The PANDA automatic weather station network between the coast and Dome A, East Antarctica

This paper introduces a unique multiyear dataset and the monitoring capability of the PANDA automatic weather station network which includes eleven automatic weather stations (AWS) across Prydz Bay-Amery Ice Shelf-dome area from the coast to the summit of the East Antarctica ice sheet. The ~1460 km...

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Main Authors: Ding, Minghu, Zou, Xiaowei, Sun, Qizhen, Yang, Diyi, Zhang, Wenqian, Bian, Lingen, Lu, Changgui, Allison, Ian, Heil, Petra, Xiao, Cunde
Format: Text
Language:English
Published: 2022
Subjects:
Online Access:https://doi.org/10.5194/essd-2022-188
https://essd.copernicus.org/preprints/essd-2022-188/
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spelling ftcopernicus:oai:publications.copernicus.org:essdd104030 2023-05-15T13:22:09+02:00 The PANDA automatic weather station network between the coast and Dome A, East Antarctica Ding, Minghu Zou, Xiaowei Sun, Qizhen Yang, Diyi Zhang, Wenqian Bian, Lingen Lu, Changgui Allison, Ian Heil, Petra Xiao, Cunde 2022-07-19 application/pdf https://doi.org/10.5194/essd-2022-188 https://essd.copernicus.org/preprints/essd-2022-188/ eng eng doi:10.5194/essd-2022-188 https://essd.copernicus.org/preprints/essd-2022-188/ eISSN: 1866-3516 Text 2022 ftcopernicus https://doi.org/10.5194/essd-2022-188 2022-07-25T16:22:42Z This paper introduces a unique multiyear dataset and the monitoring capability of the PANDA automatic weather station network which includes eleven automatic weather stations (AWS) across Prydz Bay-Amery Ice Shelf-dome area from the coast to the summit of the East Antarctica ice sheet. The ~1460 km transect from Zhongshan to Panda S station follows roughly along ~77° E longitude and covers all geographic and climatic units of East Antarctica. Initial inland observation, near the coast, started in the 1996/1997 austral summer. All AWSs in this network measure air temperature, relative humidity, air pressure, wind speed and wind direction at 1-hour intervals, and some of them can also measure firn temperature and shortwave/longwave radiation. Data are relayed in near real-time via the ARGOS system. Data quality is generally very reliable and the data have been used widely. In this paper, we firstly present a detailed overview of the AWSs, including the sensor characteristics, installation procedure, data quality control protocol, and the basic analysis of each variable. We then give an example of a short-term atmospheric event that shows the monitoring capacity of the network. This dataset, which is publicly available, is planned to be updated on a near-real time and should be valuable for climate change estimation, extreme weather events diagnosis, data assimilation, weather forecasting, etc. The dataset is available at https://doi.org/10.11888/Atmos.tpdc.272721 (Ding et al., 2022). Text Amery Ice Shelf Antarc* Antarctica East Antarctica Ice Sheet Ice Shelf Prydz Bay Copernicus Publications: E-Journals Amery ENVELOPE(-94.063,-94.063,56.565,56.565) Amery Ice Shelf ENVELOPE(71.000,71.000,-69.750,-69.750) Austral East Antarctica Prydz Bay Zhongshan ENVELOPE(76.371,76.371,-69.373,-69.373)
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description This paper introduces a unique multiyear dataset and the monitoring capability of the PANDA automatic weather station network which includes eleven automatic weather stations (AWS) across Prydz Bay-Amery Ice Shelf-dome area from the coast to the summit of the East Antarctica ice sheet. The ~1460 km transect from Zhongshan to Panda S station follows roughly along ~77° E longitude and covers all geographic and climatic units of East Antarctica. Initial inland observation, near the coast, started in the 1996/1997 austral summer. All AWSs in this network measure air temperature, relative humidity, air pressure, wind speed and wind direction at 1-hour intervals, and some of them can also measure firn temperature and shortwave/longwave radiation. Data are relayed in near real-time via the ARGOS system. Data quality is generally very reliable and the data have been used widely. In this paper, we firstly present a detailed overview of the AWSs, including the sensor characteristics, installation procedure, data quality control protocol, and the basic analysis of each variable. We then give an example of a short-term atmospheric event that shows the monitoring capacity of the network. This dataset, which is publicly available, is planned to be updated on a near-real time and should be valuable for climate change estimation, extreme weather events diagnosis, data assimilation, weather forecasting, etc. The dataset is available at https://doi.org/10.11888/Atmos.tpdc.272721 (Ding et al., 2022).
format Text
author Ding, Minghu
Zou, Xiaowei
Sun, Qizhen
Yang, Diyi
Zhang, Wenqian
Bian, Lingen
Lu, Changgui
Allison, Ian
Heil, Petra
Xiao, Cunde
spellingShingle Ding, Minghu
Zou, Xiaowei
Sun, Qizhen
Yang, Diyi
Zhang, Wenqian
Bian, Lingen
Lu, Changgui
Allison, Ian
Heil, Petra
Xiao, Cunde
The PANDA automatic weather station network between the coast and Dome A, East Antarctica
author_facet Ding, Minghu
Zou, Xiaowei
Sun, Qizhen
Yang, Diyi
Zhang, Wenqian
Bian, Lingen
Lu, Changgui
Allison, Ian
Heil, Petra
Xiao, Cunde
author_sort Ding, Minghu
title The PANDA automatic weather station network between the coast and Dome A, East Antarctica
title_short The PANDA automatic weather station network between the coast and Dome A, East Antarctica
title_full The PANDA automatic weather station network between the coast and Dome A, East Antarctica
title_fullStr The PANDA automatic weather station network between the coast and Dome A, East Antarctica
title_full_unstemmed The PANDA automatic weather station network between the coast and Dome A, East Antarctica
title_sort panda automatic weather station network between the coast and dome a, east antarctica
publishDate 2022
url https://doi.org/10.5194/essd-2022-188
https://essd.copernicus.org/preprints/essd-2022-188/
long_lat ENVELOPE(-94.063,-94.063,56.565,56.565)
ENVELOPE(71.000,71.000,-69.750,-69.750)
ENVELOPE(76.371,76.371,-69.373,-69.373)
geographic Amery
Amery Ice Shelf
Austral
East Antarctica
Prydz Bay
Zhongshan
geographic_facet Amery
Amery Ice Shelf
Austral
East Antarctica
Prydz Bay
Zhongshan
genre Amery Ice Shelf
Antarc*
Antarctica
East Antarctica
Ice Sheet
Ice Shelf
Prydz Bay
genre_facet Amery Ice Shelf
Antarc*
Antarctica
East Antarctica
Ice Sheet
Ice Shelf
Prydz Bay
op_source eISSN: 1866-3516
op_relation doi:10.5194/essd-2022-188
https://essd.copernicus.org/preprints/essd-2022-188/
op_doi https://doi.org/10.5194/essd-2022-188
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