Numerical Modeling

Numerical modeling, a term that we define as "the use of mathematical and computer/computational techniques to represent and analyze physical events", is the focus of this entire course. At this stage, you should understand the basics of atmospheric sciences -- chemistry and physics --, meteorology, and the foundations of computational science. This course focuses on the use of numerical modeling technologies, techniques, and tools in atmospheric sciences.

In OS411C: Meteorology for Air Quality Modeling, we discussed specific tools for numerical modeling in that area, namely numerical weather prediction (NWP) models. In this course, we will present a variety of numerically-intensive tools that are used in different areas of the study of atmospheric science. Most of the models presented are generically identified as "air quality models (AQM)", although other types of models, such as energy balance models (EBM) are also presented.

The graphic at right shows a conceptual schematic of generic AQMs. This schematic shows all of the components of an AQM, including theses components: scientific: the schematic includes information on scale (global, regional, meso, local, and surface), emissions (biogenic, anthropogenic, geogenic), meteorology (air mass, circulation, stability), chemistry (photolysis, radicals chemistry), and physics (transport) policy: the schematic also includes the role of public policy as influenced by the results of attainment tests (typically models that predict or forecast future ozone levels in a community). The actions of existing and new policies (and their costs!) and their affect on the activities of the society are also appropriately included in the schematic regulatory: the schematic is "driven", to some extent, by the National Ambient Air Quality Standards (NAAQS), the federal standards for air quality (ozone, PM, and other secondary pollutants). It is probably safer to say, however, that the ambient concentrations of primary and secondary pollutants is probably the driving variable on the schematic. The effect of exposure of pollutants and methods for their reduction are the "motivation" for research and development efforts in atmospheric modeling.

In the remainder of this course, we present a variety of categories of models (diagnostic, prognostic, Lagrangian, Eulerian), some representative models (EBM, radiative convective model, regional oxidant model, etc.), methods of forecasting ozone, and an overview of some of the more important AQMs. The reader should understand that the area of atmospheric modeling is quite rich, both in breadth and depth, and that the information described in this course is just the tip of the iceberg!