On the importance of representing snow over sea-ice for simulating the Arctic boundary layer

Correctly representing the snow on sea-ice in coupled numerical weather prediction models has great potential to improve weather forecast and climate monitoring applications, such as climate reanalyses, which are usually produced using such systems.In this study two different methodologies to accoun...

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Main Author: Arduini Gabriele
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2022
Subjects:
Sea ice
Online Access:https://doi.org/10.5281/zenodo.6576248
id ftzenodo:oai:zenodo.org:6576248
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spelling ftzenodo:oai:zenodo.org:6576248 2024-09-15T18:34:21+00:00 On the importance of representing snow over sea-ice for simulating the Arctic boundary layer Arduini Gabriele 2022-05-24 https://doi.org/10.5281/zenodo.6576248 unknown Zenodo https://zenodo.org/communities/applicate https://doi.org/10.5281/zenodo.6576247 https://doi.org/10.5281/zenodo.6576248 oai:zenodo.org:6576248 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/other 2022 ftzenodo https://doi.org/10.5281/zenodo.657624810.5281/zenodo.6576247 2024-07-26T22:39:30Z Correctly representing the snow on sea-ice in coupled numerical weather prediction models has great potential to improve weather forecast and climate monitoring applications, such as climate reanalyses, which are usually produced using such systems.In this study two different methodologies to account for the effect of the snowpack accumulating over the sea-ice in 5-day global forecasts are compared. This dataset contains the high-resolution (dx=9km) model data for the different simulations, with and without the snow over sea-ice, co-located with observationsat the locations of the SHEBA and N-ICE2015 field campaigns. The dataset also contains the daily averagedskin temperature, for the different simulations (interpolated on 0.25x0.25) performed over the extended time period, 2015-01-01 to 2015-02-28. Other/Unknown Material Sea ice Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description Correctly representing the snow on sea-ice in coupled numerical weather prediction models has great potential to improve weather forecast and climate monitoring applications, such as climate reanalyses, which are usually produced using such systems.In this study two different methodologies to account for the effect of the snowpack accumulating over the sea-ice in 5-day global forecasts are compared. This dataset contains the high-resolution (dx=9km) model data for the different simulations, with and without the snow over sea-ice, co-located with observationsat the locations of the SHEBA and N-ICE2015 field campaigns. The dataset also contains the daily averagedskin temperature, for the different simulations (interpolated on 0.25x0.25) performed over the extended time period, 2015-01-01 to 2015-02-28.
format Other/Unknown Material
author Arduini Gabriele
spellingShingle Arduini Gabriele
On the importance of representing snow over sea-ice for simulating the Arctic boundary layer
author_facet Arduini Gabriele
author_sort Arduini Gabriele
title On the importance of representing snow over sea-ice for simulating the Arctic boundary layer
title_short On the importance of representing snow over sea-ice for simulating the Arctic boundary layer
title_full On the importance of representing snow over sea-ice for simulating the Arctic boundary layer
title_fullStr On the importance of representing snow over sea-ice for simulating the Arctic boundary layer
title_full_unstemmed On the importance of representing snow over sea-ice for simulating the Arctic boundary layer
title_sort on the importance of representing snow over sea-ice for simulating the arctic boundary layer
publisher Zenodo
publishDate 2022
url https://doi.org/10.5281/zenodo.6576248
genre Sea ice
genre_facet Sea ice
op_relation https://zenodo.org/communities/applicate
https://doi.org/10.5281/zenodo.6576247
https://doi.org/10.5281/zenodo.6576248
oai:zenodo.org:6576248
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.657624810.5281/zenodo.6576247
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