Quality Control of CarboEurope Flux Data - Part I: Coupling Footprint Analyses with Flux Data Quality Assessment to Evaluate Sites in Forest Ecosystems

We applied a site evaluation approach combining Lagrangian Stochastic footprint modelling with a quality assessment approach for eddy-covariance data to 25 forested sites of the CarboEurope-IP network. The analysis addresses the spatial representativeness 5 of the flux measurements, instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method. Our findings demonstrate that application of a footprint filter could strengthen the CarboEurope-IP flux database, since only one third of the sites is situated in truly homogeneous terrain. Almost half of the sites experience a significant reduction in eddy-covariance data 10 quality under certain conditions, though these effects are mostly constricted to a small portion of the dataset. Reductions in data quality of the sensible heat flux are mostly induced by characteristics of the surrounding terrain, while the latent heat flux is subject to instrumentation-related problems. The Planar-Fit coordinate rotation proved to be a reliable tool for the majority of the sites using only a single set of rotation angles. 15 Overall, we found a high average data quality for the CarboEurope-IP network, with good representativeness of the measurement data for the specified target land cover types.JRC.H.2-Air and Climat

Does increased spatial replication above heterogeneous agroforestry improve the representativeness of eddy covariance measurements?

Spatial heterogeneity in terrestrial ecosystems compromises the accuracy of eddy covariance measurements. Examples of heterogeneous ecosystems are temperate agroforestry systems, which have been poorly studied by eddy covariance. Agroforestry systems have been getting increasing attention due to their potential environmental benefits, e.g. a higher carbon sequestration, improved microclimate and erosion reduction compared to open-cropland agricultural systems. Lower-cost eddy covariance setups might offer an opportunity to better capture spatial heterogeneity by allowing for more spatial replicates of flux towers. The aim of this study was to quantify the spatial variability of carbon dioxide (FC), latent heat (LE) and sensible heat (H) fluxes above a heterogeneous agroforestry system in northern Germany using a distributed network of three lower-cost eddy covariance setups across the agroforestry system. Fluxes from the three towers in the agroforestry were further compared to fluxes from an adjacent open-cropland site. The campaign took place from March 2023 until September 2024. The results indicated that the spatial variability of fluxes was largest for FC, attributed to the effect of different crops (rapeseed, corn and barley) within the flux footprints contributing to the measured fluxes. Differences between fluxes across towers were enhanced after harvest events. However, the temporal variability due to the seasonality and diurnal cycles during the campaign was larger than the spatial variability across the three towers. When comparing fluxes between the agroforestry and the open-cropland systems, weekly sums of carbon and evapotranspiration fluxes followed similar seasonality, with peak values of −50 g C m−2 week−1 and 40 mm week−1 during the growing season, respectively. The variation of the magnitude depended on the phenology of the different crops. The effect size, which is an indicator of the representativeness of the fluxes across the distributed network of three eddy covariance towers compared to only one, showed, in conjunction with the other results, that the spatial heterogeneity across the agroforestry was better captured by the network of three stations. This supports previous findings that spatial heterogeneity should be taken into account in eddy covariance studies and that lower-cost setups may offer the opportunity to bridge this gap and improve the accuracy of eddy covariance measurements above heterogeneous ecosystems.</p

Quality control of CarboEurope flux data – Part I: Footprint analyses to evaluate sites in forest ecosystems

International audienceWe applied a site evaluation approach combining Lagrangian Stochastic footprint modelling with a quality assessment approach for eddy-covariance data to 25 forested sites of the CarboEurope-IP network. The analysis addresses the spatial representativeness of the flux measurements, instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method. Our findings demonstrate that application of a footprint filter could strengthen the CarboEurope-IP flux database, since only one third of the sites is situated in truly homogeneous terrain. Almost half of the sites experience a significant reduction in eddy-covariance data quality under certain conditions, though these effects are mostly constricted to a small portion of the dataset. Reductions in data quality of the sensible heat flux are mostly induced by characteristics of the surrounding terrain, while the latent heat flux is subject to instrumentation-related problems. The Planar-Fit coordinate rotation proved to be a reliable tool for the majority of the sites using only a single set of rotation angles. Overall, we found a high average data quality for the CarboEurope-IP network, with good representativeness of the measurement data for the specified target land cover types

Interpreting canopy development and physiology using a European phenology camera network at flux sites

Plant phenological development is orchestrated through subtle changes in photoperiod, temperature, soil moisture and nutrient availability. Presently, the exact timing of plant development stages and their response to climate and management practices are crudely represented in land surface models. As visual observations of phenology are laborious, there is a need to supplement long-term observations with automated techniques such as those provided by digital repeat photography at high temporal and spatial resolution. We present the first synthesis from a growing observational network of digital cameras installed on towers across Europe above deciduous and evergreen forests, grasslands and croplands, where vegetation and atmosphere CO2 fluxes are measured continuously. Using colour indices from digital images and using piecewise regression analysis of time series, we explored whether key changes in canopy phenology could be detected automatically across different land use types in the network. The piecewise regression approach could capture the start and end of the growing season, in addition to identifying striking changes in colour signals caused by flowering and management practices such as mowing. Exploring the dates of green-up and senescence of deciduous forests extracted by the piecewise regression approach against dates estimated from visual observations, we found that these phenological events could be detected adequately (RMSE< 8 and 11 days for leaf out and leaf fall, respectively). We also investigated whether the seasonal patterns of red, green and blue colour fractions derived from digital images could be modelled mechanistically using the PROSAIL model parameterised with information of seasonal changes in canopy leaf area and leaf chlorophyll and carotenoid concentrations. From a model sensitivity analysis we found that variations in colour fractions, and in particular the late spring green hump observed repeatedly in deciduous broadleaf canopies across the network, are essentially dominated by changes in the respective pigment concentrations. Using the model we were able to explain why this spring maximum in green signal is often observed out of phase with the maximum period of canopy photosynthesis in ecosystems across Europe. Coupling such quasi-continuous digital records of canopy colours with co-located CO2 flux measurements will improve our understanding of how changes in growing season length are likely to shape the capacity of European ecosystems to sequester CO2 in the future

Atmospheric deposition, CO2, and change in the land carbon sink

Concentrations of atmospheric carbon dioxide (CO2) have continued to increase whereas atmospheric deposition of sulphur and nitrogen has declined in Europe and the USA during recent decades. Using time series of flux observations from 23 forests distributed throughout Europe and the USA, and generalised mixed models, we found that forest-level net ecosystem production and gross primary production have increased by 1% annually from 1995 to 2011. Statistical models indicated that increasing atmospheric CO2 was the most important factor driving the increasing strength of carbon sinks in these forests. We also found that the reduction of sulphur deposition in Europe and the USA lead to higher recovery in ecosystem respiration than in gross primary production, thus limiting the increase of carbon sequestration. By contrast, trends in climate and nitrogen deposition did not significantly contribute to changing carbon fluxes during the studied period. Our findings support the hypothesis of a general CO2-fertilization effect on vegetation growth and suggest that, so far unknown, sulphur deposition plays a significant role in the carbon balance of forests in industrialized regions. Our results show the need to include the effects of changing atmospheric composition, beyond CO2, to assess future dynamics of carbon-climate feedbacks not currently considered in earth system/climate modelling.Peer reviewe

Validation of 3D-CMCC Forest Ecosystem Model (v.5.1) against eddy covariance data for 10 European forest sites

This study evaluates the performances of the new version (v.5.1) of 3D-CMCC Forest Ecosystem Model (FEM) in simulating gross primary productivity (GPP), against eddy covariance GPP data for 10 FLUXNET forest sites across Europe. A new carbon allocation module, coupled with new both phenological and autotrophic respiration schemes, was implemented in this new daily version. Model ability in reproducing timing and magnitude of daily and monthly GPP fluctuations is validated at intra-annual and inter-annual scale, including extreme anomalous seasons. With the purpose to test the 3D-CMCC FEM applicability over Europe without a site-related calibration, the model has been deliberately parametrized with a single set of species-specific parametrizations for each forest ecosystem. The model consistently reproduces both in timing and in magnitude daily and monthly GPP variability across all sites, with the exception of the two Mediterranean sites. We find that 3D-CMCC FEM tends to better simulate the timing of inter-annual anomalies than their magnitude within measurements' uncertainty. In six of eight sites where data are available, the model well reproduces the 2003 summer drought event. Finally, for three sites we evaluate whether a more accurate representation of forest structural characteristics (i.e. cohorts, forest layers) and species composition can improve model results. In two of the three sites results reveal that model slightly increases its performances although, statistically speaking, not in a relevant way.Peer reviewe