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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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