Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station

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 insig...

Full description

Bibliographic Details
Main Authors: Zeng, Z., Ding, M.
Format: Conference Object
Language:English
Published: 2023
Subjects:
Online Access:https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017544
id ftgfzpotsdam:oai:gfzpublic.gfz-potsdam.de:item_5017544
record_format openpolar
spelling ftgfzpotsdam:oai:gfzpublic.gfz-potsdam.de:item_5017544 2023-06-11T04:04:41+02:00 Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station Zeng, Z. Ding, M. 2023 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017544 eng eng info:eu-repo/semantics/altIdentifier/doi/10.57757/IUGG23-1999 https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017544 XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) info:eu-repo/semantics/conferenceObject 2023 ftgfzpotsdam https://doi.org/10.57757/IUGG23-1999 2023-05-28T23:39:14Z 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 trend, increasing from 1990 to 2004 and then decreasing after that. In addition to clouds and water vapor, poor weather conditions also significantly affect solar radiation at these stations. The high-precision, long-term DGSR dataset can provide a quantitative understanding of Earth's surface radiation balance and validate satellite data for the Antarctic region, advancing our knowledge of Antarctica's role in global climate change and the interactions between snow, ice, and the atmosphere. Conference Object Antarc* Antarctic Antarctica Ice Sheet Sea ice GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam) Antarctic Great Wall Station ENVELOPE(-58.970,-58.970,-62.217,-62.217) The Antarctic Zhongshan ENVELOPE(76.371,76.371,-69.373,-69.373) Zhongshan Station ENVELOPE(76.371,76.371,-69.373,-69.373)
institution Open Polar
collection GFZpublic (German Research Centre for Geosciences, Helmholtz-Zentrum Potsdam)
op_collection_id ftgfzpotsdam
language English
description 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 trend, increasing from 1990 to 2004 and then decreasing after that. In addition to clouds and water vapor, poor weather conditions also significantly affect solar radiation at these stations. The high-precision, long-term DGSR dataset can provide a quantitative understanding of Earth's surface radiation balance and validate satellite data for the Antarctic region, advancing our knowledge of Antarctica's role in global climate change and the interactions between snow, ice, and the atmosphere.
format Conference Object
author Zeng, Z.
Ding, M.
spellingShingle Zeng, Z.
Ding, M.
Estimation and changes of long-time global solar radiation at China’s Antarctic Zhongshan Station and Great Wall Station
author_facet Zeng, Z.
Ding, M.
author_sort Zeng, Z.
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
publishDate 2023
url 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
The Antarctic
Zhongshan
Zhongshan Station
geographic_facet Antarctic
Great Wall Station
The Antarctic
Zhongshan
Zhongshan Station
genre Antarc*
Antarctic
Antarctica
Ice Sheet
Sea ice
genre_facet Antarc*
Antarctic
Antarctica
Ice Sheet
Sea ice
op_source XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
op_relation info:eu-repo/semantics/altIdentifier/doi/10.57757/IUGG23-1999
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5017544
op_doi https://doi.org/10.57757/IUGG23-1999
_version_ 1768389803875762176