Climate Change Leading to More Snow?

University of Michigan researchers publish paper on the potential impacts of climate change on lake-effect snow

By: Stephanie Ariganello

Lake effect snow

What impact is climate change having on the Great Lakes region? It’s a broad question and one that is most likely to be answered in pieces.

One such piece may be lake-effect snow, according to David Wright, a doctoral student in the Atmospheric, Oceanic and Space Sciences (AOSS) program at the University of Michigan’s College of Engineering. Wright teamed up with Dr. Derek Posselt, assistant professor, and Dr. Allison Steiner, associate professor, also of AOSS. They built climate scenarios and produced a paper on their lake-effect snow findings.

Sensitivity of Lake-effect Snowfall to Lake Ice Cover and Temperature in the Great Lakes Region has been accepted and submitted for publication in the American Meteorological Society’s publication, Monthly Weather Review. Wright is the lead author.

Wright said explaining climate change is challenging because the way it is studied is very different from how people typically relate to climate.

“In recent years, studies have predicted changes to our climate,” said Wright. “While these studies are valid, humans do not interact with our environment on climate time scales (years to decades), which is part of the challenge of convincing people of climate change. Humans interact with the environment through daily weather systems — Is it warm today? Will there be snow? This study looks at how climate change can impact weather systems, such as lake-effect snow.”

Wright examined the impact of ice cover and water temperature on lake-effect snow. He used a high-resolution weather forecast model to answer the question: How would lake-effect snow be affected if there is complete ice cover on the Great Lakes, no lake ice cover or warmer lake temperatures?

The model performs complex calculations that take into consideration the interaction between ice development, temperature and lake-effect snow. For example, with the projection of warmer temperatures in the future, the change can affect the amount of ice and when the ice forms over the Great Lakes. Lake ice, in a typical year, helps to reduce or even eliminate lake-effect snow in the Great Lake around mid-January to early February, said Wright.

The model indicated that the intensity of the snowfall could also increase, said Wright, which can affect many things like personal travel, more frequent and more intense algal blooms, and draining of local government budgets to clear and remove the snow.

The research was performed as part of a grant project that the U-M College of Engineering and School of Natural Resources and Environment, Michigan Sea Grant, and several other partners are working on, funded by the National Science Foundation. The focus of this project is assessing the effects of climate change on water quality and ecology in the Great Lakes.

Lake Erie algal bloom, photo by Tom Archer.

The topic of lake-effect snow is of interest to the project team because changes in the frequency and amount of lake-effect snow can have a direct connection to water quality. For example, more lake-effect snow can lead to more spring runoff, especially if snowmelt occurs quickly.

The runoff could, in turn, lead to an increase in harmful algal blooms. This paper provides a key piece of the puzzle needed to understand the impact of climate on water quality in the Great Lakes.

The paper provides an overview of each of the three climate scenarios analyzed through the model: complete ice cover, no ice cover and increased surface water temperatures.

“If there is a reduction in lake ice or lake ice starts forming later in the winter season, these factors can help to increase the area along the lakeshore that experience snow in a given lake-effect snow event,” he explained. “If the lake surface temperature begins to significantly increase above normal values seen during the winter season, the overall amount of snowfall increases as well as how far inland the snowfall is seen. This shows (one way) how climate change can begin to impact the distribution of precipitation and intensity in future climate scenarios.”

Research like this meets people halfway between their concrete experiences with weather and the more abstract, large-scale potential climate change scenarios based on predictive models.

“This study helps to show the impacts of climate change on daily life,” he said. “Areas that normally do not experience lake-effect snow could begin to experience more snowfall due to the Great Lakes in the future.”

The paper is available through the Monthly Weather Review.

About the Project

Climate and Water Quality Grant Project

A collaborative research team, supported through the Water Sustainability and Climate program at the National Science Foundation, is evaluating the impact of extreme events on water quality in the Great Lakes. Researchers are developing a framework for integrating human, biological, geographic and chemical controls on water quality, ecology and climate though a collaborative and interdisciplinary process.

The project focuses on the prediction of feedbacks between regional climate change and extreme precipitation events, and also looks at management scenarios that would be effective in protecting water quality under a changing climate. Climate models predict more frequent occurrence of extreme events as the climate system changes, but predictions for specific regions are more uncertain.

This material is based upon work supported by the National Science Foundation under Grant Number 1039043. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

See: NSF Climate and Water Quality Project

Full Paper Citation:  

Wright, David M., Derek J. Posselt, Allison L. Steiner, 2013: Sensitivity of Lake-Effect Snowfall to Lake Ice Cover and Temperature in the Great Lakes Region. Mon. Wea. Rev., 141, 670–689. doi: http://dx.doi.org/10.1175/MWR-D-12-00038.1