A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems
<p>Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; dri...
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Copernicus Publications
2025-02-01
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| Series: | Weather and Climate Dynamics |
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| author | C. I. Garfinkel Z. D. Lawrence Z. D. Lawrence A. H. Butler E. Dunn-Sigouin E. Dunn-Sigouin I. Statnaia A. Y. Karpechko G. Koren M. Abalos B. Ayarzagüena D. Barriopedro N. Calvo A. de la Cámara A. Charlton-Perez J. Cohen D. I. V. Domeisen D. I. V. Domeisen J. García-Serrano N. P. Hindley M. Jucker H. Kim R. W. Lee S. H. Lee M. Osman M. Osman F. M. Palmeiro I. Polichtchouk J. Rao J. H. Richter C. Schwartz S.-W. Son M. Taguchi N. L. Tyrrell C. J. Wright R. W.-Y. Wu |
| author_facet | C. I. Garfinkel Z. D. Lawrence Z. D. Lawrence A. H. Butler E. Dunn-Sigouin E. Dunn-Sigouin I. Statnaia A. Y. Karpechko G. Koren M. Abalos B. Ayarzagüena D. Barriopedro N. Calvo A. de la Cámara A. Charlton-Perez J. Cohen D. I. V. Domeisen D. I. V. Domeisen J. García-Serrano N. P. Hindley M. Jucker H. Kim R. W. Lee S. H. Lee M. Osman M. Osman F. M. Palmeiro I. Polichtchouk J. Rao J. H. Richter C. Schwartz S.-W. Son M. Taguchi N. L. Tyrrell C. J. Wright R. W.-Y. Wu |
| author_sort | C. I. Garfinkel |
| collection | DOAJ |
| description | <p>Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model's circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere–troposphere coupling. We introduce a set of diagnostics using readily available data that can be used to reveal these biases and then apply these diagnostics to 22 S2S forecast systems.</p>
<p>In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower-stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial intermodel spread likely related to how well each model represents tropospheric stationary waves.</p>
<p>In the Southern Hemisphere, the stratospheric vortex is oversensitive to upward-propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as most underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.</p> |
| format | Article |
| id | doaj-art-69c2d224f83a4db882d651c98ad31cef |
| institution | Kabale University |
| issn | 2698-4016 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Weather and Climate Dynamics |
| spelling | doaj-art-69c2d224f83a4db882d651c98ad31cef2025-02-07T05:57:11ZengCopernicus PublicationsWeather and Climate Dynamics2698-40162025-02-01617119510.5194/wcd-6-171-2025A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systemsC. I. Garfinkel0Z. D. Lawrence1Z. D. Lawrence2A. H. Butler3E. Dunn-Sigouin4E. Dunn-Sigouin5I. Statnaia6A. Y. Karpechko7G. Koren8M. Abalos9B. Ayarzagüena10D. Barriopedro11N. Calvo12A. de la Cámara13A. Charlton-Perez14J. Cohen15D. I. V. Domeisen16D. I. V. Domeisen17J. García-Serrano18N. P. Hindley19M. Jucker20H. Kim21R. W. Lee22S. H. Lee23M. Osman24M. Osman25F. M. Palmeiro26I. Polichtchouk27J. Rao28J. H. Richter29C. Schwartz30S.-W. Son31M. Taguchi32N. L. Tyrrell33C. J. Wright34R. W.-Y. Wu35Fredy & Nadine Herrmann Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, IsraelCooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, CO, USANOAA Physical Sciences Laboratory (PSL), Boulder, CO, USANOAA Chemical Sciences Laboratory (CSL), Boulder, CO, USANORCE Norwegian Research Centre, Bergen, NorwayBjerknes Centre for Climate Research, Bergen, NorwayFinnish Meteorological Institute, Meteorological Research, Helsinki, FinlandFinnish Meteorological Institute, Meteorological Research, Helsinki, FinlandCopernicus Institute of Sustainable Development, Utrecht University, Utrecht, the NetherlandsDepartment of Earth Physics and Astrophysics, Universidad Complutense de Madrid, Madrid, SpainDepartment of Earth Physics and Astrophysics, Universidad Complutense de Madrid, Madrid, SpainInstituto de Geociencias (IGEO), Consejo Superior de Investigaciones Científicas–Universidad Complutense de Madrid (CSIC-UCM), Madrid, SpainDepartment of Earth Physics and Astrophysics, Universidad Complutense de Madrid, Madrid, SpainDepartment of Earth Physics and Astrophysics, Universidad Complutense de Madrid, Madrid, SpainDepartment of Meteorology, University of Reading, Reading, UKAtmospheric and Environmental Research Inc., Lexington, MA, USAFaculty of Geosciences and Environment, University of Lausanne, Lausanne, SwitzerlandInstitute for Atmospheric and Climate Science, ETH Zurich, Zurich, SwitzerlandGroup of Meteorology, Universitat de Barcelona (UB), Barcelona, SpainCentre for Climate Adaptation & Environment Research, University of Bath, Bath, UKClimate Change Research Centre, ARC Centre of Excellence for Climate Extremes, University of New South Wales, Sydney, AustraliaSchool of Earth and Environmental Sciences, Seoul National University, Seoul, South KoreaDepartment of Meteorology, University of Reading, Reading, UKDepartment of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USACONICET–Universidad de Buenos Aires, Centro de Investigaciones del Mar y la Atmósfera (CIMA), Buenos Aires, ArgentinaCNRS–IRD–CONICET–UBA, Instituto Franco-Argentino de Estudios sobre el Clima y sus Impactos (IRL 3351, IFAECI), Buenos Aires, ArgentinaGroup of Meteorology, Universitat de Barcelona (UB), Barcelona, SpainEuropean Centre for Medium-Range Weather Forecasts, Reading, UKCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science & Technology, Nanjing, ChinaClimate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USAFredy & Nadine Herrmann Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem, IsraelSchool of Earth and Environmental Sciences, Seoul National University, Seoul, South KoreaDepartment of Earth Science, Aichi University of Education, Kariya, JapanFinnish Meteorological Institute, Meteorological Research, Helsinki, FinlandCentre for Climate Adaptation & Environment Research, University of Bath, Bath, UKInstitute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland<p>Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model's circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere–troposphere coupling. We introduce a set of diagnostics using readily available data that can be used to reveal these biases and then apply these diagnostics to 22 S2S forecast systems.</p> <p>In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower-stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial intermodel spread likely related to how well each model represents tropospheric stationary waves.</p> <p>In the Southern Hemisphere, the stratospheric vortex is oversensitive to upward-propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as most underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.</p>https://wcd.copernicus.org/articles/6/171/2025/wcd-6-171-2025.pdf |
| spellingShingle | C. I. Garfinkel Z. D. Lawrence Z. D. Lawrence A. H. Butler E. Dunn-Sigouin E. Dunn-Sigouin I. Statnaia A. Y. Karpechko G. Koren M. Abalos B. Ayarzagüena D. Barriopedro N. Calvo A. de la Cámara A. Charlton-Perez J. Cohen D. I. V. Domeisen D. I. V. Domeisen J. García-Serrano N. P. Hindley M. Jucker H. Kim R. W. Lee S. H. Lee M. Osman M. Osman F. M. Palmeiro I. Polichtchouk J. Rao J. H. Richter C. Schwartz S.-W. Son M. Taguchi N. L. Tyrrell C. J. Wright R. W.-Y. Wu A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems Weather and Climate Dynamics |
| title | A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems |
| title_full | A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems |
| title_fullStr | A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems |
| title_full_unstemmed | A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems |
| title_short | A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems |
| title_sort | process based evaluation of biases in extratropical stratosphere troposphere coupling in subseasonal forecast systems |
| url | https://wcd.copernicus.org/articles/6/171/2025/wcd-6-171-2025.pdf |
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