In this paper the accuracy of the wet-bulb and air temperature measurements of the DTS are verified, and the resulting Bowen ratio and heat fluxes are compared to eddy covariance data. The performance of BR-DTS was tested on a 46m high tower in a mixed forest in the centre of the Netherlands in August 2016. The average tree height is 26 to 30m, and the temperatures are measured below, in, and above the canopy. Using the vertical temperature profiles the storage of latent and sensible heat in the air column was calculated.
We found a significant effect of solar radiation on the temperature measurements, leading to a deviation of up to 3K. By installing screens, the error caused by sunlight is reduced to under 1K. Wind speed seems to have a minimal effect on the measured wet-bulb temperature, both below and above the canopy. After a simple quality control, the Bowen ratio measured by DTS correlates well with eddy covariance (EC) estimates (r2 = 0.59). The average energy balance closure between BR-DTS and EC is good, with a mean underestimation of 3.4Wm−2 by the BR-DTS method. However, during daytime the BR-DTS method overestimates the available energy, and during night-time the BR-DTS method estimates the available energy to be more negative. This difference could be related to the biomass heat storage, which is neglected in this study.
The BR-DTS method overestimates the latent heat flux on average by 18.7Wm−2, with RMSE = 90Wm−2. The sensible heat flux is underestimated on average by 10.6Wm−2, with RMSE = 76Wm−2. Estimates of the BR-DTS can be improved once the uncertainties in the energy balance are reduced. However, applying, for example, Monin–Obukhov similarity theory could provide independent estimates for the sensible heat flux. This would make the determination of the highly uncertain and difficult to determine net available energy redundant.
FingerprintDive into the research topics of 'Technical note: Using distributed temperature sensing for Bowen ratio evaporation measurements'. Together they form a unique fingerprint.
Schilperoort, B. (Creator), Cisneros Vaca, C. (Creator), Jiménez Rodríguez, C. (Creator), Coenders-Gerrits, M. (Contributor), Ucer, M. (Contributor) & van der Tol, C. (Contributor), Delft University of Technology, 2017