the same sites, we observe warming and an increase in SST through the spring and into the summer followed by cooling and a decrease in SST through the fall and winter. These changes in SST occur in concert with seasonal changes in surface winds. These types of day-to-day and season-to-season variability, caused by strong, regular, and periodic external forcing from the sun can be accurately predicted.
But beyond these daily and seasonal cycles, the dynamics of the climate system are more complex and incompletely understood, challenging our efforts to make predictions. For example, to answer a question like “Will the upcoming winter be colder or wetter than usual?” requires an understanding of climate variability on the timescales of weeks, months, and years. This variability stems from the atmosphere, the ocean, the land, and the coupling between them. How these components of the climate system interact and affect one another can be understood by examining how they exchange heat, moisture, and momentum. For example, the ocean absorbs heat from the sun and can also transport that heat and release it elsewhere on the earth’s surface. At mid- and high-latitudes, cooling and evaporation make surface water denser and, through convection, force surface water into the ocean’s interior. Both the density differences in the ocean and the action of the wind on the sea surface drive a global, three-dimensional circulation in the ocean that results in spatial and temporal variability in SST. Likewise, solar heating and turbulent heat and moisture fluxes at the ocean and land surfaces drive atmospheric circulations on a wide range of scales from global to local. Moist, warm parcels of air near the surface become buoyant, and this convection can communicate the influence of the surface broadly through the atmosphere and, in turn, to remote surface locations. In contrast, cooling or evaporation within the lower atmosphere stabilizes the atmospheric boundary layer locally and limits the ability of the surface to force the atmosphere elsewhere.
The ability of the atmosphere, ocean, and land to interact and affect one another occurs over a broad range of spatial scales and timescales. These interactions give rise to complex, often nonlinear, dynamics making it difficult to understand and predict the climate variability that we observe. While much progress has been made extending weather forecast skill to a week or more, the ability to make predictions on timescales longer than two weeks is still limited. At shorter timescales, most of the important dynamics reside within the atmosphere. But for longer timescales, the storage of heat and moisture by the ocean and the land becomes more important. Unfortunately, we have less information about the ocean and the land than we have about the atmosphere, and we often lack a full understanding of the interactions among the three.
Historically, deterministic “predictability” of chaotic systems like day-to-day weather processes has referred to how relatively small errors in the initial conditions lead to relatively large forecast errors some time later—typically 10–14 days. Although developed in the context of weather prediction, this concept of deterministic predictability has also been applied to predictions of the entire climate system, including those on ISI timescales. However, over time, the term “predictability” has been used in confusing ways in the atmospheric and oceanic literature. In this report, the term “predictability” is used qualitatively to describe the extent to which the representation of a physical process can contribute to and perhaps even improve prediction quality. There are two important aspects of the committee’s approach to the concept