Synoptic climatology of lake‐effect snowfall conditions in the eastern Great Lakes region

2017 ◽  
Vol 37 (12) ◽  
pp. 4377-4389 ◽  
Author(s):  
Zachary J. Suriano ◽  
Daniel J. Leathers
Keyword(s):  
Great Lakes ◽  
Synoptic Climatology ◽  
Great Lakes Region ◽  
Lake Effect

scholarly journals Lake-to-Lake Cloud Bands: Frequencies and Locations

2007 ◽  
Vol 135 (12) ◽  
pp. 4202-4213 ◽  
Author(s):  
Yarice Rodriguez ◽  
David A. R. Kristovich ◽  
Mark R. Hjelmfelt
Keyword(s):  
High Resolution ◽  
Great Lakes ◽  
Satellite Imagery ◽  
Lake Superior ◽  
Great Lakes Region ◽  
Lake Effect ◽  
Time Period ◽  
High Resolution Satellite Imagery

Abstract Premodification of the atmosphere by upwind lakes is known to influence lake-effect snowstorm intensity and locations over downwind lakes. This study highlights perhaps the most visible manifestation of the link between convection over two or more of the Great Lakes lake-to-lake (L2L) cloud bands. Emphasis is placed on L2L cloud bands observed in high-resolution satellite imagery on 2 December 2003. These L2L cloud bands developed over Lake Superior and were modified as they passed over Lakes Michigan and Erie and intervening land areas. This event is put into a longer-term context through documentation of the frequency with which lake-effect and, particularly, L2L cloud bands occurred over a 5-yr time period over different areas of the Great Lakes region.

scholarly journals Synoptic Climatology of Lake-Effect Snow Events off the Western Great Lakes

Climate ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 43
Author(s):  
Jake Wiley ◽  
Andrew Mercer
Keyword(s):  
Great Lakes ◽  
Large Scale ◽  
Lake Michigan ◽  
Lake Superior ◽  
Principal Component ◽  
Forecast Model ◽  
Synoptic Climatology ◽  
Synoptic Scale ◽  
Ongoing Research ◽  
Lake Effect

As the mesoscale dynamics of lake-effect snow (LES) are becoming better understood, recent and ongoing research is beginning to focus on the large-scale environments conducive to LES. Synoptic-scale composites are constructed for Lake Michigan and Lake Superior LES events by employing an LES case repository for these regions within the U.S. North American Regional Reanalysis (NARR) data for each LES event were used to construct synoptic maps of dominant LES patterns for each lake. These maps were formulated using a previously implemented composite technique that blends principal component analysis with a k-means cluster analysis. A sample case from each resulting cluster was also selected and simulated using the Advanced Weather Research and Forecast model to obtain an example mesoscale depiction of the LES environment. The study revealed four synoptic setups for Lake Michigan and three for Lake Superior whose primary differences were discrepancies in a surface pressure dipole structure previously linked with Great Lakes LES. These subtle synoptic-scale differences suggested that while overall LES impacts were driven more by the mesoscale conditions for these lakes, synoptic-scale conditions still provided important insight into the character of LES forcing mechanisms, primarily the steering flow and air–lake thermodynamics.

scholarly journals The Utility of Additional Soundings for Forecasting Lake-Effect Snow in the Great Lakes Region

2001 ◽  
Vol 16 (4) ◽  
pp. 448-462 ◽  
Author(s):  
Christopher P. J. Scott ◽  
Peter J. Sousounis
Keyword(s):  
Great Lakes ◽  
Great Lakes Region ◽  
Lake Effect

scholarly journals Lessons from Inter-Comparison of Decadal Climate Simulations and Observations for the Midwest U.S. and Great Lakes Region

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 266
Author(s):  
Ashish Sharma ◽  
Alan F. Hamlet ◽  
Harindra J.S. Fernando
Keyword(s):  
Great Lakes ◽  
Large Scale ◽  
Climate Modeling ◽  
Wrf Model ◽  
Warm Season ◽  
Great Lakes Region ◽  
Lake Effect ◽  
Simulated Precipitation ◽  
Decadal Climate ◽  
Meteorological Impact

Even with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and temperature at 12- and 4-km horizontal resolutions and compare it with 32-km NARR data and 1/16th-degree gridded observations for the Midwest U.S. and Great Lakes region from 1991 to 2000. We used daily climatology, inter-annual variability, percentile, and dry days as metrics for inter-comparison for precipitation. We also calculated the summer and winter daily seasonal minimum, maximum, and average temperature to delineate the temperature trends. Results showed that NARR data is a useful precipitation product for mean warm season and summer climatological studies, but performs extremely poorly for winter and cold seasons for this region. WRF model simulations at 12- and 4-km horizontal resolutions were able to capture the lake-effect precipitation successfully when driven by observed lake surface temperatures. Simulations at 4-km showed negative bias in capturing precipitation without convective parameterization but captured the number of dry days and 99th percentile precipitation extremes well. Overall, our study cautions against hastily pushing for increasingly higher resolution in climate studies, and highlights the need for the careful selection of large-scale boundary forcing data.

scholarly journals An Investigation of Cold-Season Short-Wave Troughs in the Great Lakes Region and Their Concurrence with Lake-Effect Clouds

2019 ◽  
Vol 58 (3) ◽  
pp. 605-614 ◽  
Author(s):  
Nicholas D. Metz ◽  
Zachary S. Bruick ◽  
Peyton K. Capute ◽  
Molly M. Neureuter ◽  
Emily W. Ott ◽  
...  
Keyword(s):  
Great Lakes ◽  
Lake Michigan ◽  
Short Wave ◽  
Cold Season ◽  
Great Lakes Region ◽  
Cloud Band ◽  
Wave Trough ◽  
Long Wave ◽  
Lake Effect ◽  
Concurrent Events

AbstractThe downwind shores of the Laurentian Great Lakes region often receive prolific amounts of lake-effect snowfall during the cold season (October–March). The location and intensity of this snowfall can be influenced by upper-tropospheric features such as short-wave troughs. A 7-yr cold-season climatology of 500-hPa short-wave troughs was developed for the Great Lakes region. A total of 607 short-wave troughs were identified, with an average of approximately 87 short waves per cold season. Five classes of short-wave troughs were identified on the basis of their movement through the Great Lakes region. This short-wave trough dataset was subsequently compared with the lake-effect cloud-band climatology created by N. F. Laird et al. in 2017 to determine how frequently short-wave troughs occurred concurrently with lake-effect cloud bands. Of the 607 short-wave troughs identified, 380 were concurrent with lake-effect clouds. Over 65% of these 380 short-wave troughs occurred with a lake-effect cloud band on at least four of the five Great Lakes. Short-wave troughs that rotated around the base of a long-wave trough were found to have the highest frequency of concurrence. In general, concurrence was most likely during the middle cold-season months. Further, Lake Michigan featured the highest number of concurrent events, and Lake Erie featured the fewest. It is evident that short-wave troughs are a ubiquitous feature near the Great Lakes during the cold season and have the potential to impart substantial impacts on lake-effect snowbands.

scholarly journals Prediction of Lake-Effect Snow Using Convection-Allowing Ensemble Forecasts and Regional Data Assimilation

2017 ◽  
Vol 32 (5) ◽  
pp. 1727-1744 ◽  
Author(s):  
Seth Saslo ◽  
Steven J. Greybush
Keyword(s):  
Data Assimilation ◽  
Great Lakes ◽  
Forecast Error ◽  
Weather Prediction ◽  
The United States ◽  
Ensemble Prediction ◽  
Great Lakes Region ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
Lake Effect

Abstract Lake-effect snow (LES) is a cold-season mesoscale convective phenomenon that can lead to significant snowfall rates and accumulations in the Great Lakes region of the United States. While limited-area numerical weather prediction models have shown skill in prediction of warm-season convective storms, forecasting the sharp nature of LES precipitation timing, intensity, and location is difficult because of model error and initial and boundary condition uncertainties. Ensemble forecasting can incorporate and quantify some sources of forecast error, but ensemble design must be considered. This study examines the relative contributions of forecast uncertainties to LES forecast error using a regional convection-allowing data assimilation and ensemble prediction system. Ensembles are developed using various methods of perturbations to simulate a long-lived and high-precipitation LES event in December 2013, and forecast performance is evaluated using observations including those from the Ontario Winter Lake-Effect Systems (OWLeS) campaign. Model lateral boundary conditions corresponding to weather conditions beyond the Great Lakes region play an influential role in LES precipitation forecasts and their uncertainty, as evidenced by ensemble spread, particularly at lead times beyond one day. A strong forecast dependence on regional initial conditions was shown using data assimilation. This sensitivity impacts the timing and intensity of predicted precipitation, as well as band location and orientation assessed with an object-based verification approach, giving insight into the time scales of practical predictability of LES. Overall, an assimilation-cycling convection-allowing ensemble prediction system could improve future lake-effect snow precipitation forecasts and analyses and can help quantify and understand sources of forecast uncertainty.

scholarly journals Simulation of Heavy Lake-Effect Snowstorms across the Great Lakes Basin by RegCM4: Synoptic Climatology and Variability*,+

2013 ◽  
Vol 141 (6) ◽  
pp. 1990-2014 ◽  
Author(s):  
Michael Notaro ◽  
Azar Zarrin ◽  
Steve Vavrus ◽  
Val Bennington
Keyword(s):  
Great Lakes ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Cover ◽  
Synoptic Climatology ◽  
Great Lakes Basin ◽  
Lake Ice ◽  
Lake Effect ◽  
Lake Ice Cover

Abstract A historical simulation (1976–2002) of the Abdus Salam International Centre for Theoretical Physics Regional Climate Model, version 4 (ICTP RegCM4), coupled to a one-dimensional lake model, is validated against observed lake ice cover and snowfall across the Great Lakes Basin. The model reproduces the broad temporal and spatial features of both variables in terms of spatial distribution, seasonal cycle, and interannual variability, including climatological characteristics of lake-effect snowfall, although the simulated ice cover is overly extensive largely due to the absence of lake circulations. A definition is introduced for identifying heavy lake-effect snowstorms in regional climate model output for all grid cells in the Great Lakes Basin, using criteria based on location, wind direction, lake ice cover, and snowfall. Simulated heavy lake-effect snowstorms occur most frequently downwind of the Great Lakes, particularly to the east of Lake Ontario and to the east and south of Lake Superior, and are most frequent in December–January. The mechanism for these events is attributed to an anticyclone over the central United States and related cold-air outbreak for areas downwind of Lakes Ontario and Erie, in contrast to a nearby cyclone over the Great Lakes Basin and associated cold front for areas downwind of Lakes Superior, Huron, and Michigan.

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