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.
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 overl...
Main Authors: | , , |
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Format: | Dataset |
Language: | English |
Published: |
Zenodo
2020
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Subjects: | |
Online Access: | https://dx.doi.org/10.5281/zenodo.3836199 https://zenodo.org/record/3836199 |
Summary: | 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/ : 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. : {"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"]} |
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