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Different aspects of the quality assurance and quality control (QA/QC) of micrometeorological measurements were combined to create a comprehensive algorithm which was then applied to experimental data from LITFASS-2003 (Lindenberg Inhomogeneous Terrain-Fluxes between Atmosphere and Surface: a long term Study). Eddy-covariance measurements of the latent heat flux were the main focus of the QA/QC efforts. The results of a turbulence sensor intercomparison experiment showed deviations between the different eddy-covariance systems on the order of 15%, or less than 30 W m −2 , for the latent heat flux and 5%, or less than 10 W m −2 , for the sensible heat flux. In order to avoid uncertainties due to the post-processing of turbulence data, a comprehensive software package was used for the analysis of experimental data from LITFASS-2003, including all necessary procedures for corrections and quality control. An overview of the quality test results shows that for most of the days more than 80% of the available latent heat flux data are of high quality so long as there are no instrumental problems. The representativeness of a flux value for the target land-use type was analysed using a stochastic footprint model. Different methods to calculate soil heat fluxes at the surface are discussed and a sensitivity analysis is conducted to select the most robust method for LITFASS-2003. The lack of energy balance closure, which was found for LITFASS-2003, can probably be attributed to the presence of low-frequency flux contributions that cannot be resolved with an averaging time of 30 min. Though the QA/QC system has been developed for the requirements of LITFASS-2003, it can also be applied to other experiments dealing with similar objectives.

Abstract. We applied a site evaluation approach combining Lagrangian Stochastic footprint modeling 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.

Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate-regulating properties of forests. Using both tower-based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO 2 forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO 2 forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane-damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models.

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SummaryMeasuring turbulent fluxes with the eddy covariance method has become a widely accepted and powerful tool for the determination of long term data sets for the exchange of momentum, sensible and latent heat, and trace gases such as CO 2 between the atmosphere and the underlying surface. Several flux networks developed continuous measurements above complex terrain, e.g. AmeriFlux and EUROFLUX, with a strong focus on the net exchange of CO 2 between the atmosphere and the underlying surface. Under many conditions basic assumptions for the eddy covariance method in its simplified form, such as stationarity of the flow, homogeneity of the surface and fully developed turbulence of the flow field, are not fulfilled. To deal with non-ideal conditions which are common at many FLUXNET sites, quality tests have been developed to check if these basic theoretical assumptions are valid.In the framework of the CARBOEUROFLUX project, we combined quality tests described by Foken and Wichura (1996) with the analytical footprint model of Schmid (1997). The aim was to identify suitable wind sectors and meteorological conditions for flux measurements. These tools were used on data of 18 participating sites. Quality tests were applied on the fluxes of momentum, sensible and latent heat, and on the CO 2 -flux, respectively. The influence of the topography on the vertical wind component was also checked. At many sites the land use around the flux towers is not homogeneous or the fetch may not be large enough. So the relative contribution of the land use type intended to be measured was also investigated. Thus the developed tool allows comparative investigations of the measured turbulent fluxes at different sites if using the same technique and algorithms for the determination of the fluxes as well as analyses of potential problems caused by influences of the surrounding land use patterns.

As surface temperatures are expected to rise in the future, ice-rich permafrost may thaw, altering soil topography and hydrology and creating a mosaic of wet and dry soil surfaces in the Arctic. Arctic wetlands are large sources of CH , and investigating effects of soil hydrology on CH fluxes is of great importance for predicting ecosystem feedback in response to climate change. In this study, we investigate how a decade-long drying manipulation on an Arctic floodplain influences CH -associated microorganisms, soil thermal regimes, and plant communities. Moreover, we examine how these drainage-induced changes may then modify CH fluxes in the growing and nongrowing seasons. This study shows that drainage substantially lowered the abundance of methanogens along with methanotrophic bacteria, which may have reduced CH cycling. Soil temperatures of the drained areas were lower in deep, anoxic soil layers (below 30 cm), but higher in oxic topsoil layers (0-15 cm) compared to the control wet areas. This pattern of soil temperatures may have reduced the rates of methanogenesis while elevating those of CH oxidation, thereby decreasing net CH fluxes. The abundance of Eriophorum angustifolium, an aerenchymatous plant species, diminished significantly in the drained areas. Due to this decrease, a higher fraction of CH was alternatively emitted to the atmosphere by diffusion, possibly increasing the potential for CH oxidation and leading to a decrease in net CH fluxes compared to a control site. Drainage lowered CH fluxes by a factor of 20 during the growing season, with postdrainage changes in microbial communities, soil temperatures, and plant communities also contributing to this reduction. In contrast, we observed CH emissions increased by 10% in the drained areas during the nongrowing season, although this difference was insignificant given the small magnitudes of fluxes. This study showed that long-term drainage considerably reduced CH fluxes through modified ecosystem properties.

[1] We present an inverse modeling framework designed to constrain CO 2 budgets at regional scales. The approach captures atmospheric transport processes in high spatiotemporal resolution by coupling a mesoscale model with Lagrangian Stochastic backward trajectories. Terrestrial biosphere CO 2 emissions are generated through a simple diagnostic flux model that splits the net ecosystem exchange into its major components of gross primary productivity and autotrophic and heterotrophic respirations. The modeling framework assimilates state-of-the-art data sets for advected background CO 2 and anthropogenic fossil fuel emissions as well as highly resolved remote sensing products. We introduce a Bayesian inversion setup, optimizing a posteriori flux base rates for surface types that are defined through remote sensing information. This strategy significantly reduces the number of parameters to be optimized compared with solving fluxes for each individual grid cell, thus permitting description of the surface in a very high resolution. The model is tested using CO 2 concentrations measured in the fall and winter of 2006 at two AmeriFlux sites in Oregon. Because this database does not cover a full seasonal cycle, we focus on conducting model sensitivity tests rather than producing quantitative CO 2 flux estimates. Sensitivity tests on the influence of spatial and temporal resolution indicate that optimum results can be obtained using 4 h time steps and grid sizes of 6 km or less. Further tests demonstrate the importance of dividing biome types by ecoregions to capture their different biogeochemical responses to external forcings across climatic gradients. Detailed stand age information was shown to have a positive effect on model performance.Citation: Göckede, M., A. M. Michalak, D. Vickers, D. P. Turner, and B. E. Law (2010), Atmospheric inverse modeling to constrain regional-scale CO 2 budgets at high spatial and temporal resolution,