A Bayesian model to correct underestimated 3-D wind speeds from sonic anemometers increases turbulent components of the surface energy balance

Frank, John M.; Massman, William J.; Ewers, Brent E.

doi:https://doi.org/10.5194/amt-9-5933-2016

Articles | Volume 9, issue 12

https://doi.org/10.5194/amt-9-5933-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/amt-9-5933-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 12

Research article

|

12 Dec 2016

Research article |

| 12 Dec 2016

A Bayesian model to correct underestimated 3-D wind speeds from sonic anemometers increases turbulent components of the surface energy balance

John M. Frank, William J. Massman, and Brent E. Ewers

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Final revised paper (published on 12 Dec 2016)
Supplement to the final revised paper
Preprint (discussion started on 23 Jun 2016)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Comment on "A Bayesian model to correct underestimated 3D wind speeds from sonic anemometers increases turbulent components of the surface energy balance"', Anonymous Referee #2, 18 Jul 2016
- AC2: 'Response to Referee #2', John Frank, 17 Nov 2016
RC2: 'A review of “A Bayesian model to correct underestimated 3D wind speeds from sonic anemometers increases turbulent components of the surface energy balance” by J. M. Frank et al.', Anonymous Referee #3, 26 Sep 2016
- AC1: 'Response to Referee #3', John Frank, 16 Nov 2016

Short summary

Ecosystem flux networks measure carbon dioxide and water vapor exchange and are integral to global studies of the biosphere and climate change. Yet recent evidence suggests a measurement error in sonic anemometry, the principal instrument for eddy-covariance research. A novel Bayesian analysis estimates the three-dimensional correction in these instruments and demonstrates that 60 % of the sites within the AmeriFlux network and numerous others globally underestimate all ecosystem fluxes by 8–12 %.