nAMIP simulation ...
This dataset is used for analysis of recent precipitation change over Taklamakan and Gobi Desert. Please refer to this work for more information: Dong, W., Ming, Y., Deng, Y. et al. Recent wetting trend over Taklamakan and Gobi Desert dominated by internal variability. Nat Commun 15, 4379 (2024). ht...
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Online Access: | https://dx.doi.org/10.5281/zenodo.11110868 https://zenodo.org/doi/10.5281/zenodo.11110868 |
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ftdatacite:10.5281/zenodo.11110868 2024-09-09T20:07:43+00:00 nAMIP simulation ... Dong, Wenhao Ming, Yi Deng, Yi Shen, Zhaoyi 2024 https://dx.doi.org/10.5281/zenodo.11110868 https://zenodo.org/doi/10.5281/zenodo.11110868 unknown Zenodo https://dx.doi.org/10.5281/zenodo.11110869 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 article CreativeWork Model 2024 ftdatacite https://doi.org/10.5281/zenodo.1111086810.5281/zenodo.11110869 2024-06-17T10:23:32Z This dataset is used for analysis of recent precipitation change over Taklamakan and Gobi Desert. Please refer to this work for more information: Dong, W., Ming, Y., Deng, Y. et al. Recent wetting trend over Taklamakan and Gobi Desert dominated by internal variability. Nat Commun 15, 4379 (2024). https://doi.org/10.1038/s41467-024-48743-x This dataset contains both daily and monthly variables generated by a nugded simulation using the GFDL AM4. The AM4 model, as described in Zhao et al. (2018a,b), is the atmospheric component of the GFDL coupled physical climate model CM4, GFDL’s contribution to CMIP6 (Held et al. 2019 JAMES). The model is driven by the observed SST and sea ice conditions, greenhouse gases, and natural and anthropogenic aerosol emissions. The model horizontal winds are nudged to the 3-hourly averaged products from the MERRA-2 reanalysis with a nudging time scale of 6 h. The simulation period covers 2000-2019. Daily variables include precipitation, specific humidity (700 hPa), geopotential ... Article in Journal/Newspaper Sea ice DataCite Merra ENVELOPE(12.615,12.615,65.816,65.816) |
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This dataset is used for analysis of recent precipitation change over Taklamakan and Gobi Desert. Please refer to this work for more information: Dong, W., Ming, Y., Deng, Y. et al. Recent wetting trend over Taklamakan and Gobi Desert dominated by internal variability. Nat Commun 15, 4379 (2024). https://doi.org/10.1038/s41467-024-48743-x This dataset contains both daily and monthly variables generated by a nugded simulation using the GFDL AM4. The AM4 model, as described in Zhao et al. (2018a,b), is the atmospheric component of the GFDL coupled physical climate model CM4, GFDL’s contribution to CMIP6 (Held et al. 2019 JAMES). The model is driven by the observed SST and sea ice conditions, greenhouse gases, and natural and anthropogenic aerosol emissions. The model horizontal winds are nudged to the 3-hourly averaged products from the MERRA-2 reanalysis with a nudging time scale of 6 h. The simulation period covers 2000-2019. Daily variables include precipitation, specific humidity (700 hPa), geopotential ... |
format |
Article in Journal/Newspaper |
author |
Dong, Wenhao Ming, Yi Deng, Yi Shen, Zhaoyi |
spellingShingle |
Dong, Wenhao Ming, Yi Deng, Yi Shen, Zhaoyi nAMIP simulation ... |
author_facet |
Dong, Wenhao Ming, Yi Deng, Yi Shen, Zhaoyi |
author_sort |
Dong, Wenhao |
title |
nAMIP simulation ... |
title_short |
nAMIP simulation ... |
title_full |
nAMIP simulation ... |
title_fullStr |
nAMIP simulation ... |
title_full_unstemmed |
nAMIP simulation ... |
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namip simulation ... |
publisher |
Zenodo |
publishDate |
2024 |
url |
https://dx.doi.org/10.5281/zenodo.11110868 https://zenodo.org/doi/10.5281/zenodo.11110868 |
long_lat |
ENVELOPE(12.615,12.615,65.816,65.816) |
geographic |
Merra |
geographic_facet |
Merra |
genre |
Sea ice |
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Sea ice |
op_relation |
https://dx.doi.org/10.5281/zenodo.11110869 |
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/10.5281/zenodo.1111086810.5281/zenodo.11110869 |
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1809941377269628928 |