TY - JOUR
T1 - Meteor Radar Vertical Wind Observation Biases and Mathematical Debiasing Strategies Including the 3DVAR+Div Algorithm
AU - Liu, Alan Z.
AU - Qiao, Zishun
AU - Stober, Gunter
AU - Kozlovsky, Alexander
AU - Kuchar, Ales
AU - Jacobi, Christoph
AU - Meek, Chris
AU - Janches, Diego
AU - Liu, Guiping
AU - Tsutsumi, Masaki
AU - Gulbrandsen, Njål
AU - Nozawa, Satonori
AU - Lester, Mark
AU - Belova, Evgenia
AU - Kero, Johan
AU - Mitchell, Nicholas
N1 - Stober, G., Liu, A., Kozlovsky, A., Qiao, Z., Kuchar, A., Jacobi, C., . . . Mitchell, N. (2022). Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm. Atmospheric Measurement Techniques, 15(19), 5769-5792. doi: https://doi.org/10.5194/amt-15-5769-2022
PY - 2022/10/13
Y1 - 2022/10/13
N2 - Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 km altitude region. These systems have been proven to provide reliable and continuous measurements of horizontal winds in the mesosphere and lower thermosphere. Recently, there have been many attempts to utilize specular and/or transverse scatter meteor measurements to estimate vertical winds and vertical wind variability. In this study we investigate potential biases in vertical wind estimation that are intrinsic to the meteor radar observation geometry and scattering mechanism, and we introduce a mathematical debiasing process to mitigate them. This process makes use of a spatiotemporal Laplace filter, which is based on a generalized Tikhonov regularization. Vertical winds obtained from this retrieval algorithm are compared to UA-ICON model data. This comparison reveals good agreement in the statistical moments of the vertical velocity distributions. Furthermore, we present the first observational indications of a forward scatter wind bias. It appears to be caused by the scattering center’s apparent motion along the meteor trajectory when the meteoric plasma column is drifted by the wind. The hypothesis is tested by a radiant mapping of two meteor showers. Finally, we introduce a new retrieval algorithm providing a physically and mathematically sound solution to derive vertical winds and wind variability from multistatic meteor radar networks such as the Nordic Meteor Radar Cluster (NORDIC) and the Chilean Observation Network De meteOr Radars (CONDOR). The new retrieval is called 3DVAR+DIV and includes additional diagnostics such as the horizontal divergence and relative vorticity to ensure a physically consistent solution for all 3D winds in spatially resolved domains. Based on this new algorithm we obtained vertical velocities in the range of w = ± 1–2 m s−1 for most of the analyzed data during 2 years of collection, which is consistent with the values reported from general circulation models (GCMs) for this timescale and spatial resolution.
AB - Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 km altitude region. These systems have been proven to provide reliable and continuous measurements of horizontal winds in the mesosphere and lower thermosphere. Recently, there have been many attempts to utilize specular and/or transverse scatter meteor measurements to estimate vertical winds and vertical wind variability. In this study we investigate potential biases in vertical wind estimation that are intrinsic to the meteor radar observation geometry and scattering mechanism, and we introduce a mathematical debiasing process to mitigate them. This process makes use of a spatiotemporal Laplace filter, which is based on a generalized Tikhonov regularization. Vertical winds obtained from this retrieval algorithm are compared to UA-ICON model data. This comparison reveals good agreement in the statistical moments of the vertical velocity distributions. Furthermore, we present the first observational indications of a forward scatter wind bias. It appears to be caused by the scattering center’s apparent motion along the meteor trajectory when the meteoric plasma column is drifted by the wind. The hypothesis is tested by a radiant mapping of two meteor showers. Finally, we introduce a new retrieval algorithm providing a physically and mathematically sound solution to derive vertical winds and wind variability from multistatic meteor radar networks such as the Nordic Meteor Radar Cluster (NORDIC) and the Chilean Observation Network De meteOr Radars (CONDOR). The new retrieval is called 3DVAR+DIV and includes additional diagnostics such as the horizontal divergence and relative vorticity to ensure a physically consistent solution for all 3D winds in spatially resolved domains. Based on this new algorithm we obtained vertical velocities in the range of w = ± 1–2 m s−1 for most of the analyzed data during 2 years of collection, which is consistent with the values reported from general circulation models (GCMs) for this timescale and spatial resolution.
KW - vertical winds
KW - meteors
KW - mathematical debiasing
UR - https://commons.erau.edu/publication/2095
U2 - 10.5194/amt-15-5769-2022
DO - 10.5194/amt-15-5769-2022
M3 - Article
SN - 1867-8548
VL - 15
JO - Atmospheric Measurement Techniques
JF - Atmospheric Measurement Techniques
ER -