the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Apr 2025
IMAU Antarctic automatic weather station data, including surface radiation balance (1995–2022)
Abstract. In cooperation with multiple institutes, the Institute for Marine and Atmospheric research Utrecht (IMAU) at Utrecht University has operated automated weather stations (AWS) at 19 locations on the Antarctic ice sheet from 1995 through 2022. Besides standard meteorological measurements (pressure, temperature, humidity, wind speed & direction), these stations include measured shortwave and longwave radiation components and surface height, thereby allowing for the reliable in situ quantification of the surface energy balance (SEB) and surface mass balance (SMB) at (two-)hourly temporal resolution. This unique dataset can be used for climate model evaluation and development, for the validation of remote sensing products, for the quantification of long term climatological changes, for the interpretation of ice cores, and for process understanding in general. This paper describes the dataset and the applied measurement corrections. The total dataset contains 154 station-years of data, of which 65 % include both SEB & SMB observations, and is available at https://doi.pangaea.de/10.1594/PANGAEA.974080 (Van Tiggelen et al, 2024).
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Status: final response (author comments only)
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RC1: 'Comment on essd-2025-88', Ian Allison, 07 May 2025
This preprint provides an excellent description of more than 20 years of high quality and valuable Antarctic surface meteorological data from the IMAU automatic weather station (AWS) network. These AWS were designed to enable estimation of the ice sheet surface energy and mass balances. The publication clearly outlines what variables were measured, what instrumentation was used, how the data were processed and how corrections were made. Clear links are given to how the data can be accessed and to the software codes used to pre-process and correct the measurements. I particularly liked the simple flag assigned to each data sample alerting of potential problems in each of the measured variables.
The IMAU Antarctic AWS network is one of several that provide Antarctic surface meteorological data. Others include those of the University of Wisconsin, the Australian Antarctic Division and the Chinese Antarctic Programme. These are mentioned and acknowledged in the preprint. But I think that the larger Antarctic AWS data set can be more directly referenced with a few small changes that do not length the manuscript (the focus of which clearly should be the IMAU network). I will suggest ways to do this, plus other small specific and technical comments in my more detailed reviewer comments.
This manuscript clearly fits the objectives and standards of ESSD and should be published.
Citation: https://doi.org/10.5194/essd-2025-88-RC1 -
RC2: 'Comment on essd-2025-88', Anonymous Referee #2, 13 May 2025
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2025-88/essd-2025-88-RC2-supplement.pdf
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RC3: 'Comment on essd-2025-88', David Bromwich, 20 May 2025
General Comments:
This manuscript is a welcome addition that describes an important set of surface observations from automatic weather stations (AWS) across the data sparse Antarctic continent. The authors provide a comprehensive description of their extensive quality controls. Such care is needed with observations from AWS in remote locations that often experience data collection challenges (e.g., Lazzara et al. 2012). The radiation fluxes are a valuable addition to those provided by the four BSRN stations in Antarctica. One could assume from the manuscript text that the IMAU Antarctic AWS program is mostly concluded. If so, this manuscript is an especially landmark effort.
Mostly my comments are centered around the context issue. The system requires me to rate this as major revisions, but it is more like minor with a few more important aspects.
- Are any of these observations part of the AntAWS database? I presume not from Figure 1, but it is important to make this very clear. And this encourages the merging of these two data streams.
- Were any of these observations made available to the GTS in near-realtime? If not, then the value of the observations increases because the reanalyses would not assimilate them, making the IMAU observations an independent test of the reanalyses.
- This manuscript really underplays the AWS program run by the University of Wisconsin-Madison that forms the backbone of the current Antarctic AWS network, e.g., Lazzara et al. (2012). Please rectify.
- An important monthly data set of near-surface air temperature from AWS in eastern Queen Maud Land is Kurita et al. (2024, DOI: 10.1175/JTECH-D-23-0092.1). Please integrate into your manuscript.
- I am particularly interested in the Kohnen site, AWS09, as a long-term observing site. Medley et al. (2017, https://doi.org/10.1002/2017GL075992) report 1.1C/decade warming at the Kohnen AWS, 1998-2016. I have doubts about this record because of the change in the temperature sensor in 2008 (mentioned here in Table 2) and the warming trend after this was much lower (Fig. S11). Here is the key passage from that manuscript: “Due to the low temperatures encountered at the site, some of the sensors operated outside their operational specifications. For this reason, the station was equipped with different temperature sensor in 2008.” (from Section 2.2). Downloading the Kohnen 2-m corrected temperatures from Pangaea reveals almost completely missing air temperatures after 2010 whereas the uncorrected temperatures are present. Please discuss this situation in your manuscript.
- David Bromwich May 20, 2025
Citation: https://doi.org/10.5194/essd-2025-88-RC3
Data sets
IMAU Antarctic automatic weather station data, including surface radiation balance (1995-2022) Maurice van Tiggelen et al. https://doi.pangaea.de/10.1594/PANGAEA.974080
Model code and software
MATLAB scripts used to process the IMAU Antarctic automatic weather station data, including surface radiation balance (1995-2022) Maurice van Tiggelen et al. https://doi.org/10.5281/zenodo.15101447
IMAU-IceEddie: Python scripts used to process the IMAU Antarctic automatic weather station data, including surface radiation balance (1995-2022) Maurice van Tiggelen et al. https://doi.org/10.5281/zenodo.15058515
IMAU-pyEBM: Python energy balance model for snow and ice Maurice van Tiggelen et al. https://doi.org/10.5281/zenodo.15082294
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