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What is climate? What is a model? How do we describe the uncertainty in a model? This chapter introduces key terms and concepts. We start with basic definitions of climate and weather. Then, we discuss models. Even if we do not realize it, we use models all the time. So we describe a few different conceptual types of models and put climate models in context. Finally we introduce the concept of uncertainty. As we discuss later in the book, models may have errors and still be useful, but this requires understanding the errors (the uncertainties) and understanding where they come from. These concepts are common to many types of modeling.
There is quite a bit of statistics in climate, by definition. For a technical background, a good reference is Devore, J. L. (2011). Probability and Statistics for Engineering and the Sciences, 8th ed. Duxbury, MA: Duxbury Press. Any specific aspect of statistics (e.g., standard deviation, probability distribution function) can be looked up on Wikipedia ( www.wikipedia.com).
For an overview of the history of weather forecasting, see Edwards, P. N. (2013). A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming. Cambridge, MA: MIT Press.
This definition of uncertainty has been developed by Hawkins, E., & Sutton, R. (2009). “The Potential to Narrow Uncertainty in Regional Climate Prediction.” Bulletin of the American Meteorological Society, 90(8): 1095–1107.
For a discussion of climate scenarios, see Chap. 10.
- Key Concepts in Climate Modeling
Richard B. Rood
- Springer Berlin Heidelberg
- Chapter 1