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<p>The current scientific understanding of top-of-atmosphere globally-averaged albedo stability and hemispheric symmetry on interannual to centennial time-scales is largely phenomenological and diagnostic, leading to diverging albedo estimates over the 21<sup><i>s</i><i>t</i></sup> Century. We present a framework for hypothesis testing and theory development, complemented by observations, data methods, and models, to advance towards a theory for these phenomena. We present the theory’s necessary features needed and then explore two hypotheses and their observational tests: that albedo is (1) constrained by invariant Earth system properties, or (2) maintained by cloud buffering. We argue that there is a supporting role for artificial intelligence (AI) methods that express the non-linear processes that underlie these observed phenomena. Additionally, we show that the response to and relaxation from major perturbations like stratovolcanic eruptions may help to falsify hypotheses. Finally multi-model ensemble experiments and observations can support this multi-pronged approach to advance towards a working theory for albedo.</p>

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Towards a theory for Earth’s albedo stability and hemispheric symmetry in the 21st Century

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Daniel R. Feldman,
  • Jake J. Gristey,
  • Maria Z. Hakuba,
  • Doug Hellinger,
  • Samuel Kahn

摘要

The current scientific understanding of top-of-atmosphere globally-averaged albedo stability and hemispheric symmetry on interannual to centennial time-scales is largely phenomenological and diagnostic, leading to diverging albedo estimates over the 21st Century. We present a framework for hypothesis testing and theory development, complemented by observations, data methods, and models, to advance towards a theory for these phenomena. We present the theory’s necessary features needed and then explore two hypotheses and their observational tests: that albedo is (1) constrained by invariant Earth system properties, or (2) maintained by cloud buffering. We argue that there is a supporting role for artificial intelligence (AI) methods that express the non-linear processes that underlie these observed phenomena. Additionally, we show that the response to and relaxation from major perturbations like stratovolcanic eruptions may help to falsify hypotheses. Finally multi-model ensemble experiments and observations can support this multi-pronged approach to advance towards a working theory for albedo.