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

This paper introduces a unique multiyear dataset and themonitoring capability of the PANDA automatic weather station network, whichincludes 11 automatic weather stations (AWSs) across the Prydz BayAmery IceShelfDome A area from the coast to the summit of the East Antarctic IceSheet. The ∼ 1460 km tr...

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Bibliographic Details
Published in:Earth System Science Data
Main Authors: Ding, M, Zou, X, Sun, Q, Yang, D, Zhang, W, Bian, L, Lu, C, Allison, I, Heil, P, Xiao, C
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus GmbH 2022
Subjects:
Earth Sciences
Climate change science
Climatology
Antarctic
East Antarctica
Austral
Zhongshan
Antarc*
Antarctica
Online Access:https://doi.org/10.5194/essd-14-5019-2022
http://ecite.utas.edu.au/154900
Description
Summary:This paper introduces a unique multiyear dataset and themonitoring capability of the PANDA automatic weather station network, whichincludes 11 automatic weather stations (AWSs) across the Prydz BayAmery IceShelfDome A area from the coast to the summit of the East Antarctic IceSheet. The ∼ 1460 km transect from Zhongshan to PandaSfollows roughly along ∼ 77 ∘ E longitude and coversall geographic units of East Antarctica. Initial inland observations, nearthe coast, started in the 1996/97 austral summer. All AWSs in this networkmeasure air temperature, relative humidity, air pressure, wind speed andwind direction at 1 h intervals, and some of them can also measure firntemperature and shortwave/longwave radiation. Data are relayed in nearreal time via the Argos system. The data quality is generally very reliable, andthe data have been used widely. In this paper, we firstly present a detailedoverview of the AWSs, including the sensor characteristics, installationprocedure, data quality control protocol and the basic analysis of eachvariable. We then give an example of a short-term atmospheric event thatshows the monitoring capacity of the PANDA AWS network. This dataset, whichis publicly available, is planned to be updated on a near-real-time basis andshould be valuable for climate change estimation, extreme weather eventsdiagnosis, data assimilation, weather forecasting, etc. The dataset isavailable at https://doi.org/10.11888/Atmos.tpdc.272721 (Dinget al., 2022b).

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