EGU21-191, updated on 03 Mar 2021
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Long-Range Predictability of the Length of Day and Extratropical Climate.

Adam Scaife1,2, Leon Hermanson1, Annelize van Niekerk1, Mark Baldwin3, Stephen Belcher1, Philip Bett1, Ruth Comer1, Nick Dunstone1, Ruth Geen2, Steven Hardiman1, Sarah Ineson1, Jeff Knight1, Yu Nie4, Hongli Ren5, and Smith Doug1
Adam Scaife et al.
  • 1Met Office, Hadley Centre, Exeter, United Kingdom of Great Britain and Northern Ireland (
  • 2College of Engineering, Physics and Mathematical Sciences, University of Exeter, U.K.
  • 3Department of Mathematics and Global Systems Institute, University of Exeter, UK.
  • 4Beijing Climate Centre, China Meteorological Administration, Beijing, China.
  • 5State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, China.

Angular momentum is fundamental to the structure and variability of the atmosphere and hence regional weather and climate. Total atmospheric angular momentum (AAM) is also directly related to the rotation rate of the Earth and hence the length of day. However, the long-range predictability of fluctuations in the length of day, atmospheric angular momentum and the implications for climate prediction are unknown. Here we show that fluctuations in AAM and the length of day are predictable out to more than a year ahead and that this provides an atmospheric source of long-range predictability of surface climate. Using ensemble forecasts from a dynamical climate model we demonstrate predictable signals in the atmospheric angular momentum field that propagate slowly and coherently polewards into the northern and southern hemisphere due to wave-mean flow interaction within the atmosphere. These predictable signals are also shown to precede changes in extratropical surface climate via the North Atlantic Oscillation. These results provide a novel source of long-range predictability of climate from within the atmosphere, greatly extend the lead time for length of day predictions and link geodesy with climate variability.

How to cite: Scaife, A., Hermanson, L., van Niekerk, A., Baldwin, M., Belcher, S., Bett, P., Comer, R., Dunstone, N., Geen, R., Hardiman, S., Ineson, S., Knight, J., Nie, Y., Ren, H., and Doug, S.: Long-Range Predictability of the Length of Day and Extratropical Climate., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-191,, 2020.

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