Development of a Three-Dimensional Regional and Global Model for Chemical/Dynamical Evolution of Ozone and Nitrogen Oxides in the Troposphere

点击翻译按钮获取中文摘要

To date most models for global-scale photochemistry have included detailed chemistry but have represented dynamics with a one- or two-dimensional treatment with transport based on eddy diffusion coefficients. Models of this type calculate photochemical production and loss terms based on concentrations of nitrogen oxides and other species averaged over an entire latitude band. They omit the geographical variation in nitrogen oxides concentrations which ranges over three orders of magnitude. Models of this type cannot be used to evaluate species concentrations in specific locations (e.g. the north Atlantic) that have complex source-receptor relations. Even the calculation of global average species concentrations may be flawed due to nonlinearities in the chemistry. Photochemical production and loss rates are very different in polluted environments or in regions of biomass burning than in remote continental or marine locations, and rates also depend on local meteorology. Models for global photochemical production and loss must account for these differences. This project is designed to develop a realistic chemical module which, while capable of simulating the complex nitrogen, hydrocarbon and ozone chemistry associated with atmospheric pollution, will run efficiently and effectively in a global chemical transport model. The chemical module will be developed and tested in the GFGL global chemical transport model. Successful development of a chemical module that realistically simulates photochemical production and loss of nitrogen oxides and ozone and that economically operates in a global transport model offers a number of scientific benefits. Accurate three imensional models are an essential tool for evaluating photochemical evolution in the global troposphere in a way that includes geographical variation and the episodic nature of meteorological events. A three dimensional model also allows direct comparison of results with observed species concentrations.