Addressing eddy-covariance flux errors due to uncertainties in open path IRGA operation under harsh environmental conditions on the Tibetan Plateau

When using open path infrared gas analyzers (IRGA), lens contamination, calibration inaccuracies and ageing internal chemicals may lead to a slow drift in gas concentration measurements. During flux calculations, these errors are usually not accounted for under the assumption, that a slow drift in mean gas concentrations (i.e. over several weeks to months) does not affect the estimation of turbulent fluctuations and, hence, of covariances. This is however not the case. In fact, Serrano-Ortiz et al. (2008) estimated that an underestimation of the CO₂ concentration will propagate into an overestimation of the carbon uptake via the WPL correction. In addition, for instruments – such as the widely used LI-7500 – where a nonlinear calibration curve relates raw absorptance measurements to gas concentration, Fratini et al. (2014) have shown that errors in mean concentrations leak into errors in fluxes on account of amplified or dampened estimated fluctuations. Both these effects can be eliminated, possibly completely, when the drift in gas concentration is corrected before raw data processing. Therefore, the offset between measured and reference (i.e. "real") gas concentrations has to be quantified and converted into the corresponding zero absorption biases. We performed the drift correction on a 15 years dataset from the Tibetan Plateau, where an extreme drift in concentration measurements occurred. Due to the remote location, user calibrations were performed irregularly, and no independent gas concentration measurements are available. Hence, we used the CO₂ concentration measurements from the Mauna Loa atmospheric observatory (NOAA ESRL Global Monitoring Division, 2018, updated annually) as reference gas concentration to derive an offset for every half hour measurement. The offset in H­­₂O mixing ratios could be determined from auxiliary low frequency measurements of relative humidity, temperature and air pressure. We then converted mixing ratios to raw absorptances using the instrument-specific calibration curve to apply an absorptance offset to every 10 Hz measurement, thus eliminating the long-term drift in both mean values and fluctuations of gas concentrations. The corrected raw data time series were then used for calculation of fluxes and subsequent corrections, including de-spiking, axis rotation, detrending and correction for spectral attenuations and air density fluctuations. In comparison to the uncorrected fluxes, the corrected fluxes yielded a considerably lower carbon uptake during daytime and summer, which is in compliance with instrument theory of operation and the results from numerical simulations and field data analysis as conducted by Fratini et al. (2014).

 

Fratini, G., McDermitt, D.K. & Papale, D. (2014) Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction. Biogeosciences, 11, 1037–1051.

NOAA ESRL Global Monitoring Division (2018, updated annually) Atmospheric Carbon Dioxide Dry Air Mole Fractions from quasi-continuous measurements at Mauna Loa, Hawaii, Barrow, Alaska, American Samoa and South Pole. Compiled by K.W. Thoning, D.R. Kitzis, and A. Crotwell., 2019th edn. NOAA ESRL GMD CCGG Group, Boulder, Colorado, USA.

Serrano-Ortiz, P., Kowalski, A.S., Domingo, F., Ruiz, B. & Alados-Arboledas, L. (2008) Consequences of Uncertainties in CO2 Density for Estimating Net Ecosystem CO2 Exchange by Open-path Eddy Covariance. Boundary-Layer Meteorology, 126, 209–218.