Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ...
<!--!introduction!--> Solar radiation drives numerous geophysical and biological processes in Antarctica, including sea ice melting, ice sheet mass balance, and the photosynthetic processes of phytoplankton in the polar marine environment. Despite the ability of reanalysis and satellite produc...
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GFZ German Research Centre for Geosciences
2023
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Online Access: | https://dx.doi.org/10.57757/iugg23-1999 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017544 |
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ftdatacite:10.57757/iugg23-1999 2023-06-11T04:06:47+02:00 Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ... Zeng, Zhaoliang Ding, Minghu 2023 https://dx.doi.org/10.57757/iugg23-1999 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017544 unknown GFZ German Research Centre for Geosciences Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 ConferencePaper Oral Article 2023 ftdatacite https://doi.org/10.57757/iugg23-1999 2023-06-01T11:57:52Z <!--!introduction!--> Solar radiation drives numerous geophysical and biological processes in Antarctica, including sea ice melting, ice sheet mass balance, and the photosynthetic processes of phytoplankton in the polar marine environment. Despite the ability of reanalysis and satellite products to provide valuable insights into global-scale solar radiation, the ground-based solar radiation in the polar region remains poorly understood due to the harsh conditions in Antarctica. This study evaluated the performance of empirical models and machine learning models to establish a long-term daily global solar radiation (DGSR) dataset using meteorological observation data from Zhongshan Station and the Great Wall Station. The machine learning method was found to outperform the empirical formula method, with the random forest (XGBoost) model demonstrating the best performance in terms of DGSR hindcast estimation at the Zhongshan Station (Great Wall Station). The annual DGSR at both stations showed a similar ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... Conference Object Antarc* Antarctic Antarctica Ice Sheet Sea ice DataCite Metadata Store (German National Library of Science and Technology) Antarctic Great Wall Station ENVELOPE(-58.970,-58.970,-62.217,-62.217) Zhongshan ENVELOPE(76.371,76.371,-69.373,-69.373) Zhongshan Station ENVELOPE(76.371,76.371,-69.373,-69.373) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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ftdatacite |
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unknown |
description |
<!--!introduction!--> Solar radiation drives numerous geophysical and biological processes in Antarctica, including sea ice melting, ice sheet mass balance, and the photosynthetic processes of phytoplankton in the polar marine environment. Despite the ability of reanalysis and satellite products to provide valuable insights into global-scale solar radiation, the ground-based solar radiation in the polar region remains poorly understood due to the harsh conditions in Antarctica. This study evaluated the performance of empirical models and machine learning models to establish a long-term daily global solar radiation (DGSR) dataset using meteorological observation data from Zhongshan Station and the Great Wall Station. The machine learning method was found to outperform the empirical formula method, with the random forest (XGBoost) model demonstrating the best performance in terms of DGSR hindcast estimation at the Zhongshan Station (Great Wall Station). The annual DGSR at both stations showed a similar ... : The 28th IUGG General Assembly (IUGG2023) (Berlin 2023) ... |
format |
Conference Object |
author |
Zeng, Zhaoliang Ding, Minghu |
spellingShingle |
Zeng, Zhaoliang Ding, Minghu Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ... |
author_facet |
Zeng, Zhaoliang Ding, Minghu |
author_sort |
Zeng, Zhaoliang |
title |
Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ... |
title_short |
Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ... |
title_full |
Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ... |
title_fullStr |
Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ... |
title_full_unstemmed |
Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station ... |
title_sort |
estimation and changes of long-time global solar radiation at china’s antarctic zhongshan station and great wall station ... |
publisher |
GFZ German Research Centre for Geosciences |
publishDate |
2023 |
url |
https://dx.doi.org/10.57757/iugg23-1999 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017544 |
long_lat |
ENVELOPE(-58.970,-58.970,-62.217,-62.217) ENVELOPE(76.371,76.371,-69.373,-69.373) ENVELOPE(76.371,76.371,-69.373,-69.373) |
geographic |
Antarctic Great Wall Station Zhongshan Zhongshan Station |
geographic_facet |
Antarctic Great Wall Station Zhongshan Zhongshan Station |
genre |
Antarc* Antarctic Antarctica Ice Sheet Sea ice |
genre_facet |
Antarc* Antarctic Antarctica Ice Sheet 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/10.57757/iugg23-1999 |
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1768378943673466880 |