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In the early years of climate science, the primary challenge was to describe regional climates and then piece these together to create a global overview. In the 1970s, led by Klaus Hasselmann, the focus shifted to understanding how variability forms in the climate system. This issue was addressed by identifying a small, slow dynamical core governed by the Stochastic Climate Model (SCM), with the larger part of the system acting stochastically upon this core. Later, Principal Interaction Patterns (PIPs) and Principal Oscillation Patterns (POPs) were incorporated into this concept. The SCM provided a framework for evaluating numerical experiments with quasi-realistic climate models and distinguishing between unprovoked (internal) variability and externally forced variations—a separation that was central to the “detection and attribution” problem of climate change.

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The Stochastic Paradigm of Klaus Hasselmann

  • 章节

  • 发表日期：

    2025年

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  • Hans von Storch,
  • Robert Sausen,
  • Eduardo Zorita,
  • Martin Heimann,
  • Martin Claussen

摘要

In the early years of climate science, the primary challenge was to describe regional climates and then piece these together to create a global overview. In the 1970s, led by Klaus Hasselmann, the focus shifted to understanding how variability forms in the climate system. This issue was addressed by identifying a small, slow dynamical core governed by the Stochastic Climate Model (SCM), with the larger part of the system acting stochastically upon this core. Later, Principal Interaction Patterns (PIPs) and Principal Oscillation Patterns (POPs) were incorporated into this concept. The SCM provided a framework for evaluating numerical experiments with quasi-realistic climate models and distinguishing between unprovoked (internal) variability and externally forced variations—a separation that was central to the “detection and attribution” problem of climate change.