DOI QR코드

DOI QR Code

Influence of UTLS Ozone on the QBO-MJO Connection: A Case Study Using the GloSea5 Model

상부 대류권-하부 성층권 오존이 성층권 준 2년주기 진동과 매든-줄리안 진동 상관성에 미치는 영향: GloSea5 이용 사례

  • Oh, Jiyoung (School of Earth and Environmental Sciences, Seoul National University) ;
  • Son, Seok-Woo (School of Earth and Environmental Sciences, Seoul National University) ;
  • Back, Seung-Yoon (School of Earth and Environmental Sciences, Seoul National University)
  • 오지영 (서울대학교 지구환경과학부) ;
  • 손석우 (서울대학교 지구환경과학부) ;
  • 백승윤 (서울대학교 지구환경과학부)
  • Received : 2022.06.28
  • Accepted : 2022.09.07
  • Published : 2022.09.30

Abstract

Recent studies have shown that Madden-Julian Oscillation (MJO) is modulated by Quasi-Biennial Oscillation (QBO) during the boreal winter; MJO becomes more active and predictable during the easterly phase of QBO (EQBO) than the westerly phase (WQBO). Despite growing evidences, climate models fail to capture the QBO-MJO connection. One of the possible reasons is a weak static stability change in the upper troposphere and lower stratosphere (UTLS) by neglecting QBO-induced ozone change in the model. Here, we investigate the possible impact of the ozone-radiative feedback in the tropical UTLS on the QBO-MJO connection by integrating the Global Seasonal Forecasting System 5 (GloSea5) model. A set of experiments is conducted by prescribing either the climatological ozone or the observed ozone at a given year for the EQBO-MJO event in January 2006. The realistic ozone improves the temperature simulation in the UTLS. However, its impacts on the MJO are not evident. The MJO phase and amplitude do not change much when the ozone is prescribed with observation. While it may suggest that the ozone-radiative feedback plays a rather minor role in the QBO-MJO connection, it could also result from model biases in UTLS temperature and not-well organized MJO in the model.

Keywords

Acknowledgement

본 논문의 개선을 위해 좋은 의견을 제시해주신 두분의 심사위원님께 감사를 드립니다. 이 논문은 과학기술정보통신부의 재원으로 한국연구재단의 지원을 받아 수행되었습니다(2017R1E1A1A01074889).

References

  1. Andrews, D. G., J. R. Holton, and C. B. Leovy, 1987: Middle Atmosphere Dynamics, Academic, San Diego, Calif., 489 pp.
  2. Back, S.-Y., J.-Y. Han, and S.-W. Son, 2020: Modeling evidence of QBO- MJO connection: A case study. Geophys. Res. Lett., 47, e2020GL089480.
  3. Baldwin, M. P., and Coauthors, 2001: The quasi-biennial oscillation. Rev. Geophys., 39, 179-229. https://doi.org/10.1029/1999RG000073
  4. Butchart, N., A. A. Scaife, J. Austin, S. H. E. Hare, and J. R. Knight, 2003: Quasi-biennial oscillation in ozone in a coupled chemistry-climate model. J. Geophys. Res. Atmos., 108, 4486. https://doi.org/10.1029/2002JD003004
  5. Butchart, N, and Coauthors, 2018: Overview of experiment design and comparison of models participating in phase 1 of the SPARC quasi-biennial oscillation initiative (QBOi). Geosci. Model Dev., 11, 1009-1032. https://doi.org/10.5194/gmd-11-1009-2018
  6. Collimore, C. C., D. W. Martin, M. H. Hitchman, A. Huesmann, and D. E. Waliser, 2003: On the relationship between the QBO and tropical deep convection. J. Climate, 16, 2552-2568. https://doi.org/10.1175/1520-0442(2003)016<2552:OTRBTQ>2.0.CO;2
  7. Copernicus Climate Change Service 2017: ERA5: Fifth Generation of ECMWF Atmospheric Reanalyses of the Global Climate. Copernicus Climate Change Service Climate Data Store (CDS). ECMWF [Available online at https://cds.climate.copernicus.eu/cdsapp#!/home].
  8. Davis, S. M., K. H. Rosenlof, B. Hassler, D. F. Hurst, W. G. Read, H. Vomel, H. Selkirk, M. Fujiwara, and R. Damadeo, 2016: The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database: a long-term database for climate studies, Earth Syst. Sci. Data, 8, 461-490, doi:10.5194/essd-8-461-2016.
  9. Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553-597, doi:10.1002/qj.828.
  10. Hendon, H. H., and S. Abhik, 2018: Differences in vertical structure of the Madden-Julian oscillation associated with the quasi-biennial oscillation. Geophys. Res. Lett., 45, 4419-4428, doi: 10.1029/2018GL077207.
  11. Hersbach, H., and D. Dee, 2016: ERA5 reanalysis is in production, ECMWF Newsletter 147, ECMWF, Reading, UK [Available online at https://www.ecmwf.int/en/newsletter/147/news/era5-reanalysis-production].
  12. Janiga, M. A., C. J. Schreck, J. A. Ridout, M. Flatau, N. P. Barton, E. J. Metzger, and C. A. Reynolds, 2018: Subseasonal forecasts of convectively coupled equatorial waves and the MJO: Activity and predictive skill. Mon. Wea. Rev., 146, 2337-2360, doi:10.1175/MWR-D-17-0261.1.
  13. Kim, H., F. Vitart, and D. Waliser, 2018: Prediction of the Madden-Julian Oscillation: A Reivew. J. Climate, 31, 9425-9443, doi:10.1175/JCLI-D-18-0210.1.
  14. Kim, H., J. H. Richter, and Z. Martin, 2019: Insignificant QBO-MJO prediction skill relationship in the SubX and S2S subseasonal reforecasts. J. Geophys. Res. Atmos., 124, 12655-12666, doi:10.1029/2019JD031416.
  15. Kim, H., J. M. Caron, J. H. Richter, and I. R. Simpson, 2020: The lack of QBO-MJO connection in CMIP6 models. Geophys. Res. Lett., 47, e2020GL087295, doi:10.1029/2020GL087295.
  16. Klotzbach, P., S. Abhik, H. H. Hendon, M. Bell, C. Lucas, A. G. Marshall, and E. C. J. Oliver, 2019: On the emerging relationship between the stratospheric quasibiennial oscillation and the Madden-Julian oscillation. Sci. Rep., 9, 2981, doi:10.1038/s41598-019-40034-6.
  17. Lee, J. C. K., and N. P. Klingaman, 2018: The effect of the quasi-biennial oscillation on the Madden-Julian oscillation in the Met Office unified model global ocean mixed layer configuration. Atmos. Sci. Lett., 19, e816, doi:10.1002/asl.816.
  18. Li, D., K. P. Shine, and L. J. Gray, 1995: The role of ozone-induced heating anomalies in the quasi-biennial oscillation. Quart. J. Roy. Meteor. Soc., 121, 937-943. https://doi.org/10.1002/qj.49712152411
  19. Lim, Y., S.-W. Son, and D. Kim, 2018: MJO prediction skill of the subseasonal-to-seasonal prediction models. J. Climate, 31, 4075-4094, doi:10.1175/JCLI-D17-0545.1.
  20. Lim, Y., S.-W. Son, A. G. Marshall, H. H. Hendon, and K.-H. Seo, 2019: Influence of the QBO on MJO prediction skill in the subseasonal- to-seasonal prediction models. Climate. Dyn., 53, 1681-1695, doi:10.1007/s00382-019-04719-y.
  21. Lim, Y., and S.-W. Son, 2020: QBO-MJO Connection in CMIP5 models, J. Geophys. Res. Atmos, 125, e2019-JD032157, doi:10.1029/2019JD032157.
  22. Madden, R. A., and P. R. Julian, 1971: Detection of a 40-50 day oscillation in the zonal wind in the tropical pacific. J. Atmos. Sci., 28, 702-708. https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2
  23. Madden, R. A., and P. R. Julian, 1972: Description of Global-Scale circulation cells in the tropics with a 40-50 day period. J. Atmos. Sci., 29, 1109-1123. https://doi.org/10.1175/1520-0469(1972)029<1109:DOGSCC>2.0.CO;2
  24. MacLachlan C., and Coauthors, 2015: Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Quart. J. Roy. Meteor. Soc., 141, 1072-1084, doi:10.1002/qj.2396.
  25. Marshall, A. G., H. H. Hendon, S.-W. Son, and Y. Lim, 2017: Impact of the quasi-biennial oscillation on predictability of the Madden-Julian oscillation. Climate. Dyn., 49, 1365-1377, doi:10.1007/s00382-016-3392-0.
  26. Martin, Z., S. Wang, J. Nie, and A. Sobel, 2019: The impact of the QBO on MJO convection in cloud- resolving simulations. J. Atmos. Sci., 76, 669-688, doi:10.1175/JAS-D-18-0179.1.
  27. Martin, Z., F. Vitart, S. Wang, and A. Sobel, 2020: The impact of the stratosphere on the MJO in a forecast model. J. Geophys. Res. Atmos., 125, e2019JD032106, doi:10.1029/2019JD032106.
  28. Martin, Z., C. Orbe, S. Wang, and A. Sobel, 2021: The MJOQBO relationship in a GCM with stratospheric nudging. J. Climate, 34, 4603-4624, doi:10.1175/JCLI-D20-0636.1.
  29. Nie, J., and A. Sobel, 2015: Responses of tropical deep convection to the QBO: Cloud-resolving simulations. J. Atmos. Sci., 72, 3625-3638, doi:10.1175/JAS-D-15-0035.1.
  30. Pohlmann, H., W. A. Muller, M. Bittner, S. Hettrich, K. Modali, K. Pankatz, and J. Marotzke, 2019: Realistic quasi-biennial oscillation variability in historical and decadal hindcast simulations using CMIP6 forcing. Geophys. Res. Lett., 46, 14118-14125, doi: 10.1029/2019GL084878.
  31. Randel, W., F. Wu, A. Ming, and P. Hitchcock, 2021: A simple model of ozone-temperature coupling in the tropical lower stratosphere, Atmos. Chem. Phys., 21, 18531-18542, doi:10.5194/acp-21-18531-2021.
  32. Raphaldini, B., A. S. W. Teruya, Leite da Silva, P. Dias, L. Massaroppe, and D. Y. Takahashi, 2021: Stratospheric ozone and quasi-biennial oscillation (QBO) interaction with the tropical troposphere on intraseasonal and interannual timescales: a normal-mode perspective. Earth Syst. Dynam., 12, 83-101, doi:10.5194/esd-12-83-2021.
  33. Sakaeda, N., J. Dias, and G. N. Kiladis, 2020: The unique characteristics and potential mechanisms of the MJOQBO relationship. J. Geophys. Res. Atmos., 125, e2020JD033196, doi:10.1029/2020JD033196.
  34. Son, S.-W., Y. Lim, C. Yoo, H. H. Hendon, and J. Kim, 2017: Stratospheric control of the Madden-Julian oscillation. J. Climate, 30, 1909-1922, doi:10.1175/JCLI-D-16-0620.1.
  35. Sun, L., H. Wang, and F. Liu, 2019: Combined effect of the QBO and ENSO on the MJO. Atmos. Ocean. Sci. Lett., 12, 170-176, doi:10.1080/16742834.2019.1588064.
  36. Tweedy, O. V., L. D. Oman, and D. W. Waugh, 2020: Seasonality of the MJO impact on upper tropospherelower stratosphere temperature, circulation, and composition. J. Atmos. Sci., 77, 1455-1473, doi:10.1175/JAS-D-19-0183.1.
  37. Vitart, F., and Coauthors, 2017: The subseasonal to seasonal (S2S) prediction project database. Bull. Amer. Meteor. Soc., 98, 163-173, doi:10.1175/BAMS-D-16-0017.1.
  38. Yoo, C., and S.-W. Son, 2016: Modulation of the boreal wintertime Madden-Julian Oscillation by the stratospheric quasi-biennial oscillation. Geophys. Res. Lett., 43, 1392-1398, doi:10.1002/2016GL067762.
  39. Waliser, D. K., and Coauthors, 2009: MJO simulation diagnostics. J. Climate, 22, 3006-3030. https://doi.org/10.1175/2008JCLI2731.1
  40. Wang, S., M. K. Tippett, A. Sobel, Z. Martin, and F. Vitart, 2019: Impact of the QBO on prediction and predictability of the MJO convection. J. Geophys. Res. Atmos., 124, 11766-11782, doi:10.1029/2019JD030575.
  41. Wheeler, M., and K. M. Weickmann, 2001: Real-time monitoring and prediction of modes of coherent synoptic to intraseasonal tropical variability. Mon. Wea. Rev., 129, 2677-2694. https://doi.org/10.1175/1520-0493(2001)129<2677:RTMAPO>2.0.CO;2
  42. Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917-1932. https://doi.org/10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2
  43. Zhang, C., 2005: Madden-Julian oscillation. Rev. Geophys., 43, RG2003.
  44. Zhang, C., 2013: Madden-Julian oscillation: Bridging weather and climate. Bull. Amer. Meteor. Soc., 94, 1849-1870, doi: 10.1175/BAMS-D-12-00026.1.