 In addition, climate models are used to make predictions. It might be thought that, due to chaos, climate prediction is impossible. But chaos is an obstacle to precisely predicting the trajectory of a system—the time-ordered sequence of its states over a period—not (necessarily) for predicting the statistical properties of one or more trajectories; climate prediction is concerned with the latter. Short-term predictions of climate for periods ranging from a year to a decade or so are made with both physics-based and empirical models (e.g., Meehl et al. 2014; Krueger &amp; von Storch 2011). For these predictions, assumptions are made about what external conditions actually will be like over the forecast period, and the forecasts begin from an observationally-based estimate of the recent state of the climate system. Better known, however, is the use of climate models to make longer-term conditional predictions, known as projections. These are predictions of what future climate would be like under particular external condition scenarios, without assuming that any of those scenarios will actually occur, and they are often launched from an initial state that is meant to be representative of the climate at the start of the simulated period, though not estimated directly from observations (see  Section 4.4).  Climate change projections have become a major focus of climate research and will be discussed further in  Section 5.2  below.