Preprints
https://doi.org/10.5194/essd-2022-241
https://doi.org/10.5194/essd-2022-241
 
11 Aug 2022
11 Aug 2022

The AntAWS dataset: a compilation of Antarctic automatic weather station observations

Yetang Wang1,, Xueying Zhang1,, Wentao Ning1, Matthew A. Lazzara2, Minghu Ding3, Carleen H. Reijmer4, Paul C. J. P. Smeets4, Paolo Grigioni5, Elizabeth R. Thomas6, Zhaosheng Zhai1, Yuqi Sun1, and Shugui Hou7 Yetang Wang et al.
  • 1College of Geography and Environment, Shandong Normal University, Jinan 250014, China
  • 2Antarctic Meteorological Research Center, Space Science and Engineering Center, University of Wisconsin—Madison, Madison, Wisconsin
  • 3State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • 4Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, Netherland
  • 5Laboratory for Measurements and Observations for Environment and Climate, ENEA, 00123 Rome, Italy
  • 6British Antarctic Survey, Cambridge, UK
  • 7School of Oceanography, Shanghai Jiao Tong University, Shanghai, 200240, China
  • These authors contributed equally to this work.

Abstract. A new dataset of meteorological records from Antarctic automatic weather stations (here called AntAWS dataset) at 3-hourly, daily and monthly resolutions is constructed with quality control. This dataset compiles the measurements of air temperature, air pressure, relative humidity, and wind speed and direction from 216 AWSs available during 1980–2021. Their spatial distribution remains heterogeneous, with a majority of instrumented sites located on the coastal areas, and less at the inland East Antarctic Plateau. Among the 216 AWSs, 55 of them have the records spanning more than 20 years, and 25 of them spanning more than 30 years. Among the five meteorological parameters, the air temperature measurement data have the best continuity and the highest data integrity. The comprehensive compilation of AWS observations has the main aim to make them easy and time-saving to be used for local, regional and continental studies, which can be accessed at https://doi.org/10.48567/key7-ch19 (Wang et al., 2022). This dataset will be valuable for better characterizing surface climatology throughout the continent of Antarctica, improving our understanding of Antarctic surface snow-atmosphere interactions, and estimating regional climate models or meteorological reanalysis products.

Journal article(s) based on this preprint

Yetang Wang et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on essd-2022-241', Ian Allison, 19 Aug 2022
    • AC6: 'Reply on CC1', Yetang Wang, 04 Nov 2022
  • RC1: 'Comment on essd-2022-241', Chang-Qing Ke, 30 Aug 2022
    • AC2: 'Reply on RC1', Yetang Wang, 04 Nov 2022
  • CC2: 'Comment on essd-2022-241', Christophe Genthon, 13 Sep 2022
    • AC3: 'Reply on CC2', Yetang Wang, 04 Nov 2022
  • CC3: 'Comment on essd-2022-241', Ting Wei, 21 Sep 2022
    • AC1: 'Reply on CC3', Yetang Wang, 04 Nov 2022
  • RC2: 'Comment on essd-2022-241', Christoph Kittel, 03 Oct 2022
    • RC3: 'Aditionnal comments', Christoph Kittel, 04 Oct 2022
      • AC5: 'Reply on RC3', Yetang Wang, 04 Nov 2022
    • AC4: 'Reply on RC2', Yetang Wang, 04 Nov 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Yetang Wang on behalf of the Authors (01 Dec 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (02 Dec 2022) by David Carlson
RR by Anonymous Referee #1 (11 Dec 2022)
ED: Publish subject to technical corrections (29 Dec 2022) by David Carlson
AR by Yetang Wang on behalf of the Authors (06 Jan 2023)  Author's response    Manuscript

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on essd-2022-241', Ian Allison, 19 Aug 2022
    • AC6: 'Reply on CC1', Yetang Wang, 04 Nov 2022
  • RC1: 'Comment on essd-2022-241', Chang-Qing Ke, 30 Aug 2022
    • AC2: 'Reply on RC1', Yetang Wang, 04 Nov 2022
  • CC2: 'Comment on essd-2022-241', Christophe Genthon, 13 Sep 2022
    • AC3: 'Reply on CC2', Yetang Wang, 04 Nov 2022
  • CC3: 'Comment on essd-2022-241', Ting Wei, 21 Sep 2022
    • AC1: 'Reply on CC3', Yetang Wang, 04 Nov 2022
  • RC2: 'Comment on essd-2022-241', Christoph Kittel, 03 Oct 2022
    • RC3: 'Aditionnal comments', Christoph Kittel, 04 Oct 2022
      • AC5: 'Reply on RC3', Yetang Wang, 04 Nov 2022
    • AC4: 'Reply on RC2', Yetang Wang, 04 Nov 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Yetang Wang on behalf of the Authors (01 Dec 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (02 Dec 2022) by David Carlson
RR by Anonymous Referee #1 (11 Dec 2022)
ED: Publish subject to technical corrections (29 Dec 2022) by David Carlson
AR by Yetang Wang on behalf of the Authors (06 Jan 2023)  Author's response    Manuscript

Journal article(s) based on this preprint

Yetang Wang et al.

Data sets

AntAWS Dataset: A compilation of Antarctic automatic weather station observations. Wang, Y., Zhang, X., Ning, W., Lazzara, M. A., Ding, M., Reijmer C., Smeets P., Grigioni, P., Thomas, E. R., Zhai Z., Sun Y., and Hou, S. https://amrdcdata.ssec.wisc.edu/dataset/antaws-dataset

Yetang Wang et al.

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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Short summary
Here we construct a new database of Antarctic automatic weather (AWS) station meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.