aled climate data) that do not provide credible information for the Great Lakes region. Many models poorly represent the Great Lakes, so their information about future climate is not based on known interactions between the lakes and the atmosphere. GLISA is evaluating the models to establish a set of those that best represent important components of Great Lakes regional climate. In addition to model evaluation, data processessing (i.e., downscaling) methods will also be assessed for their impact on the quality of the data.
How is GLISA developing the Great Lakes Ensemble?
There is no standard methodology for developing ensembles, but using simple model selection procedures with detailed documentation is one way to build a credible ensemble.1 GLISA starts by considering widely accepted climate model data sets (global and regional) within the climate community. Then, GLISA eliminates models that do not meet the following criteria:
1. The model provides data that is continuous in space and time
a. The Great Lakes are simulated in some fashion
b. A signal of the lakes (i.e., effect of the lakes on regional air temperatures and precipitation) is apparent
3. Any downscaling method applied to the model does not assume climate stationarity
Active Project Work
Additional resources and information related to the Ensemble work can be found on its project page at the Climate Workspace. This site is where project members are actively collaborating and developing materials to support the Ensemble.
- 1. a. b. Overland, J. E., Wang M., Bond N. A., Walsh J. E., Kattsov V. M., & Chapman W. L. (2011). Considerations in the Selection of Global Climate Models for Regional Climate Projections: The Arctic as a Case Study*. Journal of Climate. 24(6), 1583 - 1597.
- 2. McSweeney, C. F., Jones R. G., & Booth B. B. B. (2012). Selecting Ensemble Members to Provide Regional Climate Change Information. Journal of Climate. 25(20), 7100 - 7121.
- 3. Stainforth, D. A., Downing T. E., Washington R., Lopez A., & New M. (2007). Issues in the interpretation of climate model ensembles to inform decisions. Philosophical Transactions Of The Royal Society A-Mathematical Physical And Engineering Sciences. 365, 2163-2177.