Summertime Rossby waves in climate models: Substantial biases in surface imprint associated with small biases in upper-level circulation

  • Fei Luo*
  • , Frank Selten
  • , Kathrin Wehrli
  • , Kai Kornhuber
  • , Philippe Le Sager
  • , Wilhelm May
  • , Thomas Reerink
  • , Sonia I. Seneviratne
  • , Hideo Shiogama
  • , Daisuke Tokuda
  • , Hyungjun Kim
  • , Dim Coumou
  • *Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In boreal summer, circumglobal Rossby waves can promote stagnating weather systems that favor extreme events like heat waves or droughts. Recent work showed that amplified Rossby wavenumber 5 and 7 show phase-locking behavior which can trigger simultaneous warm anomalies in different breadbasket regions in the Northern Hemisphere. These types of wave patterns thus pose a potential threat to human health and ecosystems. The representation of such persistent wave events in summer and their surface anomalies in general circulation models (GCMs) has not been systematically analyzed. Here we validate the representation of wavenumbers 1-10 in three state-of-The-Art global climate models (EC-Earth, CESM, and MIROC), quantify their biases, and provide insights into the underlying physical reasons for the biases. To do so, the ExtremeX experiments output data were used, consisting of (1) historic simulations with a freely running atmosphere with prescribed ocean and experiments that additionally (2) nudge towards the observed upper-level horizontal winds, (3) prescribe soil moisture conditions, or (4) do both. The experiments are used to trace the sources of the model biases to either the large-scale atmospheric circulation or surface feedback processes. Focusing on wave 5 and wave 7, we show that while the wave's position and magnitude are generally well represented during high-Amplitude (>g 1.5 SD) episodes, the associated surface anomalies are substantially underestimated. Near-surface temperature, precipitation and mean sea level pressure are typically underestimated by a factor of 1.5 in terms of normalized standard deviations. The correlations and normalized standard deviations for surface anomalies do not improve if the soil moisture is prescribed. However, the surface biases are almost entirely removed when the upper-level atmospheric circulation is nudged. When both prescribing soil moisture and nudging the upper-level atmosphere, then the surface biases remain quite similar to the experiment with a nudged atmosphere only. We conclude that the near-surface biases in temperature and precipitation are in the first place related to biases in the upper-level circulation. Thus, relatively small biases in the models' representation of the upper-level waves can strongly affect associated temperature and precipitation anomalies.

Original languageEnglish
Pages (from-to)905-935
Number of pages31
JournalWeather and Climate Dynamics
Volume3
Issue number3
Early online date8 Aug 2022
DOIs
Publication statusPublished - 2022

Bibliographical note

Funding Information:
Acknowledgements. EC-Earth3 simulations were contributed by VU Amsterdam and the KNMI. The MIROC5 simulations were contributed by NIES Japan and the University of Tokyo. CESM1.2 simulations were contributed by ETH Zurich. The authors thank editor Irina Rudeva and the three anonymous reviewers for their constructive and insightful comments and suggestions regarding the manuscript. The authors would like to thank Mathias Hauser and Emanuel Dutra for their help in the discussions for the preparation of soil moisture prescription data and the applications in the models. Fei Luo, Dim Coumou, and Frank Selten acknowledge the VIDI award from the Netherlands Organization for Scientific Research (NWO) (Persistent Summer Extremes “PERSIST” project 016.Vidi.171.011). Kai Kornhuber was partially supported by the NSF project NSF AGS-1934358. Kathrin Wehrli and Sonia I. Seneviratne acknowledge funding from the European Research Council (ERC) (“DROUGHT-HEAT” project, grant no. 617518). Hideo Shiogama was supported by the Integrated Research Program for Advancing Climate Models (JPMXD0717935457). The MIROC5 simulations were performed by using Earth Simulator in JAMSTEC and the NEC SX in NIES. Wilhelm May is supported through the Swedish strategic research area ModElling the Regional and Global Earth system (MERGE). Hyungjun Kim acknowledges the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (2021H1D3A2A03097768). This project was partly funded by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 101003469.

Publisher Copyright:
© 2022 Authors

Funding

Acknowledgements. EC-Earth3 simulations were contributed by VU Amsterdam and the KNMI. The MIROC5 simulations were contributed by NIES Japan and the University of Tokyo. CESM1.2 simulations were contributed by ETH Zurich. The authors thank editor Irina Rudeva and the three anonymous reviewers for their constructive and insightful comments and suggestions regarding the manuscript. The authors would like to thank Mathias Hauser and Emanuel Dutra for their help in the discussions for the preparation of soil moisture prescription data and the applications in the models. Fei Luo, Dim Coumou, and Frank Selten acknowledge the VIDI award from the Netherlands Organization for Scientific Research (NWO) (Persistent Summer Extremes “PERSIST” project 016.Vidi.171.011). Kai Kornhuber was partially supported by the NSF project NSF AGS-1934358. Kathrin Wehrli and Sonia I. Seneviratne acknowledge funding from the European Research Council (ERC) (“DROUGHT-HEAT” project, grant no. 617518). Hideo Shiogama was supported by the Integrated Research Program for Advancing Climate Models (JPMXD0717935457). The MIROC5 simulations were performed by using Earth Simulator in JAMSTEC and the NEC SX in NIES. Wilhelm May is supported through the Swedish strategic research area ModElling the Regional and Global Earth system (MERGE). Hyungjun Kim acknowledges the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (2021H1D3A2A03097768). This project was partly funded by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 101003469.

FundersFunder number
National Research Foundation of Korea
Seventh Framework Programme
Horizon 2020 Framework Programme101003469
National Science Foundation1934358
Nederlandse Organisatie voor Wetenschappelijk OnderzoekNSF AGS-1934358
Ministry of Science, ICT and Future Planning2021H1D3A2A03097768
European Commission617518
European Research CouncilJPMXD0717935457

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 14 - Life Below Water
      SDG 14 Life Below Water

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