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Climate Time Series Analysis

Part of the book series: Atmospheric and Oceanographic Sciences Library ((ATSL,volume 51))

Abstract

“Weather is important but hard to predict”—laypeople and scientists alike will agree. The complexity of that system limits the knowledge about it and therefore its predictability even over a few days. It is complex because many variables within the Earth’s atmosphere, such as temperature, barometric pressure, wind velocity, humidity, clouds and precipitation, are interacting, and they do so nonlinearly. Extending the view to longer timescales, that is, the climate system in its original sense (the World Meteorological Organization defines a timescale boundary between weather and climate of 30 years), and also to larger spatial and further processual scales considered to influence climate (Earth’s surface, cryosphere, Sun, etc.) does not reduce complexity. This book loosely adopts the term “climate” to refer to this extended view, which shall also include “palaeoclimate” as the climate within the geological past.

Man observes nature and climate to learn, or extract information, and to predict. Since the climate system is complex and not all variables can be observed at arbitrary spatial and temporal range and resolution, our knowledge is, and shall be, restricted and uncertainty is introduced. In such a situation, we need the statistical language to acquire quantitative information. For that, we take the axiomatic approach by assuming that to an uncertain event (“it rains tomorrow” or “before 20,000 years the tropics were more than 5 ∘C colder than at present”) a probability (real number between 0 and 1) can be assigned (Kolmogoroff, Ergeb. Math. Grenzgeb. 2(3):195–262, 1933). Statistics then deciphers/infers events and probabilities from data.

Superiority of quantitative methods over qualitative

—Karl Popper

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    Manfred Mudelsee

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Mudelsee, M. (2014). Introduction. In: Climate Time Series Analysis. Atmospheric and Oceanographic Sciences Library, vol 51. Springer, Cham. https://doi.org/10.1007/978-3-319-04450-7_1

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