High concentrations of ozone in ambient air are hazardous not only to humans but to the ecosystem in general. The impact of ozone damage on vegetation and agricultural plants in combination with advancing climate change may affect food security in the future. While the future scenarios in themselves are uncertain, there are limiting factors constraining the accuracy of surface ozone modeling also at present: The distribution and amount of ozone precursors and ozone depleting substances, the stratosphere-troposphere exchange as well as scavenging processes. Removal of any substance through gravitational settling or 5 by uptake by plants and soil is referred to as dry deposition. The process of dry deposition is important for predicting surface ozone concentrations and understanding the observed amount and increase of tropospheric background ozone. The conceptual dry deposition velocities are calculated following a resistance-analogous approach wherein aerodynamic, quasi laminar, and canopy resistances are key components, but these are hard to measure explicitly. In this paper, we present an update of the dry deposition scheme implemented in the Oslo CTM3. We change from a purely empirical dry deposition parameterization to 10 a more process-based one which is taking the state of the atmosphere and vegetation into account. Examining the sensitivity of the scheme to various parameters, our focus lies mainly on the stomatal conductance-based description of the canopy resistance. We evaluate the resulting modeled ozone dry deposition with respect to observations and multi-model studies and also estimate the impact on the modeled ozone concentrations at the surface. We show that the global annual total ozone dry deposition decreases with respect to the previous model version (−47 %), leading to an increase in surface ozone of up to 15 100 %. While high sensitivity to changes in dry deposition to vegetation is found in the tropics, the largest impact on global scales is associated to changes in dry deposition to the ocean and deserts.Geosci. Model Dev. Discuss., https://doi.