An official website of the United States government
Abstract Observations of 30‐MHz coherent backscatter from sporadic‐Eionization layers were obtained with a VHF imaging radar located in Ithaca, New York. The volume probed by the radar lies at relatively high magnetic latitudes, on the northern edge of the mid‐latitude region and underneath the ionospheric trough. Banded, quasi‐periodic (QP) echoes observed from Ithaca are similar to those found in lower midlatitude regions. The Doppler shifts observed are smaller and, so far, do not appear to reach the threshold for Farley‐Buneman instability. However, many of the echoes exhibit fine‐scale structure, with secondary bands or braids oriented obliquely to the primary bands. Secondary bands have been seen only rarely at lower middle latitudes. In previous observations, the QP scattering has been linked to unstable neutral wind shears. Neutral wind shear commonly found in the lower thermosphere could play a key role in the formation of these irregularities and explain some morphological features of the resulting plasma density irregularities and the radar echoes. We consider whether neutral instability and turbulence in the lower thermosphere is the likely cause for some of the structuring in the sporadic‐Elayers. Results of 3D numerical simulations of atmospheric dynamics in the mesosphere to lower thermosphere support the proposition. In particular, we focus on Ekman‐type instabilities that, like the more common Kelvin‐Helmholtz instabilities, are inflection point instabilities, although specifically associated with turning shears, and result in convective rolls aligned close to the mean wind direction, with smaller‐scale secondary waves aligned normal to the primary structures.
more »
« less
Lower Hybrid Waves in High Altitude Echoes of the Topside Equatorial Ionosphere
Abstract We investigate the mechanism underlying lower hybrid waves associated with high altitude echoes recently detected in the post‐sunset equatorial topside ionosphere and inner plasmasphere by the Jicamarca VHF radar. These waves are visible as prominent sidebands in the echo Doppler spectra. New experimental results and newly processed incoherent scatter radar (ISR) datasets are presented that provide clues as to the conditions in which the echoes and associated waves occur. Numerical simulations are presented which demonstrate the feasibility of an inverse energy cascade coupled with a short wavelength instability, that is, the lower hybrid drift instability, in explaining the waves. An inverse cascade is required for short wavelength lower hybrid waves to extend to the 3 m wavelengths measured by the Jicamarca radar. The simulations were able to reproduce some features of the measurements including the lower hybrid sidebands at 3 m wavelengths, asymmetry in the sidebands, and the damping effect of higher densities and lower altitudes.
more »
« less
- Award ID(s):
- 2213849
- PAR ID:
- 10397205
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Space Physics
- Volume:
- 128
- Issue:
- 2
- ISSN:
- 2169-9380
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The influence of gravity waves generated by surface stress and by topography on the atmospheric kinetic energy (KE) spectrum is examined using idealized simulations of a cyclone growing in baroclinically unstable shear flow. Even in the absence of topography, surface stress greatly enhances the generation of gravity waves in the vicinity of the cold front, and vertical energy fluxes associated with these waves produce a pronounced shallowing of the KE spectrum at mesoscale wavelengths relative to the corresponding free-slip case. The impact of a single isolated ridge is, however, much more pronounced than that of surface stress. When the mountain waves are well developed, they produce a wavenumber to the −5/3 spectrum in the lower stratosphere over a broad range of mesoscale wavelengths. In the midtroposphere, a smaller range of wavelengths also exhibits a −5/3 spectrum. When the mountain is 500 m high, the waves do not break, and their KE is entirely associated with the divergent component of the velocity field, which is almost constant with height. When the mountain is 2 km high, wave breaking creates potential vorticity, and the rotational component of the KE spectrum is also strongly energized by the waves. Analysis of the spectral KE budgets shows that the actual spectrum is the result of continually shifting balances of direct forcing from vertical energy flux divergence, conservative advective transport, and buoyancy flux. Nevertheless, there is one interesting example where the −5/3-sloped lower-stratospheric energy spectrum appears to be associated with a gravity-wave-induced upscale inertial cascade.more » « less
-
The curvature instability of thin vortex rings is a parametric instability discovered from short-wavelength analysis by Hattori & Fukumoto ( Phys. Fluids , vol. 15, 2003, pp. 3151–3163). A full-wavelength analysis using normal modes then followed in Fukumoto & Hattori ( J. Fluid Mech. , vol. 526, 2005, pp. 77–115). The present work extends these results to the case with different densities inside and outside the vortex core in the presence of surface tension. The maximum growth rate and the instability half-bandwidth are calculated from the dispersion relation given by the resonance between two Kelvin waves of $$m$$ and $m+1$ , where $$m$$ is the azimuthal wavenumber. The result shows that vortex rings are unstable to resonant waves in the presence of density and surface tension. The curvature instability for the principal modes is enhanced by density variations in the small axial wavenumber regime, while the asymptote for short wavelengths is close to the constant density case. The effect of surface tension is marginal. The growth rates of non-principal modes are also examined, and long waves are most unstable.more » « less
-
Abstract A novel computer vision‐based meteor head echo detection algorithm is developed to study meteor fluxes and their physical properties, including initial range, range coverage, and radial velocity. The proposed Algorithm for Head Echo Automatic Detection (AHEAD) comprises a feature extraction function and a Convolutional Neural Network (CNN). The former is tailored to identify meteor head echoes, and then a CNN is employed to remove false alarms. In the testing of meteor data collected with the Jicamarca 50 MHz incoherent scatter radar, the new algorithm detects over 180 meteors per minute at dawn, which is 2 to 10 times more sensitive than prior manual or algorithmic approaches, with a false alarm rate less than 1 percent. The present work lays the foundation of developing a fully automatic AI‐meteor package that detects, analyzes, and distinguishes among many types of meteor echoes. Furthermore, although initially evaluated for meteor data collected with the Jicamarca VHF incoherent radar, the new algorithm is generic enough that can be applied to other facilities with minor modifications. The CNN removes up to 98 percent of false alarms according to the testing set. We also present and discuss the physical characteristics of meteors detected with AHEAD, including flux rate, initial range, line of sight velocity, Signal‐to‐Noise Ratio, and noise characteristics. Our results indicate that stronger meteor echoes are detected at a slightly lower altitude and lower radial velocity than other meteors.more » « less
-
Abstract The numerical forecast methods used to predict ionospheric convective plasma instabilities associated with Equatorial Spread‐F(ESF) have limited accuracy and are often computationally expensive. We test whether it is possible to bypass first‐principle numeric simulations and forecast irregularities using machine learning models. The data are obtained from the incoherent scatter radar at the Jicamarca Radio Observatory located in Lima, Peru. Our models map vertical plasma drifts, time, and solar activity to the occurrence and location of clusters of echoes telltale of ionospheric irregularities. Our results show that these models are capable of identifying the predictive power of the tested inputs, obtaining accuracies around 75%.more » « less
