Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regi...

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Published in:Ocean Science
Main Authors: Dybkjær, G., Tonboe, R., Høyer, J. L.
Format: Text
Language:English
Published: 2018
Subjects:
Online Access:https://doi.org/10.5194/os-8-959-2012
https://os.copernicus.org/articles/8/959/2012/
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spelling ftcopernicus:oai:publications.copernicus.org:os14719 2023-05-15T14:43:53+02:00 Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data Dybkjær, G. Tonboe, R. Høyer, J. L. 2018-01-15 application/pdf https://doi.org/10.5194/os-8-959-2012 https://os.copernicus.org/articles/8/959/2012/ eng eng doi:10.5194/os-8-959-2012 https://os.copernicus.org/articles/8/959/2012/ eISSN: 1812-0792 Text 2018 ftcopernicus https://doi.org/10.5194/os-8-959-2012 2020-07-20T16:25:39Z The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere. Text Arctic Greenland Ice cap Sea ice Copernicus Publications: E-Journals Arctic Greenland Ocean Science 8 6 959 970
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.
format Text
author Dybkjær, G.
Tonboe, R.
Høyer, J. L.
spellingShingle Dybkjær, G.
Tonboe, R.
Høyer, J. L.
Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data
author_facet Dybkjær, G.
Tonboe, R.
Høyer, J. L.
author_sort Dybkjær, G.
title Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data
title_short Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data
title_full Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data
title_fullStr Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data
title_full_unstemmed Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data
title_sort arctic surface temperatures from metop avhrr compared to in situ ocean and land data
publishDate 2018
url https://doi.org/10.5194/os-8-959-2012
https://os.copernicus.org/articles/8/959/2012/
geographic Arctic
Greenland
geographic_facet Arctic
Greenland
genre Arctic
Greenland
Ice cap
Sea ice
genre_facet Arctic
Greenland
Ice cap
Sea ice
op_source eISSN: 1812-0792
op_relation doi:10.5194/os-8-959-2012
https://os.copernicus.org/articles/8/959/2012/
op_doi https://doi.org/10.5194/os-8-959-2012
container_title Ocean Science
container_volume 8
container_issue 6
container_start_page 959
op_container_end_page 970
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