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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-366
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-366
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 01 Oct 2019

Submitted as: research article | 01 Oct 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Using global reanalysis data to quantify and correct airflow distortion bias in shipborne wind speed measurements

Sebastian Landwehr1, Iris Thurnherr2, Nicolas Cassar3, Martin Gysel-Beer1, and Julia Schmale1 Sebastian Landwehr et al.
  • 1Paul Scherrer Institute, Laboratory of Atmospheric Chemistry, Villigen, Switzerland
  • 2ETH, Institute for Atmospheric and Climate Science, Zurich, Switzerland
  • 3Division of Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, USA

Abstract. At sea, wind forcing is responsible for the formation and development of surface waves and represents an important source of near surface turbulence. Therefore, processes related to near surface turbulence and wave breaking, such as sea spray emission and air-sea gas exchange are often parametrised with wind speed. Shipborne wind speed measurements thus provide highly relevant observations. They can, however, be compromised by flow distortion due to the ship's structure and objects nearby the anemometer that modify the airflow, leading to a deflection of the apparent wind direction and positive or negative acceleration of the apparent wind speed. The resulting errors in the estimated true wind speed can be greatly magnified at low wind speeds. For some research ships, correction factors have been derived from computational fluid dynamic models or through direct comparison with wind speed measurements from buoys. These correction factors can, however, loose their validity due to changes of the structures nearby the anemometer and thus require frequent re-evaluation, which is costly in either computational power or ship time. Here we evaluate if global weather forecast model data can be used to quantify the flow distortion bias in shipborne wind speed measurements. The method is tested on data from the Antarctic Circumnavigation Expedition (ACE) on board the R/V Akademik Tryoshnikov, which are compared with ERA-5 reanalysis wind speeds. We find that, depending on the relative wind direction, the relative wind speed and direction measurements are biased by −37 % to +20 % and −13° to +15°, respectively. The resulting error in the true wind speed is +11 % on average but ranges from −5 % to +40 % (5th and 95th percentile). After applying the bias correction, the uncertainty in the true wind speed is reduced to 5 % and depends mainly on the average accuracy of the ERA-5 data over the period of the experiment. The obvious drawback of this approach is the potential intrusion of model bias in the correction factors. We show that this problem can be somewhat mediated when the error propagation in the true wind correction is accounted for and used to weight the observations. We discuss the potential caveats and limitations of this approach and conclude that it can be used to quantify flow distortion bias for ships that operate on a global scale. The method can also be valuable to verify Computational Fluid Dynamic studies of airflow distortion on research vessels.

Sebastian Landwehr et al.
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Quality-checked meteorological data from the Southern Ocean collected during the Antarctic Circumnavigation Expedition from December 2016 to April 2017 S. Landwehr, J. Thomas, I. Gorodetskaya, I. Thurnherr, C. Robinson, and J. Schmale https://doi.org/10.5281/zenodo.3379590

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Short summary
Shipborne wind speed measurements are relevant for field studies of air-sea interaction processes. Distortion of the airflow by the ship's structure can, however, lead to errors of several 10 %. We estimate the flow distortion bias by comparing the observations to ERA-5 reanalysis data. The underlying assumptions are that the bias depends only on the relative orientation of the ship to the wind direction and that the ERA-5 wind speeds are (on average) representative of the true wind speed.
Shipborne wind speed measurements are relevant for field studies of air-sea interaction...
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