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Atmospheric Modeling and Analysis Research

Research in Action

Air Quality and Climate Change Interactions

lighting over a lake


Global climate change is a complex problem: How does it affect other systems in the environment? How will a changing climate affect already-existing environmental management systems? And how can we take steps to reduce the effects of climate change around us? Because of the scale of climate change, scientists need tools that can be used on the regional and local levels to determine what impacts climate change will have, and how different emissions policies might reduce or eliminate these effects.

There are many potential effects of a changing climate. Water and air quality can be impaired, hurting human health. It can become more difficult to find and access water in certain areas. Airborne pollutants can deposit in areas where they previously hadn’t been found.

To protect human health and the environment, EPA needs modeling tools that can simulate the ways that air pollutants interact with changing climate – both how the pollutants affect the air, and how the changing air impacts the way pollutants move through the atmosphere. Using these models, scientists can estimate the effects of different air quality management policies before they’re put into place.

To inform mitigation strategies, there is also a need for modeling tools that can rapidly screen large numbers of scenarios across a wide range of assumptions about the future. Scientists additionally need models that can scale from global to regional and even local spatial resolutions. Global climate models typically have spatial resolutions of the order of 100 kilometers or larger. These coarse grids are insufficient to simulate geographic features, like mountain ranges and lake systems that can determine regional climate. Additionally, air pollutant emissions tend to be highly concentrated in urban and industrial areas that are not well treated by global models. Global output models, which usually rely on monthly averages, frequently do not provide data often enough to capture extreme weather and pollution events.


EPA scientists are developing techniques for dynamically downscaling future global scenarios to create regional and local climate scenarios that can assess the effects of future climate change on air quality, water quality and availability, heat stress, health, and ecosystem exposures, as well as changes in extreme events.

While Earth System Models and Integrated Assessment Models strive to accurately and comprehensively describe the complex, non-linear relationship between human activities and environmental impacts, they are computationally expensive. EPA scientists are developing a suite of modeling tools, known as GLIMPSE, to rapidly assess climate and air quality impacts of possible mitigation policy options. GLIMPSE — which stands for Geos-CHEM LIDORT Integrated with MARKAL for the Purpose of Scenario Exploration — will be able to quickly calculate the net radiative forcing distributed over the globe for a large number of future scenarios. From this emission scenario screening exercise, a few scenarios will be selected for use with the process-based models described above. The process-based models will then be able to provide a more detailed assessment of future climate and air quality consequences.

Results and Impacts

A prototype of the GLIMPSE model has been developed and will be released in 2012. With this tool, EPA scientists have developed a low-cost technology pathway for achieving important air quality and climate change mitigation goals.

Related Publications
  • Bowden, J. H., T. L. Otte, C. G. Nolte, and M. J. Otte (2011), Examining grid nudging techniques using two-way nesting in the WRF model for regional climate modeling, Journal of Climate, in press.
  • Weaver, C.P., et al. (2009), A preliminary synthesis of modeled climate change impacts on U.S. regional ozone concentrations, Bulletin of the American Meteorological Society, 90.
  • Otte, T. L., C. G. Nolte, M. J. Otte, and J. H. Bowden, Does nudging squelch the extremes in regional climate modeling?, in review, 2012.
  • Bowden, J. H., C. G. Nolte, T. L. Otte, Simulating the impact of the large-scale circulation on the regional climatology, in review, 2012.

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