Model framework for global biogeochemical modelling

Spatial modelling is challenging as data acquisition and aggregation is often difficult. Not only is the availability of data challenging, but also its format and scale. To overcome this problem the framework presented here uses global data sets for soil, climate and land use for running the biogeochemical model, ECOSSE. The framework (GlobalECOSSE) can be used on different spatial and time scales. All driving data is aggregated for the target scale. For climate data this is done by averaging. Soils data can be considered either as the dominant soil type or by the area represented by each soil type within a grid cell. The model itself is a one-dimensional model without lateral fluxes, which is applied on the spatially distributed data sets. The model can be run on monthly or daily time steps. This allows the approach to be adapted for the target question. The model can simulate croplands, grasslands, forests and peatlands. The main target variables are greenhouse gas emissions (N2O, CO2, CH4 and NO). We applied this approach for Europe (EU27) to compare monthly and daily simulations for croplands. Main differences, beside the different timesteps, are the management assumptions, which have large impacts on the simulation results. In addition, we provide greenhouse gas emission maps for all three land use types on a monthly time step.