Assessment and intercomparison of ozone dry deposition schemes over two ecosystems based on Noah-MP in China

Dry deposition of ozone (O-3) is a major sink of O-3 in near-surface air. The uncertainties in any existing dry deposition schemes are large. In this study, we incorporate four dry deposition schemes into the Noah with multiparameterization options model (Noah-MP) to assess the importance of choice of different dry deposition schemes on simulated dry deposition velocity of O-3 (V-d(O-3)) over forest and agricultural ecosystems. Our simulated V-d(O-3) values from different schemes were compared with observational data. All schemes performed similarly for agricultural ecosystems (correlation coefficient of approximately 0.4). For the forest ecosystem, Ball-Berry type schemes performed better than Jarvis-type schemes, with correlation coefficients for V-d(O-3) between simulations and observations being approximately 0.55 and 0.38, respectively. To further improve the efficacy of the simulation of V-d(O-3), we modified two canopy stomatal resistance mechanisms. For the Jarvis stomatal resistance mechanism, the minimum stomatal resistance was modified, with a mean bias of daytime reduction of by 39.3% for the forest ecosystem and 60.9% for the agricultural ecosystem. For Ball-Berry stomatal resistance mechanism, the stomatal resistance mechanism and nitrogen-limiting scheme for photosynthesis were modified. However, the results showed no significant improvement in the V-d(O-3) simulation. The results demonstrate the importance of canopy resistance parameterization over agricultural and forest ecosystems, thus making a strong case for further evaluation and model improvement of O(3 )dry deposition in different ecosystems.

Automated summary

This study evaluates the importance of different dry deposition schemes on the simulated dry deposition velocity of ozone (V-d(O-3)) in forest and agricultural ecosystems. It is found that canopy resistance parameterization plays a crucial role in the simulation of V-d(O-3).