In 2015, the Great Lakes Integrated Sciences and Assessments program (GLISA) formally started the development of a Great Lakes Ensemble of future climate projections and guidance for practitioners in 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 current challenge is not a lack of climate projections to choose from, rather, today’s practitioner is faced with an overwhelming large quantity of projections with very little guidance on how to choose the most relevant ones for their work.
The Ensemble project aims to address challenges associated with choosing and using climate projections by summarizing projections for adaptation audiences and providing expert guidance for advanced users. Ultimately, the Ensemble project as a whole is intended to increase the capacity of practitioners to be informed consumers of climate information.
Scientific and Stakeholder Advisors
The Ensemble project is informed by external two groups, a scientific advisory committee and stakeholder working group, that are made up of a diverse set of scientists and adaptation professionals who bring valuable regional perspectives to this work. Each of these groups is bi-national, including both U.S. and Canadian partners, which is essential since the Ensemble’s geographic scope includes any state that touches a Great Lake and southern Ontario.
|The Ensemble's Scientific Advisory Committee (SAC) is helping GLISA:||The Ensemble's Stakeholder Working Group (WG) is:|
1. Better understand the interactions between the lakes and our regional climate
1. Providing feedback on existing GLISA products that are commonly used by stakeholders (i.e., city climatologies, Great Lakes Adaptation Data Suite (GLADS))
2. Develop a set of model evaluation standards specific to the Great Lakes region
2. Co-developing new stakeholder products with GLISA (i.e., scenarios, consumer-style data guides, and more)
3. Reach out to end users who can help inform products of the ensemble
3. Investigating with GLISA how to scale products to larger audiences and increase usability across the region
Resources & Publications
Additional resources and information related to the Ensemble can be found at the Climate Workspace.
Frequently Asked Questions
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.