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Research article2023Peer reviewedOpen access

Two-level eddy covariance measurements reduce bias in land-atmosphere exchange estimates over a heterogeneous boreal forest landscape

Klosterhalfen, Anne; Chi, Jinshu; Kljun, Natascha; Lindroth, Anders; Laudon, Hjalmar; Nilsson, Mats B.; Peichl, Matthias


Estimates of land-atmosphere exchanges of carbon, energy, water vapor, and other greenhouse gases based on the eddy covariance (EC) technique rely on the fundamental assumption that the flux footprint area is homo-geneous. We investigated the impact of source area heterogeneity on flux estimates in single-level EC mea-surements over a managed boreal forest landscape. For this purpose, we compared single-level measurements with those from a two-level approach consisting of concurrent EC measurements at 60 and 85 m above the ground. This two-level set-up provided a unique opportunity to obtain nearly congruent diel footprint areas by combining data from the higher and lower levels during day-and nighttime, respectively.We found that the variation in the averaged footprint area between day-and nighttime was reduced by up to 89% in the two-level approach compared to the single-level data at the higher level (85 m). Considering spring, summer, and fall months, the resulting relative potential bias in flux observations due to landscape heterogeneity was highest at short time steps (= daily) ranging between 35% and 325% for half-hourly data. During winter months, when stable atmospheric regimes prevailed during day and night, the footprints within the diel course nearly overlapped also at a given single level and hence no improvement of flux estimates was found. The ab-solute cumulated sums for the study period (excluding winter months) of gross primary production, ecosystem respiration, latent heat, and sensible heat flux were underestimated by about 28%, 52%, 5%, and 3%, respec-tively, whereas that of net ecosystem CO2 exchange was overestimated by about 109% in the single-level approach. Overall this study suggests that footprint heterogeneity may introduce considerable bias in single -level flux estimates - particularly at short time scales - with large implications for model-data fusion studies, site comparisons, and up-or downscaling of land-atmosphere exchange processes.


Tall tower eddy covariance; Heterogeneous landscape; Net ecosystem CO 2 exchange; Sensible heat flux; Latent heat flux; Footprint model FFP

Published in

Agricultural and Forest Meteorology
2023, Volume: 339, article number: 109523
Publisher: ELSEVIER