A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems

Abstract. 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. 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. 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.

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Publication Details

Journal
Weather and Climate Dynamics
Published
2025-02-07
DOI
https://doi.org/10.5194/wcd-6-171-2025
Citations
7
Primary Topic
Atmospheric Ozone and Climate
Type
article
Field-Weighted Citation Impact
9.11

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article

A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems

Zachary D. Lawrence, Irene Erner, Jian Rao, Nicholas Tyrrell et al.
7 citations
Weather and Climate Dynamics
Atmospheric Ozone and Climate
9.11
article

A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems

Zachary D. Lawrence, Irene Erner, Jian Rao, Nicholas Tyrrell, Seok‐Woo Son, Chen Schwartz, Álvaro de la Cámara, Hera Kim, Amy Hawes Butler, Inna Polichtchouk, Javier García‐Serrano, Marisol Osman, Jadwiga H. Richter, Andrew Charlton‐Perez, Chaim I. Garfinkel, David Barriopedro, Natalia Calvo, Robert W. Lee, Masakazu Taguchi, Alexey Yu. Karpechko, Blanca Ayarzagüena, Martin Jucker, Daniela I. V. Domeisen, Corwin J. Wright, Simon H. Lee, Etienne Dunn‐Sigouin, Froila M. Palmeiro, Rachel W.-Y. Wu, Marta Ábalos, Neil P. Hindley, Gerbrand Koren, Judah L. Cohen
article en
7 citations

Abstract

Abstract. 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. 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. 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.

Weather and Climate DynamicsVol. 6(1)
NSF National Center for Atmospheric Research (US), Universidad Complutense de Madrid (ES), Finnish Meteorological Institute (FI), Consejo Superior de Investigaciones Científicas (ES), Seoul National University (KR), Consejo Nacional de Investigaciones Científicas y Técnicas (AR), European Centre for Medium-Range Weather Forecasts (GB), Cooperative Institute for Research in Environmental Sciences (US), University of Colorado Boulder (US), Utrecht University (NL), Hebrew University of Jerusalem (IL), Nanjing University of Information Science and Technology (CN), Universidad de Buenos Aires (AR), Bjerknes Centre for Climate Research (NO), UNSW Sydney (AU), ETH Zurich (CH), Aichi University of Education (JP), NORCE Research AS (NO), ARC Centre of Excellence for Climate System Science (AU), NOAA Physical Sciences Laboratory (US), NOAA Chemical Sciences Laboratory (US), NSF NCAR Climate and Global Dynamics Laboratory (US), Institute of Astronomy and Space Physics (AR), Instituto de Geociencias (ES), Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos (AR), Atmospheric and Environmental Research (US), University of Bath (GB), University of Reading (GB), Universitat de Barcelona (ES), Columbia University (US), University of Lausanne (CH)
National Science Foundation, National Center for Atmospheric Research, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, United States-Israel Binational Science Foundation, National Natural Science Foundation of China, Academy of Finland, Eidgenössische Technische Hochschule Zürich, National Research Foundation of Korea, Israel Science Foundation, Ministerio de Ciencia e Innovación, National Oceanic and Atmospheric Administration, Office of Science, Natural Environment Research Council, Secretaría de Ciencia y Técnica, Universidad de Buenos Aires
Openalex Percentile: Top 2%
Atmospheric Ozone and Climate
9.11
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