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Quantifying Carbon Uptake by Vegetation for Europe on a 1km² Resolution. M. Tum, C. Seipp, M. Niklaus, K.P. Günther German Aerospace Center (DLR), German Remote Sensing Data Center (DFD).
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Quantifying Carbon Uptake by Vegetation for Europe on a 1km² Resolution M. Tum, C. Seipp, M. Niklaus, K.P. Günther German Aerospace Center (DLR), German Remote Sensing Data Center (DFD) Introduction: During the last decades quantifying sinks and sources of climatological relevant trace gases as well as understanding their exchanges between atmosphere and land surface, have become essential research topics in atmospheric science. Modelling the CO2 uptake by vegetation via photosynthesis (Net Primary Productivity, NPP) has become an important tool to study the mechanisms of CO2 exchange. At the German Aerospace Center (DLR) the Biosphere Energy Transfer Hydrology (BETHY/DLR) vegetation model is used to perform simulations of NPP over Europe. The model is driven by remote sensing data of the Leaf Area Index (LAI) and land cover classification and meteorological data from the European Center for Medium-Range Weather Forecast (ECMWF). The model output is given as time series of Gross Primary Productivity (GPP) and NPP on a 1km² resolution. Methodology: With this study we like to introduce our upgraded version of the Biosphere Energy Transfer Hydrology (BETHY/DLR) Model (Wißkirchen, 2005; Knorr, 1997), which is designed for regional to continental applications. The model was already validated for Germany’s forests and agricultural areas using empirical data (Tum and Günther, 2011; Tum et al., 2011). As an example, the annual NPP of forest, agriculture and grassland areas in Europe for 2007 is shown in Figure 1 with spatial resolution of 1 km². For South-East Europe and especially for the Mediterranean area the highest values are found. Furthermore it is obvious that the NPP decreases with latitude. In total Europe’s vegetation accumulated 1320 Gt carbon in 2007. In order to assess the quality of the model results time series of estimated GPP from 83 European FLUXNET tower sites are compared with modeled GPP for the years 2000 to 2007. For each FLUXNET station we used the level 4 product of calculated GPP given as half hourly time series. The distribution of the selected FLUXNET sites is presented in figure 2, covering six different vegetation types. We excluded all datasets with less than two complete years of measurement. Results: As shown in figure 3 the modelled monthly GPP corresponds in its general annual course with the monthly eddy covariance measurements. It is also evident from figure 3 that BETHY/DLR tends to show lower GPP than the FLUXNET estimates. For most of the sites and years we found differences in the monthly and annual estimates of FLUXNET and modelled GPP values, which might be due to an underestimation of daytime respiration needed to calculate GPP from the eddy covariance measurements. This hypothesis is based on our findings that the annual modelled NPP for both agriculture and forest areas is highly correlated with statistical field data (Tum and Günther, 2011). Future investigations have to be carried out for clarification. Figure 1: Annual NPP of forest, agriculture and grassland areas in Europe for 2007. High NPP is shown in green, and low NPP in grey. Figure 3:Comparison of monthly GPP sums as calculated with FLUXNET data and BETHY/DLR results for an agriculture (DK_Ris, Denmark) and a needle-leaved forest site (SE_Sk1, Sweden) , for the period 2004 to 2007. W. Knorr (1997): Satellite Remote Sensing and Modelling of the Global CO2 Exchange of Land Vegetation: A Synthesis Study, Dissertation - Faculty of Earth Sciences of the University of Hamburg M. Tum and KP. Günther (2011): Validating modelled NPP using statistical yield data. Biomass and Bioenergy 35:4665-4674. M. Tum et al. (2011): Validation of modelled forest biomass in Germany using BETHY/DLR. Geoscientific Model Development 4:1019-1034. K. Wißkirchen (2005): Modellierung der regionalen CO2-Aufnahme durch Vegetation, Dissertation - Mathematisch-Naturwissenschaftliche Fakultät der Rheinischen Friedrich-Wilhelms Universität Bonn Figure 2: Distribution of 83 FLUXNET tower sites in 18 European countries.