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Process-Based Evaluation of the Representation of Lake-Effect Snowstorms in the Great Lakes Region Among CMIP6 Earth System Models

Abstract: The vast socio-economic importance of the Great Lakes cannot be understated. They
contain 95% of the U.S.’ freshwater supply and impact power production, navigation, industry,
commerce, recreation, agriculture, and ecosystems. Their basin has been a regional hotspot of
pronounced climate change impacts, including rising air temperatures, more frequent heavy
precipitation events, rapid summer warming of lake surfaces, declining lake ice cover, enhanced
lake evaporation, and increase in lake-effect snowfall. Extreme weather events have drawn
increased attention, due to their acute societal impacts, improved modeling capabilities, and
climate change concerns. While the Intergovernmental Panel on Climate Change (IPCC) reports
and National Climate Assessments summarize existing research on extreme events, they give
minimal attention to lake-effect snowstorms, despite their dramatic socio-economic and
environmental impacts. It remains unclear how the frequency of these cold season extremes will
change during this century. The insufficient investigation of projected changes in these cold
season extremes is partly due to the general lack of suitable modeling tools that properly
represent the Great Lakes and associated lake-atmosphere interactions, at a sufficient spatial
resolution. The CMIP6 High Resolution Model Intercomparison Project (HighResMIP)
represents an unprecedented multi-institutional effort to generate global simulations down to a
median resolution of 30 km and a unique opportunity to assess the capability of high-resolution
GCMs to accurately represent lake-atmosphere interactions and resulting lake-effect snowstorms.

A process-based evaluation is proposed of the representation of lake-atmosphere
interactions and resulting lake-effect snowstorms in the Great Lakes region among CMIP6 Earth
System Models. Analysis will primary focus on HighResMIP runs and their likely advances
over coarse DECK historical runs. Analyzed observational datasets will include: station
snowfall from NCDC and Environment Canada; CloudSat and Global Precipitation
Measurement cloud/snowfall estimates; wind, temperature, and sea-level pressure from North
American Regional Reanalysis; Great Lakes Evaporation Network over-lake evaporation and
turbulent flux measurements; buoy water temperature, air temperature, and wind from National
Data Buoy Center; Great Lakes Surface Environmental Analysis lake-surface temperature; Great
Lakes Environmental Research Laboratory (GLERL) vertical lake temperature data; GLERL
lake ice thickness; over-lake precipitation, lake evaporation, and drainage basin runoff from
GLERL Great Lakes hydrologic dataset; and NOAA Great Lakes Ice Atlas. The following
meteorological and limnological variables, considered as essential mechanistic ingredients in
lake-effect snow forecasting, will be evaluated in HighResMIP runs in terms of lake-effect
snowfall occurrence and intensity: temperature difference between the lake surface and 850-hPa;
direction and speed of the sub-700-hPa steering wind; lower tropospheric vertical directional
shear of the steering wind; existence, height, and strength of a low-level subsidence inversion;
over-lake vapor pressure gradient; and lake ice cover. The study is highly relevant to MAPP
competition objectives of addressing key issues in CMIP6 ESMs in terms of climate extremes,
through the design and application of process-oriented metrics for evaluating and improving the
representation of lake-atmosphere interactions and resulting lake-effect snowstorms in CMIP6
models. The project addresses NOAA’s goals to attain “improved…understanding of the
changing climate system” and perform “assessments of current and future states of the climate
system that identify…impacts and inform…decisions.”

Climate Risk Area: Water Resources

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