Estimating the Carbon Cycle of South Africa with BETHY/DLR

Abstract

Quantifying sources and sinks of climatological relevant trace gases as well as understanding their exchange between atmosphere and land surface have become essential research topics in atmospheric sciences during the last years. Modelling of the net CO2 uptake by vegetation via photosynthesis (Net Primary Productivity, NPP) has become an important tool to study the mechanisms of CO2 exchange and to quantify the magnitude of terrestrial sinks and sources. The vegetation model BETHY/DLR (Biosphere Energy Transfer Hydrology Model), used in our studies at the German Aerospace Center (DLR), is modified to simulate the carbon cycle in vegetated areas, computing the NPP for different regions on regional to national scales. The model is driven by remote sensing data of leaf area index (LAI) and land cover classification (GLC2000) and meteorological input data which is provided by the European Center for Medium Range Weather Forecast (ECMWF). variety of the vegetated areas can be considered. The model was widely tested and validated for Europe on coarse resolution (27 km) and on high resolution (1 km) for forests and croplands in Germany and Austria using statistical data for validation. The actual area of investigations is South Africa with special interest to analyse desertification and land degradation in terms of NPP. In collaboration with other PhD students connected via the Earth Observation System network (EOS network) of the Helmholtz Association, the presented work contributes to the understanding and solution process of these problems in semiarid areas resulting from global change. Our studies are included in the EOS topic “Global Change and Processes on the Land Surface” where specifically semiarid ecosystems are investigated facing the problem of desertification and land degradation. For this we started to adjust our model to the specific needs of the semiarid landscapes of South Africa, where first NPP maps with 1km spatial resolution for several years will be presented and discussed. Further steps will be the implementation of a phenology model to simulate plant growth and the development of an assimilation procedure to forecast the trend of the changes in the analysed ecosystems.