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Smith DM, Eade R, Andrews MB, Ayres H, Clark A, Chripko S, Deser C, Dunstone NJ, García-Serrano J, Gastineau G, Graff LS, Hardiman SC, He B, Hermanson L, Jung T, Knight J, Levine X, Magnusdottir G, Manzini E, Matei D, Mori M, Msadek R, Ortega P, Peings Y, Scaife AA, Screen JA, Seabrook M, Semmler T, Sigmond M, Streffing J, Sun L, Walsh A. Robust but weak winter atmospheric circulation response to future Arctic sea ice loss. Nat Commun 2022; 13:727. [PMID: 35132058 PMCID: PMC8821642 DOI: 10.1038/s41467-022-28283-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 01/17/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractThe possibility that Arctic sea ice loss weakens mid-latitude westerlies, promoting more severe cold winters, has sparked more than a decade of scientific debate, with apparent support from observations but inconclusive modelling evidence. Here we show that sixteen models contributing to the Polar Amplification Model Intercomparison Project simulate a weakening of mid-latitude westerlies in response to projected Arctic sea ice loss. We develop an emergent constraint based on eddy feedback, which is 1.2 to 3 times too weak in the models, suggesting that the real-world weakening lies towards the higher end of the model simulations. Still, the modelled response to Arctic sea ice loss is weak: the North Atlantic Oscillation response is similar in magnitude and offsets the projected response to increased greenhouse gases, but would only account for around 10% of variations in individual years. We further find that relationships between Arctic sea ice and atmospheric circulation have weakened recently in observations and are no longer inconsistent with those in models.
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Smith DM, Scaife AA, Eade R, Athanasiadis P, Bellucci A, Bethke I, Bilbao R, Borchert LF, Caron LP, Counillon F, Danabasoglu G, Delworth T, Doblas-Reyes FJ, Dunstone NJ, Estella-Perez V, Flavoni S, Hermanson L, Keenlyside N, Kharin V, Kimoto M, Merryfield WJ, Mignot J, Mochizuki T, Modali K, Monerie PA, Müller WA, Nicolí D, Ortega P, Pankatz K, Pohlmann H, Robson J, Ruggieri P, Sospedra-Alfonso R, Swingedouw D, Wang Y, Wild S, Yeager S, Yang X, Zhang L. North Atlantic climate far more predictable than models imply. Nature 2020; 583:796-800. [PMID: 32728237 DOI: 10.1038/s41586-020-2525-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 05/01/2020] [Indexed: 11/09/2022]
Abstract
Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change1-3. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain4. This leads to low confidence in regional projections, especially for precipitation, over the coming decades5,6. The chaotic nature of the climate system7-9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models10, and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade.
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Affiliation(s)
- D M Smith
- Met Office Hadley Centre, Exeter, UK.
| | - A A Scaife
- Met Office Hadley Centre, Exeter, UK.,College of Engineering, Mathematics and Physical Sciences, Exeter University, Exeter, UK
| | - R Eade
- Met Office Hadley Centre, Exeter, UK
| | - P Athanasiadis
- Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy
| | - A Bellucci
- Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy
| | - I Bethke
- Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway
| | - R Bilbao
- Barcelona Supercomputing Center, Barcelona, Spain
| | - L F Borchert
- Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France
| | - L-P Caron
- Barcelona Supercomputing Center, Barcelona, Spain
| | - F Counillon
- Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway.,Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
| | - G Danabasoglu
- National Center for Atmospheric Research, Boulder, CO, USA
| | - T Delworth
- Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ, USA
| | - F J Doblas-Reyes
- Barcelona Supercomputing Center, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | | | - V Estella-Perez
- Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France
| | - S Flavoni
- Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France
| | | | - N Keenlyside
- Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway.,Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
| | - V Kharin
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada
| | - M Kimoto
- Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan
| | - W J Merryfield
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada
| | - J Mignot
- Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France
| | - T Mochizuki
- Department of Earth and Planetary Sciences, Kyushu University, Fukuoka, Japan.,Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
| | - K Modali
- Max-Planck-Institut für Meteorologie, Hamburg, Germany.,Regional Computing Center, University of Hamburg, Hamburg, Germany
| | - P-A Monerie
- National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK
| | - W A Müller
- Max-Planck-Institut für Meteorologie, Hamburg, Germany
| | - D Nicolí
- Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy
| | - P Ortega
- Barcelona Supercomputing Center, Barcelona, Spain
| | - K Pankatz
- Deutscher Wetterdienst, Hamburg, Germany
| | - H Pohlmann
- Max-Planck-Institut für Meteorologie, Hamburg, Germany.,Deutscher Wetterdienst, Hamburg, Germany
| | - J Robson
- National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK
| | - P Ruggieri
- Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy
| | - R Sospedra-Alfonso
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada
| | - D Swingedouw
- CNRS-EPOC, Université de Bordeaux, Pessac, France
| | - Y Wang
- Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway
| | - S Wild
- Barcelona Supercomputing Center, Barcelona, Spain
| | - S Yeager
- National Center for Atmospheric Research, Boulder, CO, USA
| | - X Yang
- Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ, USA
| | - L Zhang
- Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ, USA
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Sheen KL, Smith DM, Dunstone NJ, Eade R, Rowell DP, Vellinga M. Skilful prediction of Sahel summer rainfall on inter-annual and multi-year timescales. Nat Commun 2017; 8:14966. [PMID: 28541288 PMCID: PMC5529672 DOI: 10.1038/ncomms14966] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Accepted: 02/17/2017] [Indexed: 11/09/2022] Open
Abstract
Summer rainfall in the Sahel region of Africa exhibits one of the largest signals of climatic variability and with a population reliant on agricultural productivity, the Sahel is particularly vulnerable to major droughts such as occurred in the 1970s and 1980s. Rainfall levels have subsequently recovered, but future projections remain uncertain. Here we show that Sahel rainfall is skilfully predicted on inter-annual and multi-year (that is, >5 years) timescales and use these predictions to better understand the driving mechanisms. Moisture budget analysis indicates that on multi-year timescales, a warmer north Atlantic and Mediterranean enhance Sahel rainfall through increased meridional convergence of low-level, externally sourced moisture. In contrast, year-to-year rainfall levels are largely determined by the recycling rate of local moisture, regulated by planetary circulation patterns associated with the El Niño-Southern Oscillation. Our findings aid improved understanding and forecasting of Sahel drought, paramount for successful adaptation strategies in a changing climate.
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Affiliation(s)
- K. L. Sheen
- Met Office Hadley Centre, Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK
- Department of Physical Geography, University of Exeter, Peter Lanyon Building, Penryn Campus, Trelevier Road, Penryn, Cornwall TR10 9FE, UK
| | - D. M. Smith
- Met Office Hadley Centre, Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK
| | - N. J. Dunstone
- Met Office Hadley Centre, Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK
| | - R. Eade
- Met Office Hadley Centre, Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK
| | - D. P. Rowell
- Met Office Hadley Centre, Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK
| | - M. Vellinga
- Met Office Hadley Centre, Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK
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