North Atlantic climate far more predictable than models imply.

Autor: Smith DM; Met Office Hadley Centre, Exeter, UK. doug.smith@metoffice.gov.uk., Scaife AA; Met Office Hadley Centre, Exeter, UK.; College of Engineering, Mathematics and Physical Sciences, Exeter University, Exeter, UK., Eade R; Met Office Hadley Centre, Exeter, UK., Athanasiadis P; Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy., Bellucci A; Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy., Bethke I; Geophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway., Bilbao R; Barcelona Supercomputing Center, Barcelona, Spain., Borchert LF; Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France., Caron LP; Barcelona Supercomputing Center, Barcelona, Spain., Counillon F; 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., Danabasoglu G; National Center for Atmospheric Research, Boulder, CO, USA., Delworth T; Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ, USA., Doblas-Reyes FJ; Barcelona Supercomputing Center, Barcelona, Spain.; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain., Dunstone NJ; Met Office Hadley Centre, Exeter, UK., Estella-Perez V; Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France., Flavoni S; Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France., Hermanson L; Met Office Hadley Centre, Exeter, UK., Keenlyside N; 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., Kharin V; Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada., Kimoto M; Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Japan., Merryfield WJ; Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada., Mignot J; Sorbonne Universités, LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Paris, France., Mochizuki T; Department of Earth and Planetary Sciences, Kyushu University, Fukuoka, Japan.; Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan., Modali K; Max-Planck-Institut für Meteorologie, Hamburg, Germany.; Regional Computing Center, University of Hamburg, Hamburg, Germany., Monerie PA; National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK., Müller WA; Max-Planck-Institut für Meteorologie, Hamburg, Germany., Nicolí D; Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy., Ortega P; Barcelona Supercomputing Center, Barcelona, Spain., Pankatz K; Deutscher Wetterdienst, Hamburg, Germany., Pohlmann H; Max-Planck-Institut für Meteorologie, Hamburg, Germany.; Deutscher Wetterdienst, Hamburg, Germany., Robson J; National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK., Ruggieri P; Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna, Italy., Sospedra-Alfonso R; Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, British Columbia, Canada., Swingedouw D; CNRS-EPOC, Université de Bordeaux, Pessac, France., Wang Y; Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen, Norway., Wild S; Barcelona Supercomputing Center, Barcelona, Spain., Yeager S; National Center for Atmospheric Research, Boulder, CO, USA., Yang X; Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ, USA., Zhang L; Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ, USA.
Jazyk: angličtina
Zdroj: Nature [Nature] 2020 Jul; Vol. 583 (7818), pp. 796-800. Date of Electronic Publication: 2020 Jul 29.
DOI: 10.1038/s41586-020-2525-0
Abstrakt: Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change 1-3 . Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain 4 . This leads to low confidence in regional projections, especially for precipitation, over the coming decades 5,6 . The chaotic nature of the climate system 7-9 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 models 10 , and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade.
Databáze: MEDLINE
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