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Natural and anthropogenic disturbances, in particular forest management, affect forest age-structures all around the globe. Forest age-structures in turn influence biophysical and biogeochemical interactions of the vegetation with the atmosphere. Yet, many dynamic global vegetation models (DGVMs), including those used as land surface models (LSMs) in Earth system models (ESMs), do not account for subgrid forest age structures, despite being used to investigate land-use effects on the global carbon budget or simulating land–atmosphere interactions. In this paper we present a new scheme to introduce forest age-classes in hierarchical tile-based DGVMs combining benefits of recently applied approaches. Our scheme combines a computationally efficient age-dependent simulation of all relevant processes, such as photosynthesis and respiration, without loosing the information about the exact forest age, which is a prerequisite for the implementation of age-based forest management. This combination is achieved by using the hierarchy to track the area fraction for each age on an aggregated plant functional type level, whilst simulating the relevant processes for a set of age-classes. We describe how we implemented this scheme in JSBACH4, the LSM of the ICON-ESM. Subsequently, we compare simulation output against global observation-based products for gross primary production, leaf area index and above-ground biomass to assess the ability of simulations with and without age-classes to reproduce the annual cycle and large-scale spatial patterns of these variables. The comparisons show differences exponentially decreasing with the number of distinguished age-classes and linearly increasing computation costs. The results demonstrate the benefit of the introduction of age-classes, with the optimal number of age-classes being a compromise between computation costs and accuracy.
