Study of second-order wind statistics in the mesosphere and lower
thermosphere region from multistatic specular meteor radar
observations during the SIMONe 2018 campaign

Earth and Space Science

Urco

et al. 2021

Self Cite

Section: Accepted Articlesupporting

confidence: 82%

“…All five transmitted codes are simultaneously decoded at each receiving site by means of compressed sensing (e.g., Urco et al, 2019). Hardware and software details of both systems, i.e., SI-MONe Peru and SIMONe Argentina, can be found in Chau et al (2020).…”

Section: Simone Argentinamentioning

confidence: 99%

First Studies of Mesosphere and Lower Thermosphere Dynamics Using a Multistatic Specular Meteor Radar Network Over Southern Patagonia

Conte

Earth and Space Science

Urco

et al. 2021

Self Cite

“…Diurnal wave signatures in w 0 have been found throughout the entire SIMONe Argentina data set (not shown). Moreover, similar features have been observed in the mean vertical winds over Peru and northern Germany (Charuvil Asokan et al, 2020;Chau et al, 2020). Hence, it is possible that our results on w 0 are also revealing real geophysical features, for example, diurnal tidal effects.…”

Section: Gradients and Vertical Windsupporting

confidence: 76%

First studies of mesosphere and lower thermosphere dynamics using a multistatic specular meteor radar network over southern Patagonia

Conte

Urco

et al. 2020

Preprint

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The mesosphere and lower thermosphere (MLT) is the atmospheric region that couples the lower and upper parts of the terrestrial atmosphere. For this reason, knowledge of its dynamics is of great importance in order to understand the behavior of the atmosphere as a whole. The coupling is accomplished mainly via propagation of three dominant types of waves: planetary waves (PWs), tides, and gravity waves (GWs). PWs are waves with scales of thousands of kilometers and periods of up to ∼30 days. They are mainly generated in the troposphere by land-sea discontinuities, or triggered in situ by, for example, baroclinic instabilities and filtered GWs (e.g., H. L. Liu & Roble, 2002;McCormack et al., 2014;Rossby, 1939). Tides are also waves with horizontal scales of thousands of kilometers, but periods that are subharmonics of the solar and lunar days. Thermal tides are mainly a consequence of solar radiation absorption by water vapor in the troposphere and ozone in the stratosphere, while the lunar tide results from the gravitational pull of the Moon (e.g., Forbes, 1984;Lindzen & Chapman, 1969). GWs are small to medium scale waves with periods ranging from about 5 min to many hours. They can be triggered by a myriad of different sources, e.g., the orography, thunderstorms, shear instabilities, convection, etc.

“…By using recent technological developments in atmospheric radars, such as spread-spectrum, MIMO (Multi-input multiple-output), and compressed sensing approaches (Vierinen et al, 2016;Urco et al, 2018Urco et al, , 2019b, SIMONe allows the implementation of MMARIA with several attractive qualities: it is easier, cheaper, and inherently expandable compared to original proposed configurations using traditional pulsed systems. Examples of SIMONe implementations in Germany, Peru and Argentina can be found in several studies (Vierinen et al, 2019;Charuvil Asokan et al, 2020;Vargas et al, 2020;Chau et al, 2021;Conte et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…In November 2018, a short observing campaign was conducted in northern Germany, herein denoted SIMONe2018, in which six existing MMARIA links were complemented with eight additional SIMONe links. During this campaign, we obtained on average two hundred thousand meteor scatter observations per day (e.g., Vierinen et al, 2019;Charuvil Asokan et al, 2020). For reference, a monostatic SMR obtains on average ten thousand meteors per day at a comparable latitude and seasonal time.…”

Section: Introductionmentioning

confidence: 99%

Four-dimensional mesospheric and lower thermospheric wind ﬁelds using Gaussian process regression on multistatic specular meteor radar observations

Volz

Erickson

et al. 2021

Preprint

Self Cite

Abstract. Mesoscale dynamics in the mesosphere and lower thermosphere (MLT) region have been difficult to study from either ground- or satellite-based observations. For understanding of atmospheric coupling processes, important spatial scales at these altitudes range between tens to hundreds of kilometers in the horizontal plane. To date, this scale size is challenging observationally, and so structures are usually parameterized in global circulation models. The advent of multistatic specular meteor radar networks allows exploration of MLT mesocale dynamics on these scales using an increased number of detections and a diversity of viewing angles inherent to multistatic networks. In this work, we introduce a four dimensional wind field inversion method that makes use of Gaussian process regression (GPR), a non-parametric and Bayesian approach. The method takes measured projected wind velocities and prior distributions of the wind velocity as a function of space and time, specified by the user or estimated from the data, and produces posterior distributions for the wind velocity. Computation of the predictive posterior distribution is performed on sampled points of interest and is not necessarily regularly sampled. The main benefits of the GPR method include this non-gridded sampling, the built-in statistical uncertainty estimates, and the ability to horizontally-resolve winds on relatively small scales. The performance of the GPR implementation has been evaluated on Monte Carlo simulations with known distributions using the same spatial and temporal sampling as one day of real meteor measurements. Based on the simulation results we find that the GPR implementation is robust, providing wind fields that are statistically unbiased and with statistical variances that depend on the geometry and are proportional to the prior velocity variances. A conservative and fast approach can be straightforwardly implemented by employing overestimated prior variances and distances, while a more robust but computationally intensive approach can be implemented by employing training and fitting of model parameters. The latter GPR approach has been applied to a 24-hour data set and shown to compare well to previously used homogeneous and gradient methods. Small scale features have reasonably low statistical uncertainties, implying geophysical wind field horizontal structures as low as 20–50 km. We suggest that this GPR approach forms a suitable method for MLT regional and weather studies.