Climate change will affect forests, but tools which would facilitate risk assessment and informed decision making, based on understanding undelaying biogeochemical processes in forests, currently do not exist in Croatia. MODFLUX aims at providing climate change equipped modelling framework that is adapted for national forest ecosystems and environmental conditions. Using a model‑data‑fusion (MDF) technique, through an iterative and interactive process of comparison of model results and measured data, continuous adjustment of model parameters, and possible modification of the model, we will calibrate and validate a process-based biogeochemical model Biome-BGCMuSo for main national forest ecosystems. In MDF we will use two existing independent datasets which will be expanded with additional data from new field measurements. First dataset is a high-frequency eddy covariance (EC) data of CO₂ fluxes at forest experimental station in Jastrebarsko, which is operational since 2008. Second dataset is spatially-explicit database on above and belowground forest ecosystem variables (i.e. wood biomass increment obtained from tree-rings, carbon stocks in forest floor and soil, fine root biomass) collected at 250 plots distributed throughout Continental, Alpine and Mediterranean regions of Croatia. Using future climate scenarios calibrated model will yield with improved capacity for the assessment of climate change impact on different forest types. Estimated changes in soil carbon stocks, obtained within MODFLUX, would be available for consideration in Croatia’s GHG reporting. By estimating forest fire risks under future climate scenarios MODFLUX will be the first to provide, to the policymakers and to the general public, a notion of the expected future fire risks in forest-rich parts of Croatia which are currently not affected by forest-fires. Overhaul of the existing EC station will ensure the continuation of the internationally unique research of CO₂ fluxes in periodically flooded, pedunculate oak forest. Project results will be published in high impact factor journals and data collected within the project will be uploaded to open-access scientific databases.