Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm
<p>Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 <span class="inline-formula">km</span> altitude region. These systems have been proven to provide reliable and continuous measurements of horizontal winds in...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-10-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/15/5769/2022/amt-15-5769-2022.pdf |
| _version_ | 1811240771777462272 |
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| author | G. Stober A. Liu A. Kozlovsky Z. Qiao A. Kuchar C. Jacobi C. Meek D. Janches G. Liu G. Liu M. Tsutsumi M. Tsutsumi N. Gulbrandsen S. Nozawa M. Lester E. Belova J. Kero N. Mitchell N. Mitchell |
| author_facet | G. Stober A. Liu A. Kozlovsky Z. Qiao A. Kuchar C. Jacobi C. Meek D. Janches G. Liu G. Liu M. Tsutsumi M. Tsutsumi N. Gulbrandsen S. Nozawa M. Lester E. Belova J. Kero N. Mitchell N. Mitchell |
| author_sort | G. Stober |
| collection | DOAJ |
| description | <p>Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 <span class="inline-formula">km</span> 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 <span class="inline-formula"><i>w</i></span> <span class="inline-formula">=</span> <span class="inline-formula">±</span> 1–2 <span class="inline-formula">m s<sup>−1</sup></span> 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.</p> |
| first_indexed | 2024-04-12T13:26:12Z |
| format | Article |
| id | doaj.art-441a7e5c7e894dafbabf273e26fe8f9b |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-04-12T13:26:12Z |
| publishDate | 2022-10-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-441a7e5c7e894dafbabf273e26fe8f9b2022-12-22T03:31:18ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482022-10-01155769579210.5194/amt-15-5769-2022Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithmG. Stober0A. Liu1A. Kozlovsky2Z. Qiao3A. Kuchar4C. Jacobi5C. Meek6D. Janches7G. Liu8G. Liu9M. Tsutsumi10M. Tsutsumi11N. Gulbrandsen12S. Nozawa13M. Lester14E. Belova15J. Kero16N. Mitchell17N. Mitchell18Institute of Applied Physics & Oeschger Center for Climate Change Research, Microwave Physics, University of Bern, Bern, SwitzerlandCenter for Space and Atmospheric Research and Department of Physical Sciences, Embry-Riddle Aeronautical University, Daytona Beach, Florida, USASodankylä Geophysical Observatory, University of Oulu, Oulu, FinlandCenter for Space and Atmospheric Research and Department of Physical Sciences, Embry-Riddle Aeronautical University, Daytona Beach, Florida, USAInstitute for Meteorology, Leipzig University, Leipzig, GermanyInstitute for Meteorology, Leipzig University, Leipzig, GermanyPhysics & Engineering Physics, University of Saskatchewan, Saskatoon, CanadaITM Physics Laboratory, Mail Code 675, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USAITM Physics Laboratory, Mail Code 675, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USASpace Sciences Laboratory, University of California, Berkeley, CA, USANational Institute of Polar Research, Tachikawa, JapanThe Graduate University for Advanced Studies (SOKENDAI), Tokyo, JapanTromsø Geophysical Observatory, UiT – The Arctic University of Norway, Tromsø, NorwayDivision for Ionospheric and Magnetospheric Research Institute for Space-Earth Environment Research, Nagoya University, Nagoya, JapanDepartment of Physics and Astronomy, University of Leicester, Leicester, UKSwedish Institute of Space Physics (IRF), Kiruna, SwedenSwedish Institute of Space Physics (IRF), Kiruna, SwedenBritish Antarctic Survey, Cambridge, UKDepartment of Electronic & Electrical Engineering, University of Bath, Bath, UK<p>Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 <span class="inline-formula">km</span> 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 <span class="inline-formula"><i>w</i></span> <span class="inline-formula">=</span> <span class="inline-formula">±</span> 1–2 <span class="inline-formula">m s<sup>−1</sup></span> 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.</p>https://amt.copernicus.org/articles/15/5769/2022/amt-15-5769-2022.pdf |
| spellingShingle | G. Stober A. Liu A. Kozlovsky Z. Qiao A. Kuchar C. Jacobi C. Meek D. Janches G. Liu G. Liu M. Tsutsumi M. Tsutsumi N. Gulbrandsen S. Nozawa M. Lester E. Belova J. Kero N. Mitchell N. Mitchell Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm Atmospheric Measurement Techniques |
| title | Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm |
| title_full | Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm |
| title_fullStr | Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm |
| title_full_unstemmed | Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm |
| title_short | Meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3DVAR+DIV algorithm |
| title_sort | meteor radar vertical wind observation biases and mathematical debiasing strategies including the 3dvar div algorithm |
| url | https://amt.copernicus.org/articles/15/5769/2022/amt-15-5769-2022.pdf |
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