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Falge, E; Foken, T*: Influence of the energy balance closure problem on the fluxes measured at CarboEurope flux stations
Poster, 5th CarboEurope-IP Integrated Project Meeting, Poznan: 08.10.2007 - 12.10.2007

Abstract:
Well-known examples of problems in interpreting eddy covariance (EC) data as biophysical flux of CO2, or energy between the vegetation and the atmosphere are related to conditions where basic assumptions for EC theory is not fulfilled. Many sites do not show flat terrain, homogeneous vegetation, or a constant flux layer. In addition, absence of or low turbulence or occurrence of horizontal and vertical advection limit the applicability of EC. Another – eventually related - problem of the EC method is the common absence of a surface energy balance. Closure improves with turbulent intensity, and a plethora of causes are discussed in literature (sensor alignment, flow distortion, non-ideal terrain and inconsistent source areas, flux divergence, low frequency loss, averaging periods, or effects of turbulent organized, coherent structures). According to recent findings the energy balance closure problem is connected with the heterogeneity of the landscape and to circulations which are generated by these heterogeneities. To improve standardization of post-processing methods, data interpretation and homogeneity for utilization in budgeting and modeling studies, we investigated effects of footprint heterogeneity on EC measurements for several forested sites of CarboEurope-IP. We analyzed mean diurnal courses of relative energy balance with respect to quality flags of either sensible or latent heat flux. Similarly, we compared average relative energy balances for quality flag cross-products. We examined the influence of landuse heterogeneity in the data footprint on energy imbalance, and potential causes of energy imbalances. Together with analyses of the spatial representativeness of data using footprint modelling (Göckede et al. 2004, 2006, Rebmann et al. 2005), those approaches allowed for a more profound data interpretation, designed to elucidate spatial structures in site maps for residual energy.

Letzte Änderung 28.12.2007