An assessment of the precision and confidence of aquatic eddy correlation measurements
Donis, D.; Holtappels, M.; Noss, C.; Cathalot, C.; Hancke, K.; Polsenaere, P.; Wenzhöfer, F.; Lorke, A.; Meysman, F.; Glud, R.N.; McGinnis, D.F. (2015). An assessment of the precision and confidence of aquatic eddy correlation measurements. J. Atmos. Oceanic. Technol. 32(3): 642–655. dx.doi.org/10.1175/JTECH-D-14-00089.1
In: Journal of Atmospheric and Oceanic Technology. American Meteorological Society: Boston, MA. ISSN 0739-0572; e-ISSN 1520-0426
|   |
| Keyword |
|
| Author keywords |
Turbulence, Boundary layer, Fluxes, Instrumentation/sensors, Optimization, Experimental design |
| Authors | | Top |
- Donis, D.
- Holtappels, M.
- Noss, C.
- Cathalot, C.
|
- Hancke, K.
- Polsenaere, P.
- Wenzhöfer, F.
- Lorke, A.
|
- Meysman, F.
- Glud, R.N.
- McGinnis, D.F.
|
| Abstract |
The quantification of benthic fluxes with the aquatic eddy correlation (EC) technique is based on simultaneous measurement of the current velocity and a targeted bottom water parameter (e. g., O-2, temperature). High-frequency measurements (64Hz) are performed at a single point above the seafloor using an acoustic Doppler velocimeter (ADV) and a fast-responding sensor. The advantages of aquatic EC technique are that 1) it is noninvasive, 2) it integrates fluxes over a large area, and 3) it accounts for in situ hydrodynamics. The aquatic EC has gained acceptance as a powerful technique; however, an accurate assessment of the errors introduced by the spatial alignment of velocity and water constituent measurements and by their different response times is still needed. Here, this paper discusses uncertainties and biases in the data treatment based on oxygen EC flux measurements in a large-scale flume facility with well-constrained hydrodynamics. These observations are used to review data processing procedures and to recommend improved deployment methods, thus improving the precision, reliability, and confidence of EC measurements. Specifically, this study demonstrates that 1) the alignment of the time series based on maximum cross correlation improved the precision of EC flux estimations; 2) an oxygen sensor with a response time of <0.4 s facilitates accurate EC fluxes estimates in turbulence regimes corresponding to horizontal velocities <11 cm s(-1); and 3) the smallest possible distance (<1 cm) between the oxygen sensor and the ADV's sampling volume is important for accurate EC flux estimates, especially when the flow direction is perpendicular to the sensor's orientation. |
|
