Why climate sensitivity may not be so unpredictable ?

Alexis Hannart (1) , Jean-Louis Dufresne (2) , Philippe Naveau (3, 4)

1 LOCEAN - Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques
2 LMD - Laboratoire de Météorologie Dynamique (UMR 8539)
3 LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette]
4 ESTIMR - Extrèmes : Statistiques, Impacts et Régionalisation

Different explanations have been proposed as to why the range of climate sensitivity predicted by GCMs have not lessened substantially in the last decades, and subsequently if it can be reduced. One such study (\textit{Why is climate sensitivity so unpredictable?}, \cite{RB07}) adressed these questions using rather simple theoretical considerations and reached the conclusion that reducing uncertainties on climate feedbacks and underlying climate processes will not yield a large reduction in the envelope of climate sensitivity. In this letter, we revisit the premises of this conclusion. We show that it results from a mathematical artefact caused by peculiar definitions of uncertainty used by these authors. Applying standard concepts and definitions of descriptive statistics to the exact same framework of analysis as Roe and Baker, we show that within this simple framework, reducing inter-model spread on feedbacks does in fact induce a reduction of uncertainty on climate sensitivity, almost proportionally. Therefore, following Roe and Baker assumptions, climate sensitivity is actually not so unpredictable. %We then briefly focus on ongoing advances in cloud physics that may narrow the spread on feedbacks, thus reducing the uncertainty on climate sensitivity.

Domaines: Océan, Atmosphère

Alexis Hannart, Jean-Louis Dufresne, Philippe Naveau. Why climate sensitivity may not be so unpredictable ?. Geophysical Research Letters, 2009, 36, pp.L16707. ⟨10.1029/2009GL039640⟩. ⟨hal-00423477⟩