In 2015, GLISA formally started the development of an Ensemble of future climate projections and information for the Great Lakes region. This project is motivated by the need for high-quality, regionally relevant climate projections for use in climate change adaptation work. The U.S. Great Lakes are known for their impact on local and regional weather and climate, however, the processes responsible for producing lake-effects and lake-induced modifications of weather are often poorly represented or missing from climate models. The Ensemble project addresses this gap through regionally based evaluation of climate models to identify models that offer the highest quality information (and models that should not be used).
The Ensemble consists of:
1. An evaluation framework, specifically tailored to the Great Lakes region, that provides a regional perspective on the quality of information coming from the models.
2. Expert guidance regarding the limitations, shortcomings, and appropriate uses of the climate model data.
3. Synthesis and integration of information from the models that “pass” our evaluation framework into GLISA products (i.e., regional climatologies) to provide narratives and visual representations of future climate change information to stakeholders.
Ensemble Primary Documents
Additional resources and information related to the Ensemble can be found at the Climate Workspace.
The Ensemble's scientific advisory committee is helping GLISA:
1. Better understand the interactions between the lakes and our regional climate
2. Develop a set of model evaluation standards specific to the Great Lakes region
3. Reach out to end users who can help inform products of the ensemble
Members: Drew Gronewold (NOAA Great Lakes Environmental Research Laboratory) | Michael Notaro (University of Wisconsin - Madison) | Peter Snyder (University of Minnesota) | Joe Barsugli (NOAA Earth System Research Laboratory) | Edmundo Fausto (Ontario Climate Consortium) | Glenn Milner (Ontario Climate Consortium) | Biljana Music (Ouranos)
We are in the process of collecting names of those who are 1) interested in staying informed of Ensemble work and/or 2) willing to co-develop, use, and provide evaluation of early Ensemble products. Please indicate if you are interested in either option using our Stakeholder Form.
What is an ensemble?
"Ensembles" are collections of data from multiple climate model simulations. Typically, an ensemble consists of data from several different climate models to show the range of variability. Given that no single model perfectly simulates the dynamics governing any scale of climate (global, regional, or local), the reliance on several model simulations allows users to better characterize the range of possible future climate outcomes. To that end, ensembles provide measures of uncertainty related to the model-based information.
Why is GLISA developing a Great Lakes Ensemble?
Many climate models do not provide credible information for the Great Lakes region, because they poorly represent the Great Lakes and lake-land-atmosphere dynamics. GLISA is evaluating several climate model data sets to establish a set (ensemble) 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 single standard methodology for developing ensembles, but using simple model selection procedures with detailed documentation is one way to build a credible ensemble.1 GLISA is developing a regional model evaluation framework to assess an initial set of widely accepted climate model data sets (global and regional). The most basic evaluation criteria include:
1. The model provides data that is continuous in space and time
a. The Great Lakes are simulated in the model
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
For additional information please contact Laura Briley (firstname.lastname@example.org)
- 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.