Published May 20, 2020 | Version 1.0
Dataset Open

Air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017.

  • 1. Ecole Polytechnique Federale de Lausanne, Switzerland
  • 2. Swiss Polar Institute, Switzerland

Contributors

Contact person:

Data manager:

Researcher:

  • 1. Ecole Polytechnique Federale de Lausanne, Switzerland
  • 2. Swiss Polar Institute, Switzerland

Description

Dataset abstract

This data set contains the air-flow distortion bias factors of the port and starboard anemometers of the Akademik Tryoshnikov estimated during the Antarctic Circumnavigation Expedition (ACE) legs 0-4 undertaken during the austral summer of 2016/2017. The data are provided over overlapping wind direction secotors of 5(10) degree width stepped by 1(2) degrees relative wind direction. These bias factors can be used to correct the observed wind speeds for air-flow distortion on a sample by sample basis. For details see Landwehr et al. (2019; DOI: https://doi.org/10.5194/amt-2019-366).

Dataset contents

  • flow_distortion_bias_sensor1.csv, data file, comma-separated values
  • flow_distortion_bias_sensor2.csv, data file, comma-separated values
  • data_file_header, metadata, text format
  • README.txt, metadata, text format

Dataset license

This dataset of air-flow distortion factors is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/

Notes

The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals. SL received funding from the Swiss Data Science Center project c17-02.

Files

data_file_header.txt

Files (44.2 kB)

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md5:acda398cc271d68b92996527dfe1bb57
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md5:2098204e1a6dcf87aa9daa7bc62d00ff
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md5:aa9114120f43cd9e95782bc825ba68d6
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md5:c619421e0693a442ebd17efc5d7bfacf
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Additional details

References

  • Landwehr, S., Thurnherr, I., Cassar, N., Gysel-Beer, M., and Schmale, J.: Using global reanalysis data to quantify and correct airflow distortion bias in shipborne wind speed measurements, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-366
  • Smith, Shawn R., Mark A. Bourassa, and Ryan J. Sharp. 'Establishing More Truth in True Winds'. Journal of Atmospheric and Oceanic Technology 16 (1999): 14
  • Python Software Foundation. Python Language Reference, version 3.7.3. Available at https://www.python.org