Preprints
https://doi.org/10.5194/wcd-2021-48
https://doi.org/10.5194/wcd-2021-48

  06 Aug 2021

06 Aug 2021

Review status: this preprint is currently under review for the journal WCD.

Summertime circumglobal Rossby waves in climate models: Small biases in upper-level circulation create substantial biases in surface imprint

Fei Luo1,2, Frank Selten2, Kathrin Wehrli3, Kai Kornhuber4,5, Philippe Le Sager2, Wilhelm May6, Thomas Reerink2, Sonia I. Seneviratne3, Hideo Shiogama7, Daisuke Tokuda8, Hyungjun Kim8, and Dim Coumou1,2 Fei Luo et al.
  • 1Institute for Environmental Studies, VU University Amsterdam, Amsterdam, Netherlands
  • 2Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands
  • 3Institute for Atmospheric and Climate Science, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
  • 4Earth Institute, Columbia University, New York, United States
  • 5Lamont-Doherty Earth observatory, Columbia University, New York, United States
  • 6Centre for Environmental and Climate Science (CEC), Lund University, Lund, Sweden
  • 7Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan
  • 8Institute of Industrial Science, University of Tokyo, Tokyo, Japan

Abstract. In boreal summer, circumglobal Rossby waves can promote stagnating weather systems that favor extreme events like heatwaves or droughts. Recent work highlighted the risks associated with amplified Rossby wavenumber 5 and 7 in triggering simultaneous warm anomalies in specific agricultural breadbaskets in the Northern Hemisphere. These type of wave patterns thus pose potential risks for food production, as well as human health, and other impacts. The representation of such summertime wave events and their surface imprints in general circulation models (GCMs) has not been  systematically analyzed. Here we validate 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, which are (1) historic simulations (1979–2015/2016) of a freely running atmosphere with prescribed ocean, and experiments that additionally nudge toward the observed (2) upper-level horizontal winds in the atmosphere, (3) soil moisture conditions, or (4) both. The nudged experiments are used to trace the sources of the model biases to either the large-scale atmospheric circulation or surface feedback processes. We show that while the wave position and magnitude is represented well compared to ERA5 reanalysis data. During high amplitudes (> 1.5 s.d.) wave-5 and wave- 7 events, the imprint on surface variables temperature, precipitation and sea level pressure is substantially underestimated: typically, by a factor of 1.5 in correlation and normalized standard deviations (n.s.d.) for near-surface temperature and mean sea level pressure. As for the precipitation, it’s still a factor of 1.5 for n.s.d. but 2 for correlation. The correlations and n.s.d. for surface variables do not improve if only the soil moisture is prescribed, but considerably increased when the upper-level atmosphere circulation is nudged. The underestimation factors are corrected almost entirely. When applying both soil moisture prescription and the nudging of upper-level atmosphere, both the correlation and n.s.d. values are quite similar to  only atmosphere component is nudged experiments. Hence, the near-surface biases can be substantially improved when nudging the upper-level circulation providing evidence that relatively small biases in the models’ representation of the upper-level waves can strongly affect associated temperature and rainfall anomalies.

Fei Luo et al.

Status: open (until 29 Sep 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Fei Luo et al.

Fei Luo et al.

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Short summary
Recent studies have identified the weather systems in observational data, where wave patterns with high magnitude values that circle around the whole global in either wavenumber 5 or wavenumber 7, are responsible for the extreme events.In conclusion, we find that the climate models are able to reproduce the large-scale atmospheric circulation patterns, as well as their associated surface temperature, precipitation, sea level pressures characters.