Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation
Diverse and severe weather conditions and rapid climate change rates in the Arctic emphasize the need for high-resolution climatic and environmental data that cannot be obtained from the scarce observational networks. This study presents a new detailed hydrometeorological dataset for the Russian Arc...
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ftmdpi:oai:mdpi.com:/2073-4433/12/3/350/ 2023-08-20T04:03:55+02:00 Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation Vladimir Platonov Mikhail Varentsov agris 2021-03-08 application/pdf https://doi.org/10.3390/atmos12030350 EN eng Multidisciplinary Digital Publishing Institute Climatology https://dx.doi.org/10.3390/atmos12030350 https://creativecommons.org/licenses/by/4.0/ Atmosphere; Volume 12; Issue 3; Pages: 350 COSMO-CLM COSMO regional climate modeling Arctic climate extreme climate statistics verification hindcast long-term hydrometeorological dataset Text 2021 ftmdpi https://doi.org/10.3390/atmos12030350 2023-08-01T01:13:48Z Diverse and severe weather conditions and rapid climate change rates in the Arctic emphasize the need for high-resolution climatic and environmental data that cannot be obtained from the scarce observational networks. This study presents a new detailed hydrometeorological dataset for the Russian Arctic region, obtained as a long-term hindcast with the nonhydrostatic atmospheric model COSMO-CLM for the 1980–2016 period. The modeling workflow, evaluation techniques, and preliminary analysis of the obtained dataset are discussed. The model domain included the Barents, Kara, and Laptev Seas with ≈12-km grid spacing. The optimal model setup was chosen based on preliminary simulations for several summer and winter periods with varied options, and included the usage of ERA-Interim reanalysis data as forcing data, the new model version 5.05 with so-called ICON-based physics, and a spectral nudging technique. The wind speed and temperature climatology in the new COSMO-CLM dataset closely agreed with the ERA-Interim reanalysis, but with detailed spatial patterns. The added value of the higher-resolution COSMO-CLM data with respect to the ERA-Interim was most pronounced for higher wind speeds during downslope windstorms with the influence of mountain ranges on the temperature patterns, including surface temperature inversions. The potential applications and plans of further product development are also discussed. Text Arctic Climate change laptev MDPI Open Access Publishing Arctic Atmosphere 12 3 350 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
COSMO-CLM COSMO regional climate modeling Arctic climate extreme climate statistics verification hindcast long-term hydrometeorological dataset |
spellingShingle |
COSMO-CLM COSMO regional climate modeling Arctic climate extreme climate statistics verification hindcast long-term hydrometeorological dataset Vladimir Platonov Mikhail Varentsov Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation |
topic_facet |
COSMO-CLM COSMO regional climate modeling Arctic climate extreme climate statistics verification hindcast long-term hydrometeorological dataset |
description |
Diverse and severe weather conditions and rapid climate change rates in the Arctic emphasize the need for high-resolution climatic and environmental data that cannot be obtained from the scarce observational networks. This study presents a new detailed hydrometeorological dataset for the Russian Arctic region, obtained as a long-term hindcast with the nonhydrostatic atmospheric model COSMO-CLM for the 1980–2016 period. The modeling workflow, evaluation techniques, and preliminary analysis of the obtained dataset are discussed. The model domain included the Barents, Kara, and Laptev Seas with ≈12-km grid spacing. The optimal model setup was chosen based on preliminary simulations for several summer and winter periods with varied options, and included the usage of ERA-Interim reanalysis data as forcing data, the new model version 5.05 with so-called ICON-based physics, and a spectral nudging technique. The wind speed and temperature climatology in the new COSMO-CLM dataset closely agreed with the ERA-Interim reanalysis, but with detailed spatial patterns. The added value of the higher-resolution COSMO-CLM data with respect to the ERA-Interim was most pronounced for higher wind speeds during downslope windstorms with the influence of mountain ranges on the temperature patterns, including surface temperature inversions. The potential applications and plans of further product development are also discussed. |
format |
Text |
author |
Vladimir Platonov Mikhail Varentsov |
author_facet |
Vladimir Platonov Mikhail Varentsov |
author_sort |
Vladimir Platonov |
title |
Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation |
title_short |
Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation |
title_full |
Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation |
title_fullStr |
Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation |
title_full_unstemmed |
Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation |
title_sort |
introducing a new detailed long-term cosmo-clm hindcast for the russian arctic and the first results of its evaluation |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
url |
https://doi.org/10.3390/atmos12030350 |
op_coverage |
agris |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change laptev |
genre_facet |
Arctic Climate change laptev |
op_source |
Atmosphere; Volume 12; Issue 3; Pages: 350 |
op_relation |
Climatology https://dx.doi.org/10.3390/atmos12030350 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/atmos12030350 |
container_title |
Atmosphere |
container_volume |
12 |
container_issue |
3 |
container_start_page |
350 |
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1774714347970363392 |