application, a "climate indicator", whether it's calculated using an analytic expression or a complex numerical model. Climate indicators and the other preliminary study design decisions will be discussed further in Chapter 5, but it's important to know from the start that this guide assumes you have a way to quantify how your study system depends on climatic factors.
If you encounter a problem with the UTCDW Guidebook, would like to make suggestions on how to improve it, or otherwise would like to contact the authors, please use the Feedback page of the main UTCDW website. We invite you to contribute to the UTCDW Guidebook by making a Pull Request through the Github Repository that hosts the files that comprise the UTCDW Guidebook. If you're not familiar with Git, then you're welcome to use the Feedback page instead.
The contents of the UTCDW Guidebook were written predominantly by Michael Morris. This work was performed under the supervision of Professor Paul J. Kushner, who conceived of the project and provided feedback, and Professor Karen L. Smith, who provided content suggestions and feedback for most chapters. Special thanks to Aleksandra Elias Chereque, Cassandra Chanen and Lilian Chan who tested early iterations of the materials. Extra special thanks to Julian Comanean, who coded the UTCDW website and the guided survey/flowchart generator, and designed the UTCDW logo.
Funding for this project was provided by the Centre for Climate Science and Engineering, Climate Positive Energy, and the University of Toronto Data Sciences Institute.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
