Accurate model representation of land- atmosphere carbon fluxes is essential for climate projections. However, the exact responses of carbon cycle processes to climatic drivers often remain uncertain. Presently, knowledge derived from experiments, …
Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative to global environmental change. A full characterization of C cycling requires detailed information on spatiotemporal patterns of …
Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes and fires can have severe regional effects, but a …
Temporal variability of meteorological variables and extreme weather events is projected to increase in many regions of the world during the next century. Artificial experiments using process-oriented terrestrial ecosystem models make it possible to …
Assumptions of steady-state conditions in biogeochemical modelling are often invoked because knowledge on the development status of the modelling domain is generally unavailable. Here, we investigate the role of vegetation pool sizes on …
Information about the uncertainties associated with eddy covariance measurements of surface-atmosphere CO2 exchange is needed for data assimilation and inverse analyses to estimate model parameters, validation of ecosystem models against flux data, …