Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval
Ground-based remote sensing of atmospheric parameters is often limited to single station observations by vertical profiles at a certain geographic location. This is a limiting factor for investigating gravity wave dynamics as the spatial information is often missing, e.g., horizontal wavelength, pro...
Published in: | Atmospheric Measurement Techniques |
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ftembryriddleaun:oai:commons.erau.edu:publication-2975 2023-10-01T03:54:15+02:00 Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval Stober, Gunter Liu, Alan Z. Qiao, Zishun Kozlovsky, Alexander Tsutsumi, Masaki Hall, Chris Nozawa, Satonori Lester, Mark Belova, Evgenia Kero, Johan Espy, Patrick J Hibbins, Robert E Mitchell, Nicholas 2372595, 2482071 2021-10-08T07:00:00Z application/pdf https://commons.erau.edu/publication/1803 https://doi.org/10.5194/amt-14-6509-2021 https://commons.erau.edu/context/publication/article/2975/viewcontent/Atmospheric.pdf unknown Scholarly Commons https://commons.erau.edu/publication/1803 doi:10.5194/amt-14-6509-2021 https://commons.erau.edu/context/publication/article/2975/viewcontent/Atmospheric.pdf Publications remote sensing gravity wave dynamics retrieval algorithm multistatic meteor radar networks Atmospheric Sciences text 2021 ftembryriddleaun https://doi.org/10.5194/amt-14-6509-2021 2023-09-02T19:04:01Z Ground-based remote sensing of atmospheric parameters is often limited to single station observations by vertical profiles at a certain geographic location. This is a limiting factor for investigating gravity wave dynamics as the spatial information is often missing, e.g., horizontal wavelength, propagation direction or intrinsic frequency. In this study, we present a new retrieval algorithm for multistatic meteor radar networks to obtain tomographic 3-D wind fields within a pre-defined domain area. The algorithm is part of the Agile Software for Gravity wAve Regional Dynamics (ASGARD) and called 3D-Var, and based on the optimal estimation technique and Bayesian statistics. The performance of the 3D-Var retrieval is demonstrated using two meteor radar networks: the Nordic Meteor Radar Cluster and the Chilean Observation Network De Meteor Radars (CONDOR). The optimal estimation implementation provide statistically sound solutions and diagnostics from the averaging kernels and measurement response. We present initial scientific results such as body forces of breaking gravity waves leading to two counter-rotating vortices and horizontal wavelength spectra indicating a transition between the rotational k-3 and divergent k-5/3 mode at scales of 80–120 km. In addition, we performed a keogram analysis over extended periods to reflect the latitudinal and temporal impact of a minor sudden stratospheric warming in December 2019. Finally, we demonstrate the applicability of the 3D-Var algorithm to perform large-scale retrievals to derive meteorological wind maps covering a latitude region from Svalbard, north of the European Arctic mainland, to central Norway. Text Arctic Svalbard Embry-Riddle Aeronautical University: ERAU Scholarly Commons Arctic Svalbard Norway Atmospheric Measurement Techniques 14 10 6509 6532 |
institution |
Open Polar |
collection |
Embry-Riddle Aeronautical University: ERAU Scholarly Commons |
op_collection_id |
ftembryriddleaun |
language |
unknown |
topic |
remote sensing gravity wave dynamics retrieval algorithm multistatic meteor radar networks Atmospheric Sciences |
spellingShingle |
remote sensing gravity wave dynamics retrieval algorithm multistatic meteor radar networks Atmospheric Sciences Stober, Gunter Liu, Alan Z. Qiao, Zishun Kozlovsky, Alexander Tsutsumi, Masaki Hall, Chris Nozawa, Satonori Lester, Mark Belova, Evgenia Kero, Johan Espy, Patrick J Hibbins, Robert E Mitchell, Nicholas Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval |
topic_facet |
remote sensing gravity wave dynamics retrieval algorithm multistatic meteor radar networks Atmospheric Sciences |
description |
Ground-based remote sensing of atmospheric parameters is often limited to single station observations by vertical profiles at a certain geographic location. This is a limiting factor for investigating gravity wave dynamics as the spatial information is often missing, e.g., horizontal wavelength, propagation direction or intrinsic frequency. In this study, we present a new retrieval algorithm for multistatic meteor radar networks to obtain tomographic 3-D wind fields within a pre-defined domain area. The algorithm is part of the Agile Software for Gravity wAve Regional Dynamics (ASGARD) and called 3D-Var, and based on the optimal estimation technique and Bayesian statistics. The performance of the 3D-Var retrieval is demonstrated using two meteor radar networks: the Nordic Meteor Radar Cluster and the Chilean Observation Network De Meteor Radars (CONDOR). The optimal estimation implementation provide statistically sound solutions and diagnostics from the averaging kernels and measurement response. We present initial scientific results such as body forces of breaking gravity waves leading to two counter-rotating vortices and horizontal wavelength spectra indicating a transition between the rotational k-3 and divergent k-5/3 mode at scales of 80–120 km. In addition, we performed a keogram analysis over extended periods to reflect the latitudinal and temporal impact of a minor sudden stratospheric warming in December 2019. Finally, we demonstrate the applicability of the 3D-Var algorithm to perform large-scale retrievals to derive meteorological wind maps covering a latitude region from Svalbard, north of the European Arctic mainland, to central Norway. |
author2 |
2372595, 2482071 |
format |
Text |
author |
Stober, Gunter Liu, Alan Z. Qiao, Zishun Kozlovsky, Alexander Tsutsumi, Masaki Hall, Chris Nozawa, Satonori Lester, Mark Belova, Evgenia Kero, Johan Espy, Patrick J Hibbins, Robert E Mitchell, Nicholas |
author_facet |
Stober, Gunter Liu, Alan Z. Qiao, Zishun Kozlovsky, Alexander Tsutsumi, Masaki Hall, Chris Nozawa, Satonori Lester, Mark Belova, Evgenia Kero, Johan Espy, Patrick J Hibbins, Robert E Mitchell, Nicholas |
author_sort |
Stober, Gunter |
title |
Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval |
title_short |
Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval |
title_full |
Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval |
title_fullStr |
Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval |
title_full_unstemmed |
Atmospheric Tomography Using the Nordic Meteor Radar Cluster And Chilean Observation Network de Meteor Radars: Network Details and 3D-Var Retrieval |
title_sort |
atmospheric tomography using the nordic meteor radar cluster and chilean observation network de meteor radars: network details and 3d-var retrieval |
publisher |
Scholarly Commons |
publishDate |
2021 |
url |
https://commons.erau.edu/publication/1803 https://doi.org/10.5194/amt-14-6509-2021 https://commons.erau.edu/context/publication/article/2975/viewcontent/Atmospheric.pdf |
geographic |
Arctic Svalbard Norway |
geographic_facet |
Arctic Svalbard Norway |
genre |
Arctic Svalbard |
genre_facet |
Arctic Svalbard |
op_source |
Publications |
op_relation |
https://commons.erau.edu/publication/1803 doi:10.5194/amt-14-6509-2021 https://commons.erau.edu/context/publication/article/2975/viewcontent/Atmospheric.pdf |
op_doi |
https://doi.org/10.5194/amt-14-6509-2021 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
14 |
container_issue |
10 |
container_start_page |
6509 |
op_container_end_page |
6532 |
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1778521679543140352 |