Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard
We present Sval_Imp, a high-resolution gridded dataset designed for forcing models of terrestrial surface processes on Svalbard. The dataset is defined on a 1 km grid covering the archipelago of Svalbard, located in the Norwegian Arctic (74–82∘ N). Using a hybrid methodology, combining multidimensio...
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fttriple:oai:gotriple.eu:oai:doaj.org/article:27ac6b7016f4442abccdba614db21710 2023-05-15T15:10:41+02:00 Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard T. V. Schuler T. I. Østby 2020-04-01 https://doi.org/10.5194/essd-12-875-2020 https://www.earth-syst-sci-data.net/12/875/2020/essd-12-875-2020.pdf https://doaj.org/article/27ac6b7016f4442abccdba614db21710 en eng Copernicus Publications doi:10.5194/essd-12-875-2020 1866-3508 1866-3516 https://www.earth-syst-sci-data.net/12/875/2020/essd-12-875-2020.pdf https://doaj.org/article/27ac6b7016f4442abccdba614db21710 undefined Earth System Science Data, Vol 12, Pp 875-885 (2020) info geo Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2020 fttriple https://doi.org/10.5194/essd-12-875-2020 2023-01-22T18:11:02Z We present Sval_Imp, a high-resolution gridded dataset designed for forcing models of terrestrial surface processes on Svalbard. The dataset is defined on a 1 km grid covering the archipelago of Svalbard, located in the Norwegian Arctic (74–82∘ N). Using a hybrid methodology, combining multidimensional interpolation with simple dynamical modeling, the atmospheric reanalyses ERA-40 and ERA-Interim by the European Centre for Medium-Range Weather Forecasting have been downscaled to cover the period 1957–2017 at steps of 6 h. The dataset is publicly available from a data repository. In this paper, we describe the methodology used to construct the dataset, present the organization of the data in the repository and discuss the performance of the downscaling procedure. In doing so, the dataset is compared to a wealth of data available from operational and project-based measurements. The quality of the downscaled dataset is found to vary in space and time, but it generally represents an improvement compared to unscaled values, especially for precipitation. Whereas operational records are biased to low elevations around the fringes, we stress the hitherto underused potential of project-based measurements at higher elevation and in the interior of the archipelago for evaluating atmospheric models. For instance, records of snow accumulation on large ice masses may represent measures of seasonally integrated precipitation in regions sensitive to the downscaling procedure and thus providing added value. Sval_Imp (Schuler, 2018) is publicly available from the Norwegian Research Data Archive NIRD, a data repository (https://doi.org/10.11582/2018.00006). Article in Journal/Newspaper Arctic Climate change Svalbard Unknown Arctic Svalbard Earth System Science Data 12 2 875 885 |
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English |
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info geo |
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info geo T. V. Schuler T. I. Østby Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard |
topic_facet |
info geo |
description |
We present Sval_Imp, a high-resolution gridded dataset designed for forcing models of terrestrial surface processes on Svalbard. The dataset is defined on a 1 km grid covering the archipelago of Svalbard, located in the Norwegian Arctic (74–82∘ N). Using a hybrid methodology, combining multidimensional interpolation with simple dynamical modeling, the atmospheric reanalyses ERA-40 and ERA-Interim by the European Centre for Medium-Range Weather Forecasting have been downscaled to cover the period 1957–2017 at steps of 6 h. The dataset is publicly available from a data repository. In this paper, we describe the methodology used to construct the dataset, present the organization of the data in the repository and discuss the performance of the downscaling procedure. In doing so, the dataset is compared to a wealth of data available from operational and project-based measurements. The quality of the downscaled dataset is found to vary in space and time, but it generally represents an improvement compared to unscaled values, especially for precipitation. Whereas operational records are biased to low elevations around the fringes, we stress the hitherto underused potential of project-based measurements at higher elevation and in the interior of the archipelago for evaluating atmospheric models. For instance, records of snow accumulation on large ice masses may represent measures of seasonally integrated precipitation in regions sensitive to the downscaling procedure and thus providing added value. Sval_Imp (Schuler, 2018) is publicly available from the Norwegian Research Data Archive NIRD, a data repository (https://doi.org/10.11582/2018.00006). |
format |
Article in Journal/Newspaper |
author |
T. V. Schuler T. I. Østby |
author_facet |
T. V. Schuler T. I. Østby |
author_sort |
T. V. Schuler |
title |
Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard |
title_short |
Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard |
title_full |
Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard |
title_fullStr |
Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard |
title_full_unstemmed |
Sval_Imp: a gridded forcing dataset for climate change impact research on Svalbard |
title_sort |
sval_imp: a gridded forcing dataset for climate change impact research on svalbard |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/essd-12-875-2020 https://www.earth-syst-sci-data.net/12/875/2020/essd-12-875-2020.pdf https://doaj.org/article/27ac6b7016f4442abccdba614db21710 |
geographic |
Arctic Svalbard |
geographic_facet |
Arctic Svalbard |
genre |
Arctic Climate change Svalbard |
genre_facet |
Arctic Climate change Svalbard |
op_source |
Earth System Science Data, Vol 12, Pp 875-885 (2020) |
op_relation |
doi:10.5194/essd-12-875-2020 1866-3508 1866-3516 https://www.earth-syst-sci-data.net/12/875/2020/essd-12-875-2020.pdf https://doaj.org/article/27ac6b7016f4442abccdba614db21710 |
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op_doi |
https://doi.org/10.5194/essd-12-875-2020 |
container_title |
Earth System Science Data |
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12 |
container_issue |
2 |
container_start_page |
875 |
op_container_end_page |
885 |
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1766341659227848704 |