Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ...
The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic...
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Online Access: | https://dx.doi.org/10.57760/sciencedb.16286 https://www.scidb.cn/en/detail?dataSetId=4587cf1d46fa4b3ca82a35e858339293 |
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ftdatacite:10.57760/sciencedb.16286 2024-04-28T08:05:56+00:00 Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... Shu, Qi Wang, Qiang Song, Zhenya Gao, Gui Hailong Liu Shizhu Wang He, Yan Fangli Qiao 2024 https://dx.doi.org/10.57760/sciencedb.16286 https://www.scidb.cn/en/detail?dataSetId=4587cf1d46fa4b3ca82a35e858339293 en eng Science Data Bank Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Earth science Arctic Ocean dynamical downscaling climate change climate models sea ice ice-ocean model SSP245 SSP585 CMIP6 FIO-ESM FESOM dataset Dataset 2024 ftdatacite https://doi.org/10.57760/sciencedb.16286 2024-04-02T12:48:02Z The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for ... : The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for ... Dataset Arctic Arctic Ocean Climate change Sea ice DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
Earth science Arctic Ocean dynamical downscaling climate change climate models sea ice ice-ocean model SSP245 SSP585 CMIP6 FIO-ESM FESOM |
spellingShingle |
Earth science Arctic Ocean dynamical downscaling climate change climate models sea ice ice-ocean model SSP245 SSP585 CMIP6 FIO-ESM FESOM Shu, Qi Wang, Qiang Song, Zhenya Gao, Gui Hailong Liu Shizhu Wang He, Yan Fangli Qiao Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... |
topic_facet |
Earth science Arctic Ocean dynamical downscaling climate change climate models sea ice ice-ocean model SSP245 SSP585 CMIP6 FIO-ESM FESOM |
description |
The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for ... : The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for ... |
format |
Dataset |
author |
Shu, Qi Wang, Qiang Song, Zhenya Gao, Gui Hailong Liu Shizhu Wang He, Yan Fangli Qiao |
author_facet |
Shu, Qi Wang, Qiang Song, Zhenya Gao, Gui Hailong Liu Shizhu Wang He, Yan Fangli Qiao |
author_sort |
Shu, Qi |
title |
Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... |
title_short |
Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... |
title_full |
Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... |
title_fullStr |
Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... |
title_full_unstemmed |
Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... |
title_sort |
arctic ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... : arctic ocean dynamical downscaling data (ssp245) for understanding past and future climate change ... |
publisher |
Science Data Bank |
publishDate |
2024 |
url |
https://dx.doi.org/10.57760/sciencedb.16286 https://www.scidb.cn/en/detail?dataSetId=4587cf1d46fa4b3ca82a35e858339293 |
genre |
Arctic Arctic Ocean Climate change Sea ice |
genre_facet |
Arctic Arctic Ocean Climate change Sea ice |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.57760/sciencedb.16286 |
_version_ |
1797575679451070464 |