Winds and temperatures of the Arctic middle atmosphere during January measured by Doppler lidar
Abstract. We present an extensive data set of simultaneous temperature and wind measurements in the Arctic middle atmosphere. It consists of more than 300 h of Doppler Rayleigh lidar observations obtained during three January seasons (2012, 2014, and 2015) and covers the altitude range from 30 km up to about 85 km. The data set reveals large year-to-year variations in monthly mean temperatures and winds, which in 2012 are affected by a sudden stratospheric warming. The temporal evolution of winds and temperatures after that warming are studied over a period of 2 weeks, showing an elevated stratopause and the reformation of the polar vortex. The monthly mean temperatures and winds are compared to data extracted from the Integrated Forecast System of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Horizontal Wind Model (HWM07). Lidar and ECMWF data show good agreement of mean zonal and meridional winds below  ≈ 55 km altitude, but we also find mean temperature, zonal wind, and meridional wind differences of up to 20 K, 20 m s−1, and 5 m s−1, respectively. Differences between lidar observations and HWM07 data are up to 30 m s−1. From the fluctuations of temperatures and winds within single nights we extract the potential and kinetic gravity wave energy density (GWED) per unit mass. It shows that the kinetic GWED is typically 5 to 10 times larger than the potential GWED, the total GWED increases with altitude with a scale height of  ≈ 16 km. Since temporal fluctuations of winds and temperatures are underestimated in ECMWF, the total GWED is underestimated as well by a factor of 3–10 above 50 km altitude. Similarly, we estimate the energy density per unit mass for large-scale waves (LWED) from the fluctuations of nightly mean temperatures and winds. The total LWED is roughly constant with altitude. The ratio of kinetic to potential LWED varies with altitude over 2 orders of magnitude. LWEDs from ECMWF data show results similar to the lidar data. From the comparison of GWED and LWED, it follows that large-scale waves carry about 2 to 5 times more energy than gravity waves.
A climatology of elevated stratopause events in the whole atmosphere community climate model
Elevated stratopause (ES) events occurring during Northern Hemisphere winter are identified in four climate simulations of the period 1953–2005 made with the Whole Atmosphere Community Climate Model (WACCM). We find 68 ES events in 212 winters. These events are found in winters when the middle atmosphere is disturbed and there are zonal wind reversals in the stratosphere at high latitudes. These disturbances can be associated with both major and minor stratospheric sudden warming events (SSWs). The ES events occur under conditions where the stratospheric jet, the gravity wave forcing, and the residual circulation remain reversed longer than in those winters where an SSW occurs without an ES. We compare ES events with the type of SSW (vortex splitting and vortex displacement) and find that 68% of ES events form after vortex splitting events. We also present a climatology of ES events based on NASA's Modern‐Era Retrospective Analysis for Research and Applications reanalysis data from 1979 to 2012 and compare it to the model results. WACCM composites of major SSW and ES also show enhanced Eliassen‐Palm flux divergences in the upper mesosphere after the stratospheric warming, immediately before the formation of an ES. However, the formation of an ES in WACCM is due primarily to adiabatic heating from gravity wave‐driven downwelling, which follows the reestablishment of the eastward jet in the upper stratosphere. We find nine winters where an ES forms in the absence of any significant planetary wave activity in the upper mesosphere and illustrate one such event.
Mean field model of a game for power
Abstract Our aim is to model a game for power (equivalent to total energy) as a dynamical process, where an excess of power possessed by a player allows him to gain even more power. Such a positive feedback is often termed as the Matthew effect. Analytical and numerical methods allow to identify a set of stationary states, i.e. fixed points of the model dynamics. The positions of the unstable fixed points give an insight on the basins of attraction of the stable fixed points. The results are interpreted in terms of modeling of coercive power.