Articles | Volume 9, issue 5
https://doi.org/10.5194/amt-9-2253-2016
https://doi.org/10.5194/amt-9-2253-2016
Research article
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23 May 2016
Research article | Highlight paper |  | 23 May 2016

Retrieving atmospheric turbulence information from regular commercial aircraft using Mode-S and ADS-B

Jacek M. Kopeć, Kamil Kwiatkowski, Siebren de Haan, and Szymon P. Malinowski

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Cited articles

Cho, J. Y. N., Newell, R. E., Anderson, B. E., Barrick, J. D. W., and Thornhill, K. L.: Characterizations of tropospheric turbulence and stability layers from aircraft observations, J. Geophys. Res., 108, 8784, https://doi.org/10.1029/2002JD002820, 2003.
Cornman, L. B., Morse, C. S., and Cunning, G.: Real-time estimation of atmospheric turbulence severity from in-situ aircraft measurements, J. Aircraft, 32, 171–177, https://doi.org/10.2514/3.46697, 1995.
Drüe, C., Deimel, S., and Hoff, A.: A low-cost approach to derive upper-air wind measurements from ADS-B, 13th EMS Annual Meeting, Reading, UK, 9–13 September 2013, available at: http://presentations.copernicus.org/EMS2013-702_presentation.pdf (last access: 21 August 2015), 2013.
Frehlich, R. and Sharman, R.: Climatology of velocity and tempera-ture turbulence statistics determined from rawinsonde and ACARS/AMDAR data, J. Appl. Meteorol. Clim., 49, 1149–1169, https://doi.org/10.1175/2010JAMC2196.1, 2010.
Gill, P. G. and Buchanan, P.: An ensemble based turbulence forecasting system, Meteorol. Appl., 21, 12–19, https://doi.org/10.1002/met.1373, 2014.
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Short summary
This paper is presenting a feasibility study focused on methods of estimating the turbulence intensity based on a class of navigational messages routinely broadcast by the commercial aircraft (known as ADS-B and Mode-S). Using this kind of information could have potentially significant impact on aviation safety. Three methods have been investigated.