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A one-dimensional ͑1D͒ electrostatic particle-in-cell simulation was performed to study wave excitation processes due to a tenuous electron beam in a plasma system, which is composed of hot and cold electron components. In this case, three types of electrostatic waves are excited, namely, Langmuir waves, electron-acoustic waves, and beam-driven waves. The beam-driven waves have a broad frequency spectrum, which extends from ͑0.1-0.2͒ pe ͑ pe is the electron plasma frequency͒ to ͑1.5-2.5͒ pe , with phase speeds close to the speed of the electron beam. The interactions among these waves are investigated for different values of density, temperature, and speed of the electron beam, etc. One special case is that when the density of the electron beam is sufficiently high, compressive solitary waves with bipolar structure of the electric field are generated. The generation mechanism of these solitons is mainly due to the trapping of a fraction of the beam electrons by the potential well of the enhanced beam-driven waves, as shown by the holes that are formed in phase-space plots. The relevance of these excited electrostatic waves to the intense broadband electrostatic noise observed in the Earth's auroral region is also discussed.

[1] In this work we extend the gravity wave parameterization scheme currently used in the Whole Atmosphere Community Climate Model (WACCM), which is based upon Lindzen's linear saturation theory, by including the Coriolis effect to better describe the inertia-gravity waves (IGW). We perform WACCM simulations to study the generation of equatorial oscillations of the zonal mean zonal winds by including a spectrum of IGWs, and the parametric dependence of the wind oscillation on the IGWs and the effect of the new scheme. These simulations demonstrate that the parameterized IGW forcing from the standard and the new scheme are both capable of generating equatorial wind oscillations with a downward phase progression in the stratosphere using the standard spatial resolution settings in the current model. The period of the oscillation is dependent on the strength of the IGW forcing, and the magnitude of the oscillation is dependent on the width of the wave spectrum. The new parameterization affects the wave breaking level and acceleration rates mainly through changing the critical level. The quasi-biennial oscillations (QBO) can be internally generated with the proper selection of the parameters of the scheme. The characteristics of the wind oscillations thus generated are compared with the observed QBO. These experiments demonstrate the need to parameterize IGWs for generating the QBO in General Circulation Models (GCMs).

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[1] The long-term temperature data sets obtained by Rayleigh lidars at six different locations from low to high latitudes within the Network for the Detection of Atmospheric Composition Change (NDACC) were used to derive the annual oscillations (AO) and semiannual oscillations (SAO) of middle atmosphere temperature: Reunion Island (21.8°S); Mauna Loa Observatory, Hawaii (19.5°N); 0°N). The results were compared with those derived from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite. The zonal mean temperatures at similar latitudes show good agreement. The observations also reveal that the AO dominates the seasonal oscillations in both the stratosphere and the mesosphere at middle and high latitudes, with the amplitudes increasing poleward. The SAO oscillations are weaker at all six sites. The oscillations in the upper mesosphere are usually stronger than those in the upper stratosphere with a local minimum near 50-65 km. The upper mesospheric signals are clearly out of phase with upper stratospheric signals. Some differences between lidar and SABER results were found in both the stratosphere and mesosphere. These could be due to: the difference in data sampling between ground-based and space-based instruments, the length of data set, the tidal aliasing owing to the temperature AO and SAO since lidar data are nighttime only, and lidar temperature analysis algorithms. The seasonal oscillations of tidal amplitudes derived from SABER observations suggests that the tidal aliasing of the lidar temperature AO and SAO in the upper mesosphere may over-or under-estimate the real temperature oscillations, depending on the tidal phases. In addition, the possibly unrealistic seasonal oscillations embedded in the climatological models (e.g., MSIS or CIRA) at the reference point for lidar temperature analysis may also affect the lidar results in the top part of the profiles (usually in the upper mesosphere).