Europe’s Carbon Towers Put Two Flux Correction Methods to the Test

Across Europe, hundreds of tall towers rise above forests, peatlands, croplands and grasslands, quietly sniffing the air twenty times per second. These eddy-covariance stations are the backbone of global carbon monitoring, providing the ground truth against which satellites and climate models are judged. But the numbers they produce are never raw: before a single flux of carbon dioxide or water vapour can be trusted, the signal must be corrected for a subtle but persistent problem known as high-frequency attenuation. A new multi-site study, published in Atmospheric Measurement Techniques, has now put the two rival correction philosophies head to head across 38 stations of the Integrated Carbon Observation System (ICOS), and the verdict carries real consequences for the reliability of long-term ecosystem data.

The problem the researchers tackled is fundamentally physical. Eddy-covariance instruments measure the covariance between vertical wind speed and gas concentration at high frequency, typically 10 to 20 hertz, to capture the turbulent eddies that carry gases between the surface and the atmosphere. Yet no instrument is perfect. Limited sampling time, line averaging, the physical separation between the sonic anemometer and the gas analyser’s inlet, and the passage of air through tubes and filters all act like a low-pass filter, smoothing out the fastest fluctuations. Because small eddies contribute disproportionately to the total flux, this smoothing causes a systematic underestimation that can range from a few percent to tens of percent depending on the setup, the site and the weather. Correcting for it is one of the most stubborn technical challenges in micrometeorology.

Two experimental strategies dominate the field. The spectral approach computes the ratio of the attenuated gas concentration power spectrum to the unattenuated sonic temperature spectrum, deriving an empirical transfer function from which a correction factor follows. The co-spectral approach instead uses the co-spectrum of the gas flux itself relative to the sensible heat flux, folding every attenuation source, including sensor separation, into a single empirical characterisation. Each camp has its defenders: spectral methods, championed by widely used software such as EddyPro and embedded in the official ICOS processing pipeline, avoid the complications of time-lag and phase-shift estimation, while co-spectral methods are immune to high-frequency noise and need no separate sensor-separation term. Until now, no systematic, network-wide comparison of the two had ever been attempted.

Ariane Faurès of the University of Liege and her colleagues filled that gap using a full year of carbon dioxide and water vapour flux data from 38 ICOS Class 1 and 2 ecosystem stations, all equipped with an identical enclosed-path LI-7200 gas analyser and a Gill sonic anemometer. This standardisation was a scientific gift: because every site shares the same hardware, the same heated 0.73-metre sampling line, the same rain cap and inlet filter, and flow rates fixed between 10 and 16 litres per minute, differences between sites could be attributed to atmospheric conditions and ecosystem type rather than instrument quirks. The team classified stations into high-measurement-height sites, essentially forests, and low-measurement-height sites such as croplands, grasslands and non-forested peatlands, then computed cut-off frequencies and correction factors for both methods under carefully controlled wind speed, stability and humidity classes.

The first headline finding is reassuring: the standardised ICOS setup performs remarkably well. Cut-off frequencies for carbon dioxide generally exceeded 1 hertz and were strikingly consistent across the continent, with a mean of 2.1 hertz and a tight spread at a wind speed of 3 metres per second. Correction factors for carbon dioxide typically stayed below 1.2, meaning the fluxes needed boosting by less than 20 percent, and often by less than 10. For water vapour the picture was harsher: attenuation was stronger, with correction factors occasionally approaching 2 under humid, windy conditions, reflecting the well-known tendency of water molecules to adsorb onto and desorb from the surfaces of the sampling tube and filter in a manner that varies with relative humidity.

When the two correction methods were compared directly, the differences for carbon dioxide proved small. After the standard turbulence filtering that removes weakly turbulent periods, cumulative annual flux differences between the methods typically stayed below 2 percent, and at high forest towers they were often negligible. The dominant source of carbon dioxide attenuation turned out to be sensor separation, the spatial offset between the anemometer and the analyser inlet, which the spectral approach must add back through a theoretical formulation from Horst and Lenschow. Water vapour told a different story. Here the two methods diverged substantially, with cumulative flux discrepancies frequently reaching 5 to 10 percent, and the largest gaps occurring under stable atmospheric stratification, at low measurement heights, and under strong attenuation.

The reasons for this divergence are methodological as much as physical. Both approaches rest on the assumption of spectral similarity, the idea that gas and temperature fluctuations share the same spectral shape at low frequencies. The study found that this assumption holds well for carbon dioxide but breaks down for water vapour, particularly in humid air, where the gas spectra departed from the ideal reference far more strongly than the co-spectra did. On top of that, the spectral approach was repeatedly plagued by high-frequency noise, requiring a dedicated denoising procedure at 58 percent of sites for carbon dioxide and 84 percent for water vapour, while the theoretical sensor-separation term it depends on produced unrealistically large corrections under stable conditions. The co-spectral approach, by contrast, delivered stable, physically consistent results across all sites and conditions, leading the authors to recommend it for this specific experimental configuration.

Perhaps the most provocative result emerged when the team compared their independently computed corrections with the official fluxes produced by the ICOS Ecosystem Thematic Centre. Since the network pipeline also uses a spectral method, one might expect close agreement, but the opposite was true: differences between the study’s spectral corrections and the official products were often larger than the differences between the spectral and co-spectral approaches themselves. For water vapour, cumulative flux differences against the ICOS pipeline averaged 10.7 percent at low-measurement-height sites, with some stations showing gaps exceeding 20 percent, and even carbon dioxide showed average differences of 1.6 percent and station-level extremes above 10 percent. The causes are a cascade of small choices: different low-pass and anemometer correction equations, a different sensor-separation formulation, different filtering thresholds and fitting ranges, and a contested use of the transfer function when computing correction factors, a choice that earlier work suggests can bias fluxes by up to 10 percent.

These numbers matter far beyond the technical community. Eddy-covariance fluxes feed the global carbon budgets that inform climate policy, underpin assessments of whether forests and peatlands are net sinks or sources of greenhouse gases, and enter the long-running debate over the surface energy balance closure problem. A systematic 10 percent uncertainty in water vapour fluxes propagates directly into estimates of evapotranspiration and ecosystem water use, while even a few percent in carbon dioxide can shift the calculated carbon balance of a young forest or a drained peatland. The study also carries a practical design lesson: because attenuation grows as the measurement height approaches the canopy, mounting sensors as high as feasible, within footprint constraints, dramatically reduces the correction burden, and at many forest towers the carbon dioxide correction is now so small it could arguably be skipped altogether.

The authors have released their analysis as an open-source Python tool, FreqCor, designed to be configurable across setups and trace gases, and they argue that the high-frequency correction step deserves a broader reassessment within the ICOS processing pipeline. They are candid that a fully automated, network-scale procedure remains elusive: thresholds, fitting ranges and denoising decisions still involve user judgement, and future work should replace uniform flux thresholds with signal-to-noise criteria and validate denoising across many sites. The study’s scope is limited to enclosed-path analysers, and the authors note that closed-path systems with long tubes, common for methane and nitrous oxide measurements, could show even larger method differences and merit a similar network-wide test. For now, one thing is clear: the quiet correction applied inside every flux tower’s software is not a formality, and choosing the right way to do it can change what Europe’s ecosystems appear to breathe.

Subject of Research: Comparison of spectral and co-spectral high-frequency attenuation corrections for eddy-covariance flux measurements across the ICOS ecosystem network

Article Title: Spectral versus co-spectral correction of eddy-covariance fluxes: a multi-site assessment across the ICOS network

Article References: Faurès, A., Fratini, G., Nicolini, G., Papale, D., Sabbatini, S., & Heinesch, B. (2026). Spectral versus co-spectral correction of eddy-covariance fluxes: a multi-site assessment across the ICOS network. Atmospheric Measurement Techniques, 19(18), 6037-6074. https://doi.org/10.5194/amt-19-6037-2026

Image Credits: AI Generated

DOI: 10.5194/amt-19-6037-2026

Keywords: eddy covariance, ICOS, spectral correction, co-spectral correction, high-frequency attenuation, carbon dioxide flux, water vapour flux, gas analyser, sensor separation, micrometeorology, ecosystem monitoring, Atmospheric Measurement Techniques