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.
Original language | English |
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Pages (from-to) | 171-195 |
Number of pages | 25 |
Journal | Weather and Climate Dynamics |
Volume | 6 |
Issue number | 1 |
DOIs | |
Publication status | Published - 7 Feb 2025 |
Data Availability Statement
The hindcasts from the S2S database used here are available from https://apps.ecmwf.int/datasets/data/s2s/ (Vitart et al., 2017) under the “Reforecasts” S2S set. The NOAA GEFSv12 hindcasts can be obtained from https://registry.opendata.aws/noaa-gefs-reforecast/ (Guan et al., 2022). Hindcasts for CESM2–CAM are available at https://www.earthsystemgrid.org/dataset/ucar.cgd.cesm2.s2s_hindcasts.html (Richter et al., 2022), while those for CESM2–WACCM are from https://www.earthsystemgrid.org/dataset/ucar.cgd.cesm2-waccm.s2s_hindcasts.html (Richter et al., 2022).Acknowledgements
This work uses S2S project data. S2S is a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP). This work was initiated by the Stratospheric Network for the Assessment of Predictability (SNAP), a joint program of APARC (WCRP) and the S2S project (WWRP–WCRP).Funding
Chaim I. Garfinkel and Jian Rao are supported by the ISF–NSFC joint research program (Israel Science Foundation grant no. 3065/23 and National Natural Science Foundation of China grant no. 42361144843). Chaim I. Garfinkel and Judah Cohen are supported by the NSF–BSF joint research program (National Science Foundation grant no. AGS-2140909 and United States–Israel Binational Science Foundation grant no. 2021714). Irina Statnaia and Alexey Y. Karpechko are supported by the Research Council of Finland (grant no. 355792). The work of Marisol Osman is supported by UBACyT (project nos. 20020220100075BA, PIP 11220200102038CO, and PICT-2021-GRF-TI-00498). The work of Alvaro de la Cámara is funded by the Spanish Ministry of Science, Innovation and Universities (project no. PID2022-136316NB-I00). Marta Abalos, Blanca Ayarzagüena, and Natalia Calvo are supported by the Spanish Ministry of Science, Innovation and Universities through the RecO3very project (no. PID2021-124772OB-I00). Froila M. Palmeiro and Javier García-Serrano have been partially supported by the Spanish ATLANTE project (no. PID2019-110234RB-C21) and Ramón y Cajal program (no. RYC-2016-21181), respectively. Neil P. Hindley and Corwin J. Wright are supported by the UK Natural Environment Research Council (NERC; grant no. NE/S00985X/1). Corwin J. Wright is also supported by a Royal Society University Research Fellowship (grant no. URF/R/221023). Seok-Woo Son and Hera Kim are supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and Information and Communication Technology, MSIT) (grant no. 2023R1A2C3005607). The work of Rachel W.-Y. Wu is funded through ETH (grant no. ETH-05 19-1). Daniela I. V. Domeisen is supported by the Swiss National Science Foundation (project no. PP00P2_198896). This material is based upon work supported by the U.S. Department of Energy Office of Science Biological and Environmental Research (BER) program Regional and Global Model Analysis (RGMA) component of the Earth and Environment Systems Modeling program (award no. DE-SC0022070) and National Science Foundation (NSF; grant no. IA 1947282). This work was also supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF (cooperative agreement no. 1852977). Zachary D. Lawrence was partially supported by NOAA (award no. NA20NWS4680051).
ASJC Scopus subject areas
- Atmospheric Science