Using the Surface Renewal Technique to Estimate CO2 Exchange from a Rice Field to the Atmosphere

Abstract:

Measuring CO₂ emissions as surface fluxes is crucial for climate change predictions. One major set of techniques to measure surface fluxes is through continuous micrometeorological observations over different landscapes. Recent approaches of the surface renewal method (SR) are becoming important for their capacity to independently measure sensible (H) and latent heat (LE) fluxes while avoiding some of the shortcomings of the eddy covariance method (EC). Unlike EC, SR avoids orientation limitations, leveling requirements and instrumentation separation and shadowing issues. The main advantage of SR over EC method is in its applicability in both roughness and inertial sub-layers. Therefore, SR measurements can be planned in cases where fetch requirements are not adequate for EC application. We applied the recent approach as suggested by Castellvi et al. (2008) over two months (May to July, 2015) of high-frequency data collected by EC equipment from a rice field in Arkansas. The main goal was to extend this SR application to CO₂ fluxes (Fc) over agricultural fields. The results show high correlation between EC and SR fluxes (H, LE and Fc) when they are compared for all atmospheric stability conditions (R² > 0.75). Some overestimation is observed for SR with respect to EC fluxes, similar to the findings of Castellvi et al. (2008) for rangeland grass. For all the data, SR analysis results were about 11%, 18% and 17% higher than the EC results for H, LE and Fc, respectively. These higher flux estimates resulted in better energy balance closure. The root mean square error for Fc was 6.55 μmol m^-2 s^-1. The observed overestimation will be addressed in the future by using additional methods for the turbulent fluxes quantification.