Evaluation of a plot scale methane emission model at the ecosystem scale using eddy covariance observations and footprint modelling

Abstract

Abstract. Most plot-scale methane emission models – of which many have been developed in the recent past – are validated using data collected with the closed-chamber technique. This method, however, suffers from a low spatial representativeness and a poor temporal resolution. Also, during a chamber-flux measurement the air within a chamber is separated from the ambient atmosphere, which negates the influence of wind on emissions. Additionally, some methane models are validated by upscaling fluxes based on the area-weighted averages of closed-chamber measurements, and by comparing those to the eddy covariance (EC) flux. This technique is rather inaccurate, as the area of upscaling might be different from the EC tower footprint, therefore introducing significant mismatch. In this study, we present an approach to validate plot-scale methane models with EC observations using the footprint-weighted average method. Our results show that the fluxes obtained by the footprint-weighted average method are of the same magnitude as the EC flux. More importantly, the temporal dynamics of the EC flux on a daily time scale are also captured (r2 = 0.7). In contrast, using the area-weighted average method yielded a low (r2 = 0.14) correlation with the EC measurements and an underestimation of methane emissions by 27.4%. This shows that the footprint-weighted average method is preferable when validating methane emission models with EC fluxes for areas with a heterogeneous and irregular vegetation pattern.

Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling

“…The results of this study support the importance of footprint modelling in heterogeneous environments, as found in earlier studies (Budishchev et al 2014, Tuovinen et al 2018. In previous work, Wang et al (2016) used a threshold for δ of 10%, i.e.…”

“…In a sub-Arctic mire site in Finland, the Kormann and Meixner (2001) footprint model was applied to get half-hourly footprint-weighted spatial indices, these were used as in-put for a process-based model and improved the correlation between growing season upscaled chamber CH 4 fluxes and EC flux estimates, with an increase in r 2 from 0.41 to 0.72 (Hartley et al 2015). Budishchev et al (2014) also used a footprint model to upscale the chamber measurements to the EC scale, improving the r 2 correlation coefficient from 0.14 to 0.7, in a Russian polygonal tundra. Davidson et al (2017) show a 20%-30% improvement and an r 2 of 0.88, across several tundra sites in Alaska by using footprint modelling to upscale chamber measurements to the EC tower fluxes.…”

East Siberian Arctic inland waters emit mostly contemporary carbon

“…U 10 values were available from the eddy covariance site at 30 min intervals 49 . Pond k 600 values were taken from ref.…”

“…The eddy covariance tower at the study site ( Fig. 1) was installed in 2003 to measure net ecosystem exchange, using an ultrasonic anemometer (Gill Instruments, Lymington, UK, type R3-50) for wind speed and temperature, and water vapor and CO 2 concentrations were measured by an openpath infra-red gas analyzer (LI-COR LI-7500, Lincoln, NE, USA) 49 . An open-path infra-red gas analyzer (LI-COR LI-7700) has been used to measure atmospheric CH 4 concentrations since 2014.…”

“…An open-path infra-red gas analyzer (LI-COR LI-7700) has been used to measure atmospheric CH 4 concentrations since 2014. All sensors measure at 10 Hz and are installed at a height of 4.7 m. Energy balance closure and good co-spectral shapes required for validation of the eddy covariance methods were demonstrated at the site previously 44,49 .…”