Mechanisms Setting the Strength of Orographic Rossby Waves across a Wide Range of Climates in a Moist Idealized GCM
Orographic stationary Rossby waves are an important influence on the large-scale circulation of the atmosphere, especially in Northern Hemisphere winter. Changes in stationary waves with global warming have the potential to modify patterns of surface temperature and precipitation. This paper presents an analysis of the forcing of stationary waves by midlatitude orography across a wide range of climates in a moist idealized GCM, where latent heating and transient eddies are allowed to feed back on the stationary-eddy dynamics. The stationary-eddy amplitude depends to leading order on the surface winds impinging on the orography, resulting in different climate change responses for mountains at different latitudes. Latent heating is found to damp orographic stationary waves, whereas transient eddies are found to reinforce them. As the climate warms, the damping by latent heating becomes more effective while the reinforcement by transient eddies becomes less effective, leading to an overall reduction in orographic stationary wave amplitude. These effects overwhelm the influences of a reduced meridional temperature gradient and increased dry static stability, both of which increase the sensitivity of the free troposphere to orographic forcing. Together with a reduction in the midlatitude meridional temperature gradient, the weakening of orographic stationary waves leads to reduced zonal asymmetry of temperature and net precipitation in warm, moist climates. While circulation changes in this idealized model cannot be expected to agree quantitatively with changes in the real world, the key physical processes identified are broadly relevant.
© 2018 American Meteorological Society. Manuscript received 21 October 2017, in final form 30 May 2018. Published online: 9 August 2018. This work was primarily completed while both authors were at the Department of Earth Sciences, ETH Zürich, Zurich, Switzerland. This research has also been supported by NSF Grant AGS-1019211 while both authors were at the California Institute of Technology, Pasadena, California. The idealized GCM simulations for this study were performed on ETH Zürich's EULER computing cluster. Code for the idealized GCM is available online (at https://github.com/tapios/fms-idealized). We thank Simona Bordoni, Andy Thompson, Jess Adkins, Rachel White, Momme Hell, Farid Ait Chaalal, Ori Adam, and three anonymous reviewers for useful comments and discussion during the development of this manuscript.
Published - jcli-d-17-0700.1.pdf