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Representing the effects of stratosphere–troposphere exchange on 3-D O3 distributions in chemistry transport models using a potential vorticity-based parameterization
Mathur, R., Jon Pleim, C. Hogrefe, M. Gan, G. Sarwar, David-C Wong, J. Wang, S. McKeen, J. Xing, AND J. Wang. Representing the effects of stratosphere–troposphere exchange on 3-D O3 distributions in chemistry transport models using a potential vorticity-based parameterization. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, Germany, 16:10865-10877, (2016).
Downward transport of ozone (O3) from the stratosphere can be a significant contributor to tropospheric O3 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 parameterize upper tropospheric and/or lower stratospheric (UTLS) O3 in a chemistry transport model. This dynamic O3–PV function is developed 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 O3 ∕ 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 O3 ∕ PV function was then applied in the Community Multiscale Air Quality (CMAQ) model for an annual simulation of the year 2006. The simulated UTLS O3 agrees much better with observations in both magnitude and seasonality after the implementation of the new parameterization. Considerable impacts on surface O3 model performance were found in the comparison with observations from three observational networks, i.e., EMEP, CASTNET and WDCGG. With the new parameterization, 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 O3 from upper layers has large impacts on surface concentration and needs to be properly represented in regional models.
The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
Record Details:Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL EXPOSURE RESEARCH LABORATORY
COMPUTATIONAL EXPOSURE DIVISION