GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1)

Reflected signals of Global Navigation Satellite Systems (GNSS) have been investigated for various applications in remote sensing over the last three decades. The overall research field of GNSS reflectometry includes the retrieval of sea ice parameters as an important application. For this purpose,...

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Bibliographic Details
Main Authors: Semmling, Maximilian, Wickert, Jens, Magnussen, Sylvia, Gerber, Thomas, Spreen, Gunnar, Kaleschke, Lars, Ricker, Robert, Tavri, Aikaterini
Format: Dataset
Language:unknown
Published: GFZ Data Services 2021
Subjects:
Online Access:https://dx.doi.org/10.5880/gfz.1.1.2021.002
https://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=f5ad8763-7206-11eb-9603-497c92695674
id ftdatacite:10.5880/gfz.1.1.2021.002
record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic GNSS Reflectometry
Sea Ice
relative Permittivity
MOSAiC
Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > GPS > GNSS RECEIVER
spellingShingle GNSS Reflectometry
Sea Ice
relative Permittivity
MOSAiC
Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > GPS > GNSS RECEIVER
Semmling, Maximilian
Wickert, Jens
Magnussen, Sylvia
Gerber, Thomas
Spreen, Gunnar
Kaleschke, Lars
Ricker, Robert
Tavri, Aikaterini
GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1)
topic_facet GNSS Reflectometry
Sea Ice
relative Permittivity
MOSAiC
Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > GPS > GNSS RECEIVER
description Reflected signals of Global Navigation Satellite Systems (GNSS) have been investigated for various applications in remote sensing over the last three decades. The overall research field of GNSS reflectometry includes the retrieval of sea ice parameters as an important application. For this purpose, GNSS reflectometry data have been recorded over the Arctic Ocean with a dedicated receiver setup during the MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate). The setup was mounted on the German research icebreaker Polarstern (AWI, 2017) that drifted during nine months of the expedition with the Arctic sea ice. The here described data set comprises the expedition’s first leg in autumn 2019. It includes the drift period of the ship from 27th September until 14th December at about 82°N to 87°N in the Siberian Sector of the Arctic. The data set is based on essential contributions of setup & data recording (by GFZ), maintenance & data transfer (by AWI and MOSAiC partners), processing to data level 1 & documentation (by DLR-SO). The level 1 data consist of GNSS signal power estimates of the direct and reflected signal. Data appear in event files (netcdf format) sorted into day folders. Each event includes observations of a satellite on a continuous track, here, in a satellite elevation range from min. 1° to max. 45°. A dedicated GNSS reflectometry receiver, of GORS (GNSS Occultation Reflectometry Scatterometry) type, was used for the measurements. It is equipped with four antenna front-ends. A master channel and two slave channels are assigned to the front-ends. The master channel tracks the GNSS signal on the direct link. The slave channels are dedicated for observations of reflection events: one at left-handed (LH) and another one at right-handed (RH) circular polarization. The respective up-looking master antenna and port-side looking slave antenna (dual-polarization) are set up with a short baseline on the ship’s observation deck, about 22 m above the water level. The given ship-based geometry results in events with rather short excess paths of the reflected signal relative to the direct signal, much less than the range of a code chip (about 300 m for GPS L1 C/A). Interferometric pattern of direct and reflected signal contributions are observed in the channel. A separation step is required in further processing.
format Dataset
author Semmling, Maximilian
Wickert, Jens
Magnussen, Sylvia
Gerber, Thomas
Spreen, Gunnar
Kaleschke, Lars
Ricker, Robert
Tavri, Aikaterini
author_facet Semmling, Maximilian
Wickert, Jens
Magnussen, Sylvia
Gerber, Thomas
Spreen, Gunnar
Kaleschke, Lars
Ricker, Robert
Tavri, Aikaterini
author_sort Semmling, Maximilian
title GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1)
title_short GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1)
title_full GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1)
title_fullStr GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1)
title_full_unstemmed GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1)
title_sort gnss signal power data for reflectometry recorded during the mosaic expedition (leg 1)
publisher GFZ Data Services
publishDate 2021
url https://dx.doi.org/10.5880/gfz.1.1.2021.002
https://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=f5ad8763-7206-11eb-9603-497c92695674
geographic Arctic
Arctic Ocean
geographic_facet Arctic
Arctic Ocean
genre Arctic
Arctic Ocean
Icebreaker
Sea ice
genre_facet Arctic
Arctic Ocean
Icebreaker
Sea ice
op_relation https://www.ion.org/publications/abstract.cfm?articleID=7461
https://sensor.awi.de/rest/sensors/onlineResources/getOnlineResourcesFile/1238/190919_manual_gnss-atmo_on_mosaic.pdf
https://www.ion.org/publications/abstract.cfm?articleID=7461
https://dx.doi.org/10.17815/jlsrf-3-163
https://dx.doi.org/10.1002/2017rs006272
https://dx.doi.org/10.1002/rds.20049
https://dx.doi.org/10.1109/tgrs.2019.2933911
https://sensor.awi.de/rest/sensors/onlineResources/getOnlineResourcesFile/1238/190919_manual_gnss-atmo_on_mosaic.pdf
https://dx.doi.org/10.5880/gfz.1.1.2021.003
op_rights Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.5880/gfz.1.1.2021.002
https://doi.org/10.17815/jlsrf-3-163
https://doi.org/10.1002/2017rs006272
https://doi.org/10.1002/rds.20049
https://doi.org/10.1109/tgrs.2019.2933911
https://doi.org/10.5880/gfz.1.1.2021.003
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spelling ftdatacite:10.5880/gfz.1.1.2021.002 2023-05-15T14:56:24+02:00 GNSS signal power data for reflectometry recorded during the MOSAiC Expedition (leg 1) Semmling, Maximilian Wickert, Jens Magnussen, Sylvia Gerber, Thomas Spreen, Gunnar Kaleschke, Lars Ricker, Robert Tavri, Aikaterini 2021 https://dx.doi.org/10.5880/gfz.1.1.2021.002 https://dataservices.gfz-potsdam.de/panmetaworks/showshort.php?id=f5ad8763-7206-11eb-9603-497c92695674 unknown GFZ Data Services https://www.ion.org/publications/abstract.cfm?articleID=7461 https://sensor.awi.de/rest/sensors/onlineResources/getOnlineResourcesFile/1238/190919_manual_gnss-atmo_on_mosaic.pdf https://www.ion.org/publications/abstract.cfm?articleID=7461 https://dx.doi.org/10.17815/jlsrf-3-163 https://dx.doi.org/10.1002/2017rs006272 https://dx.doi.org/10.1002/rds.20049 https://dx.doi.org/10.1109/tgrs.2019.2933911 https://sensor.awi.de/rest/sensors/onlineResources/getOnlineResourcesFile/1238/190919_manual_gnss-atmo_on_mosaic.pdf https://dx.doi.org/10.5880/gfz.1.1.2021.003 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY GNSS Reflectometry Sea Ice relative Permittivity MOSAiC Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > GPS > GNSS RECEIVER dataset Dataset 2021 ftdatacite https://doi.org/10.5880/gfz.1.1.2021.002 https://doi.org/10.17815/jlsrf-3-163 https://doi.org/10.1002/2017rs006272 https://doi.org/10.1002/rds.20049 https://doi.org/10.1109/tgrs.2019.2933911 https://doi.org/10.5880/gfz.1.1.2021.003 2021-11-05T12:55:41Z Reflected signals of Global Navigation Satellite Systems (GNSS) have been investigated for various applications in remote sensing over the last three decades. The overall research field of GNSS reflectometry includes the retrieval of sea ice parameters as an important application. For this purpose, GNSS reflectometry data have been recorded over the Arctic Ocean with a dedicated receiver setup during the MOSAiC expedition (Multidisciplinary drifting Observatory for the Study of Arctic Climate). The setup was mounted on the German research icebreaker Polarstern (AWI, 2017) that drifted during nine months of the expedition with the Arctic sea ice. The here described data set comprises the expedition’s first leg in autumn 2019. It includes the drift period of the ship from 27th September until 14th December at about 82°N to 87°N in the Siberian Sector of the Arctic. The data set is based on essential contributions of setup & data recording (by GFZ), maintenance & data transfer (by AWI and MOSAiC partners), processing to data level 1 & documentation (by DLR-SO). The level 1 data consist of GNSS signal power estimates of the direct and reflected signal. Data appear in event files (netcdf format) sorted into day folders. Each event includes observations of a satellite on a continuous track, here, in a satellite elevation range from min. 1° to max. 45°. A dedicated GNSS reflectometry receiver, of GORS (GNSS Occultation Reflectometry Scatterometry) type, was used for the measurements. It is equipped with four antenna front-ends. A master channel and two slave channels are assigned to the front-ends. The master channel tracks the GNSS signal on the direct link. The slave channels are dedicated for observations of reflection events: one at left-handed (LH) and another one at right-handed (RH) circular polarization. The respective up-looking master antenna and port-side looking slave antenna (dual-polarization) are set up with a short baseline on the ship’s observation deck, about 22 m above the water level. The given ship-based geometry results in events with rather short excess paths of the reflected signal relative to the direct signal, much less than the range of a code chip (about 300 m for GPS L1 C/A). Interferometric pattern of direct and reflected signal contributions are observed in the channel. A separation step is required in further processing. Dataset Arctic Arctic Ocean Icebreaker Sea ice DataCite Metadata Store (German National Library of Science and Technology) Arctic Arctic Ocean