Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018
This dataset contains spectral reflectances, measured at the top-of-atmosphere in the solar spectral range, by the three different sensors GOME, SCIAMACHY and GOME-2A respectively on board the ERS-2, ENVISAT and MetOpA satellites. The time interval covered is January 1996 up to and including Decembe...
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Online Access: | https://doi.pangaea.de/10.1594/PANGAEA.933905 https://doi.org/10.1594/PANGAEA.933905 |
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ftpangaea:oai:pangaea.de:doi:10.1594/PANGAEA.933905 2024-05-19T07:33:13+00:00 Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 Lelli, Luca Vountas, Marco Khosravi, Narges Burrows, John Philipp LATITUDE: 90.000000 * LONGITUDE: 0.000000 2021 application/x-hdf, 12.4 MBytes https://doi.pangaea.de/10.1594/PANGAEA.933905 https://doi.org/10.1594/PANGAEA.933905 en eng PANGAEA Lelli, Luca; Vountas, Marco; Khosravi, Narges; Burrows, John Philipp (2023): Satellite remote sensing of regional and seasonal Arctic cooling showing a multi-decadal trend towards brighter and more liquid clouds. Atmospheric Chemistry and Physics, 23(4), 2579-2611, https://doi.org/10.5194/acp-23-2579-2023 https://doi.pangaea.de/10.1594/PANGAEA.933905 https://doi.org/10.1594/PANGAEA.933905 CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess AC3 Arctic Arctic Amplification pan-Arctic reflectance satellite measurements spectrally resolved top of atmosphere Dataset 2021 ftpangaea https://doi.org/10.1594/PANGAEA.93390510.5194/acp-23-2579-2023 2024-04-23T23:36:33Z This dataset contains spectral reflectances, measured at the top-of-atmosphere in the solar spectral range, by the three different sensors GOME, SCIAMACHY and GOME-2A respectively on board the ERS-2, ENVISAT and MetOpA satellites. The time interval covered is January 1996 up to and including December 2017. The temporal granularity is monthly. The geographic extent is from parallel 60 N to 85 N. The dataset is functional to inspect long-term changes in Arctic reflectivity and to analyze the relative contribution of mainly sea ice, snow and clouds. Data in this version has already been harmonized for the spatial footprint at the ground of the respective sensors and for subsequent analysis with complementary and independent datasets of cloud properties and radiative fluxes. As such, they are not suitable for in-situ validation of ground, air- or ship-borne reflectances. The underlying original reflectances at native resolution are available upon request. Dataset Arctic Arctic Sea ice PANGAEA - Data Publisher for Earth & Environmental Science ENVELOPE(0.000000,0.000000,90.000000,90.000000) |
institution |
Open Polar |
collection |
PANGAEA - Data Publisher for Earth & Environmental Science |
op_collection_id |
ftpangaea |
language |
English |
topic |
AC3 Arctic Arctic Amplification pan-Arctic reflectance satellite measurements spectrally resolved top of atmosphere |
spellingShingle |
AC3 Arctic Arctic Amplification pan-Arctic reflectance satellite measurements spectrally resolved top of atmosphere Lelli, Luca Vountas, Marco Khosravi, Narges Burrows, John Philipp Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 |
topic_facet |
AC3 Arctic Arctic Amplification pan-Arctic reflectance satellite measurements spectrally resolved top of atmosphere |
description |
This dataset contains spectral reflectances, measured at the top-of-atmosphere in the solar spectral range, by the three different sensors GOME, SCIAMACHY and GOME-2A respectively on board the ERS-2, ENVISAT and MetOpA satellites. The time interval covered is January 1996 up to and including December 2017. The temporal granularity is monthly. The geographic extent is from parallel 60 N to 85 N. The dataset is functional to inspect long-term changes in Arctic reflectivity and to analyze the relative contribution of mainly sea ice, snow and clouds. Data in this version has already been harmonized for the spatial footprint at the ground of the respective sensors and for subsequent analysis with complementary and independent datasets of cloud properties and radiative fluxes. As such, they are not suitable for in-situ validation of ground, air- or ship-borne reflectances. The underlying original reflectances at native resolution are available upon request. |
format |
Dataset |
author |
Lelli, Luca Vountas, Marco Khosravi, Narges Burrows, John Philipp |
author_facet |
Lelli, Luca Vountas, Marco Khosravi, Narges Burrows, John Philipp |
author_sort |
Lelli, Luca |
title |
Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 |
title_short |
Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 |
title_full |
Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 |
title_fullStr |
Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 |
title_full_unstemmed |
Pan-Arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 |
title_sort |
pan-arctic spectral reflectances at the top-of-atmosphere between 1996 and 2018 |
publisher |
PANGAEA |
publishDate |
2021 |
url |
https://doi.pangaea.de/10.1594/PANGAEA.933905 https://doi.org/10.1594/PANGAEA.933905 |
op_coverage |
LATITUDE: 90.000000 * LONGITUDE: 0.000000 |
long_lat |
ENVELOPE(0.000000,0.000000,90.000000,90.000000) |
genre |
Arctic Arctic Sea ice |
genre_facet |
Arctic Arctic Sea ice |
op_relation |
Lelli, Luca; Vountas, Marco; Khosravi, Narges; Burrows, John Philipp (2023): Satellite remote sensing of regional and seasonal Arctic cooling showing a multi-decadal trend towards brighter and more liquid clouds. Atmospheric Chemistry and Physics, 23(4), 2579-2611, https://doi.org/10.5194/acp-23-2579-2023 https://doi.pangaea.de/10.1594/PANGAEA.933905 https://doi.org/10.1594/PANGAEA.933905 |
op_rights |
CC-BY-4.0: Creative Commons Attribution 4.0 International Access constraints: unrestricted info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1594/PANGAEA.93390510.5194/acp-23-2579-2023 |
_version_ |
1799471318366683136 |