Stratospheric impacts on climate variability and predictability in nudging experiments (WCD/GMD inter-journal SI)(WCD/GMD inter-journal SI)
Stratospheric impacts on climate variability and predictability in nudging experiments (WCD/GMD inter-journal SI)(WCD/GMD inter-journal SI)
Editor(s): GMD topic editors | Coordinators: James Anstey (Environment and Climate Change Canada, Canada) and Chaim Garfinkel (Hebrew University of Jerusalem, Israel) Special issue jointly organized between Weather and Climate Dynamics and Geoscientific Model Development

Constraining the circulation in general circulation models by nudging the model variables toward reanalysis provides a rather powerful tool for investigating the sensitivities of predictions and simulations to specific processes or phenomena and enables the impact of model biases to be better quantified. A shared methodology for applying nudging to stratospheric variables has been developed by the World Climate Research Programme (WCRP) Stratosphere–troposphere Process And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) and Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) activities. This methodology involves nudging (relaxing) only the zonal mean, while atmospheric waves are allowed to evolve freely, though publications that adopt other nudging methodologies or that explore sensitivity to the nudging methodology are encouraged to submit. For SNAPSI the nudging is applied throughout the stratosphere, whereas QBOi applies nudging to a localized region of the equatorial stratosphere. The reliability and robustness of the conclusions obtained from this new approach are further enhanced by the use of coordinated multi-model experiments.

The purpose of the special issue is to provide a common location for reporting results from the SNAPSI and QBOi coordinated experiments utilizing stratospheric nudging, along with results from other related studies that nudge the atmosphere, whether nudging just the zonal mean or the full field. A number of modelling centres have now carried out the SNAPSI and QBOi experiments. The special issue would collect papers analysing these datasets that have been produced by participating modelling centres.

The SNAPSI experiments are designed to study the role of sudden stratospheric warmings (SSWs) in surface predictability; they are hindcast-type experiments, specifying 45-day runs covering three recent SSW events, with a large ensemble size of 50–100 members for each case. Analysis topics include the role of stratospheric variability in surface extremes and predictability and stratosphere–troposphere coupling mechanisms. The QBOi experiments are designed to study the impact of biases in the quasi-biennial oscillation (QBO) on QBO teleconnections and the forcing of the QBO; they are climate-type experiments, specifying 40-year runs with one to three ensemble members. Analysis topics include the QBO teleconnections with the stratospheric polar vortex and the relationship between the QBO and Madden–Julian oscillation (MJO). Analysis of both sets of coordinated experiments, SNAPSI and QBOi, is currently in progress, with papers expected to be submitted in the coming 1–2 years.

Review process: This inter-journal special issue co-lists papers of different journals. Thereby, each paper was submitted to 1 particular journal and underwent the regular interactive peer-review process of that journal. The peer review was handled by regular members of the editorial board.

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03 Jul 2024
Role of the Quasi-Biennial Oscillation on Alleviating Biases in the Semi-Annual Oscillation
Aleena Moolakkunnel Jaison, Lesley J. Gray, Scott M. Osprey, Jeff R. Knight, and Martin B. Andrews
EGUsphere, https://doi.org/10.5194/egusphere-2024-1818,https://doi.org/10.5194/egusphere-2024-1818, 2024
Revised manuscript accepted for WCD (discussion: final response, 3 comments)
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04 Jul 2022
Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): a protocol for investigating the role of stratospheric polar vortex disturbances in subseasonal to seasonal forecasts
Peter Hitchcock, Amy Butler, Andrew Charlton-Perez, Chaim I. Garfinkel, Tim Stockdale, James Anstey, Dann Mitchell, Daniela I. V. Domeisen, Tongwen Wu, Yixiong Lu, Daniele Mastrangelo, Piero Malguzzi, Hai Lin, Ryan Muncaster, Bill Merryfield, Michael Sigmond, Baoqiang Xiang, Liwei Jia, Yu-Kyung Hyun, Jiyoung Oh, Damien Specq, Isla R. Simpson, Jadwiga H. Richter, Cory Barton, Jeff Knight, Eun-Pa Lim, and Harry Hendon
Geosci. Model Dev., 15, 5073–5092, https://doi.org/10.5194/gmd-15-5073-2022,https://doi.org/10.5194/gmd-15-5073-2022, 2022
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