Adapted from: Lenart, M. Basics of Regional Models. (September 14, 2008). Southwest Climate Change Network
Although climate change projections are most reliable at the global level, people seeking to adapt and respond to the projected changes need to know about climate change impacts at the local level. Fortunately, increasing resolution and other advances in global climate models (GCMs) are helping to improve regional scale modeling.
Increasingly reliable regional climate change projections are now available for many regions of the world, thanks to advances in modeling and understanding of the physical processes of the climate system (Christensen et al. 2007). Using a high-resolution weather model for a dynamic regional climate model allows researchers to produce a more realistic topography and better representation of finer landscape-atmosphere feedbacks, all of which can help produce more realistic simulations of climate.
Scientists are confident resolution will continue to improve as computational power increases. In the meantime, researchers expect that their efforts to refine regional models will in turn improve the skill of GCMs. A greater understanding of climate dynamics at the regional scale should translate well into improved GCMs as the resolution of global models approaches that of existing regional models.
With their better spatial resolution, regional scale models can help resolve important factors affecting regional climate, as David Bader and his colleagues reported (2008) in their detailed assessment of the status of climate models. These factors include:
- Jet stream activity, which particularly influences the frontal storms driving winter and spring precipitation.
- Tropical storms, including those comprising monsoons and hurricanes.
- Elevational effects of mountains, with their year-round influence on temperature and precipitation.
As the resolution of global climate models improves, so does the potential for considering a higher resolution on the regional scale -- but sometimes researchers seeking more detail on the landscape push the resolution beyond what can be considered scientifically robust. A general rule holds that a regional model’s resolution should not surpass about one-twelfth of the resolution of the model feeding into it (Bader et al. 2008). As GCM resolution has increased to about 4,000 square miles per grid square, regional models could reliably drop down to resolutions of about 350 square miles, roughly twice the area of Albuquerque.
Regional models rely on the input of GCMs from individual models, as is standard for dynamical downscaling. In contrast, approaches using statistical downscaling can employ the averages of many GCMs, using what modelers call multiple model ensembles. Both dynamical and statistical approaches depend on having reasonable input from GCMs. In other words, major climate features, such as the jet stream, must be in the right position at the right time when feeding into regional climate models for the latter to perform well.
Adapted for eXtension.org by Melanie Lenart, University of Arizona
References Cited
Bader, D.C., C. Covey, W.J. Gutowski, I.M. Held, K.E. Kunkel, R.L. Miller, R.T. Tokmakian, and M.H. Zhang, 2008. Climate Models: An Assessment of Strengths and Limitations. A report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological and Environmental Research, Washington, D.C. Available at: http://www.sc.doe.gov/ober/sap3-1-final-all.pdf
Christensen, J.H., B. Hewitson, A. Busuioc, A. Chen, X. Gao, I. Held, R. Jones, R.K. Kolli, W.-T. Kwon, R. Laprise, V. Magaña Rueda, L. Mearns, C.G. Menéndez, J. Räisänen, A. Rinke, A. Sarr, and P. Whetton, 2007: Regional Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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