• The Structure of Climate Variability Across Scales 

      Franzke, Christian; Barbosa, Susana; Blender, Richard; Fredriksen, Hege-Beate; Laepple, Thomas; Lambert, Fabrice; Nilsen, Tine; Rypdal, Kristoffer; Rypdal, Martin Wibe; Scotto, Manuel; Vannitsem, Stephane; Watkins, Nicholas W.; Yang, Lichao; Yuan, Naiming (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-05)
      One of the most intriguing facets of the climate system is that it exhibits variability across all temporal and spatial scales; pronounced examples are temperature and precipitation. The structure of this variability, however, is not arbitrary. Over certain spatial and temporal ranges, it can be described by scaling relationships in the form of power laws in probability density distributions and ...
    • The Structure of Climate Variability Across Scales 

      Franzke, Christian L.E.; Barbosa, Susana; Blender, Richard; Fredriksen, Hege-Beate; Laepple, Thomas; Lambert, Fabrice; Nilsen, Tine; Rypdal, Kristoffer; Rypdal, Martin; Scotto, Manuel G; Vannitsem, Stephane; Watkins, Nicholas W.; Yang, Lichao; Yuan, Naiming (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-05)
      One of the most intriguing facets of the climate system is that it exhibits variability across all temporal and spatial scales; pronounced examples are temperature and precipitation. The structure of this variability, however, is not arbitrary. Over certain spatial and temporal ranges, it can be described by scaling relationships in the form of power laws in probability density distributions and ...
    • Warming trends and long-range dependent climate variability since year 1900: A Bayesian approach 

      Myrvoll-Nilsen, Eirik; Fredriksen, Hege-Beate; Sørbye, Sigrunn Holbek; Rypdal, Martin wibe (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-08-21)
      Temporal persistence in unforced climate variability makes detection of trends in surface temperature difficult. Part of the challenge is methodological since standard techniques assume a separation of time scales between trend and noise. In this work we present a novel Bayesian approach to trend detection under the assumption of long-range dependent natural variability, and we use estimates of ...