MELINDA M. HALL
Natural variability in the ocean has periods ranging from seconds to millennia. Those phenomena that have the most obvious impact on human affairs tend to recur periodically as well: daily, such as the tides; sporadically, such as storm surges or tsunamis; and seasonally, such as the simple warming of coastal waters in summer. Most of these events are predictable to varying degrees. It is now recognized that occurrences of the El Niño-Southern Oscillation (ENSO), a phenomenon of global scale that has tremendous socioeconomic consequences, are quasi-periodic (over a term of several years) and are therefore within the realm of predictability as well. Our understanding of these examples of natural variability, and hence our ability to predict them, are derived from our past experience with them—in other words, repeated observations of the same event—as well as from theoretical models based on ocean physics. Identifying the effects of anthropogenically induced changes in the ocean is a subtle problem, for there are few precedents against which models can be tested. But a prerequisite for prediction in any case is a knowledge of the natural variability inherent in the system, and an understanding of the physics that drives that variability.
The study of natural variability at periods of decades to centuries presents particular challenges. A primary difficulty derives from the fact that the observed variability that we surmise to be associated with climate change is generally smaller in magnitude than variability due to other causes, and is sometimes at the limits of instrumental accuracy. Long time series are therefore required to deconvolve its signal from the much more energetic influences of seasonal and other types of variability. Long in situ records are inherently difficult to obtain, however, due to the hostile nature of the very environment we are trying to observe. Indeed, because oceanographic data will never be quite complete enough to ''solve" the problem, there is a natural interdependency between the observations and modeling efforts. Models can provide globally complete fields, but data will always be required for their initialization, calibration, and validation.
On the other hand, regarding the observational effort, it is important to note that oceanographic variability tied to atmospheric forcing may be much stronger in isolated areas. For example, it is now recognized that the production of deep water in the northern North Atlantic is intimately related to the global climate, and thus changes in its production are either the result of, or harbingers of, more widely spread climate changes. Although it is almost impossible to directly measure the amounts of water convectively overturned each year, much qualitative and some quantitative information regarding production in previous years can be inferred from an examination of the variability of water properties at locations downstream from the source waters, in the deep western boundary current that carries these waters to the mid-ocean. Swift (1995) clearly outlines these arguments; focusing particularly on the deep-water formation in the northern North Atlantic, he provides a good introduction to how one documents, studies, and interprets decadal changes.