Representing the effects of stratosphere-troposphere exchange on 3D O3 distributions in chemistry transport models using a potential vorticity based parameterization
Atmospheric Chemistry and Physics Discussions
Downward transport of ozone (O<sub>3</sub>) from the stratosphere can be a significant contributor to tropospheric O<sub>3</sub> background levels. However, this process often is not well represented in current regional models. In this study, we develop a seasonally and spatially varying potential vorticity (PV)-based function to numerically assimilate upper tropospheric / lower stratospheric (UTLS) O<sub>3</sub> in a chemistry transport model. This dynamic O<sub>3</sub>-PV function is
... unction is parametrized based on 21-year ozonesonde records from World Ozone and Ultraviolet Radiation Data Centre (WOUDC) with corresponding PV values from a 21-year Weather Research and Forecasting (WRF) simulation across the northern hemisphere from 1990 to 2010. The result suggests strong spatial and seasonal variations of O<sub>3</sub>/PV ratios which exhibits large values in the upper layers and in high latitude regions, with highest values in spring and the lowest values in autumn over an annual cycle. The newly-developed O<sub>3</sub>/PV function was then applied in the Community Multiscale Air Quality (CMAQ) model for an annual simulation of the year 2006. The simulated UTLS O<sub>3</sub> agrees much better with observations in both magnitude and seasonality after the implementation of the new function. Considerable impacts on surface O<sub>3</sub> model performance were found in the comparison with observations from three observational networks, i.e., EMEP, CASTNET and WDCGG. With the new function, the negative bias in spring is reduced from −20 to −15 % in the reference case to −9 to −1 %, while the positive bias in autumn is increased from 1 to 15 % in the reference case to 5 to 22 %. Therefore, the downward transport of O<sub>3</sub> from upper layers has large impacts on surface concentration and needs to be properly represented in regional models.