Statistics in Oceanography

Authored by: Christopher K. Wikle

Handbook of Environmental and Ecological Statistics

Print publication date:  September  2017
Online publication date:  January  2019

Print ISBN: 9781498752022
eBook ISBN: 9781315152509
Adobe ISBN:


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The world’s oceans cover over 70 percent of the earth’s surface. These oceans, commonly believed to have spawned life over 3 billion years ago, are an immensely complex system, with critical interactions across the primary systems of the planet – the atmosphere, biosphere, and crysosphere. One of the most interesting (and challenging) aspects of the ocean is that it operates over an enormous range of spatial and temporal scales, and its interactions and internal dynamics can be highly nonlinear – which makes characterizing its interaction with these various systems very challenging. These challenges have traditionally been further exacerbated by the lack of in situ observations of the ocean state and ocean biology - with primary observations coming from ships of opportunity, research cruises, tidal gauges, and moored buoys, which are limited in spatial and temporal coverage. However, in recent years there has been an enormous increase in oceanographic data coming from autonomous systems (e.g., Argo floats, buoyancy gliders, drifters, radio telemetry) and remotely sensed observations of the surface and near surface. Oceanography is in a unique situation of simultaneously having a wealth of information (for surface processes) and a dearth of information (for subsurface processes and lower trophic ecosystem components). Thus, the complexity of the system and its interactions, as well as challenges imposed by its observational record, make uncertainty quantification a fundamental component of oceanography. Not surprisingly, there has been a long history of using relatively advanced statistical methods in oceanography to help deal with the uncertainties in data and process knowledge for both inference and prediction.

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