Climatology of cold season lake‐effect cloud bands for the North American Great Lakes

Abstract

Geostationary Operational Environmental Satellite (GOES) visible imagery was used to identify lake‐effect (LE) clouds in the North American Great Lakes region for the cold seasons (October–March) of 1997/1998 through 2013/2014 to provide a comprehensive climatological description of the seasonal and interannual variability of LE cloud bands. During the average cold season, at least 60% of days each month had LE clouds over some portion of the Great Lakes region and nearly 75% of all LE days had LE clouds present over several lakes simultaneously. Wind‐parallel bands (WPB) are observed far more frequently than any other type of LE over Lakes Superior, Michigan, and Huron during the months of December, January, and February. Over Lake Erie, the occurrence of days per month with WPB was found to be approximately 5–10% greater than days with shore‐parallel bands (SPBs) throughout the entire cold season. The greatest frequency of SPB occurrences in the Great Lakes region was over Lake Ontario during the months of January and February (∼20% of days). In addition, Lake Ontario was the only lake where the frequencies of WPB and SPB occurrences were fairly similar each month. The annual frequency of WPB occurrences are the most variable among the Great Lakes, decreasing in frequency from the western lakes toward the eastern lakes. Lake Ontario has the largest annual frequency of SPB occurrences and the greatest variation in SPB annual frequency. Lake Huron has the second largest annual frequency of SPB days with small interannual variation. The primary differences of the annual frequency of lake‐to‐lake (L2L) LE occurrences when compared with previous research were a greater variability in the L2L annual frequency of Superior‐to‐Michigan connections, greater frequency of Michigan‐to‐Huron connections, and less frequent occurrences for Superior‐to‐Huron and Michigan‐to‐Erie connections.

On the frequency of lake-effect snowfall in the Catskill Mountains

“…For example, the winter of 2013-14 was a big snow year for western New York State, including the Catskill Mountains to the east. It was also a year with a high number of LE snowstorms (Laird et al, 2017). Our inspection of NEXRAD radar data for that winter corroborated this.…”

“…Use of satellite data to study LE snow in the Great Lakes has typically focused on studies of cloud cover (e.g., Ackerman et al, 2013;Laird et al, 2017). We employed a combination of data sources, including a time series of NOAA IMS 4km snow maps along with weather radar and precipitation maps.…”

The Cloud Top Distribution and Diurnal Variation of Clouds Over East Asia: Preliminary Results From Advanced Himawari Imager

“…MPH at low level rarely happens, except for Lake Baikal (Figure c, locates approximately at 108°E, 53°N), Bohai Bay (Figure d, 118°E, 33°N), and western parts of the Sea of Japan (Figure e, 128°E, 40°N). Clouds form above Lake Baikal may be associated with lake effects (e.g., Alcott et al, ; Laird et al, ). Conversely, there is no significant land‐ocean difference in low‐latitude regions (shown in Figures e and ).…”

Classification of Lake Michigan snow days for estimation of the lake‐effect contribution to the downward trend in November snowfall

“…Satellite (e.g., Kristovich & Steve, 1995; Laird et al, 2016) and radar‐based methods (e.g., Laird, Desrochers, & Payer, 2009) are valuable for identification of lake‐effect climatology, though the reduced temporal availability limits their efficacy for evaluating long‐term trends. Kristovich and Steve (1995) reported Lake Michigan lake‐effect clouds on 17% of November days during their study period, which is remarkably similar to the frequency of LE days herein, while Laird et al (2016) found a much greater frequency of lake‐effect cloud structures.…”

“…Although many studies have evaluated trends in Great Lakes snowfall, the lake‐effect contribution to the trend (when assessed) has been typically inferred from the spatial distribution (e.g., Bard & Kristovich, 2012; Clark et al, 2018) or by proxy (such as oxygen isotope data utilized in Burnett et al (2003)). The daily, event‐level attribution used herein provides a direct estimate of the lake‐effect trend contribution, informed by the lake‐effect snowfall paradigm based on decades of case studies (e.g., Peace & Sykes, 1966), climatology (e.g., Braham Jr & Dungey, 1995; Laird et al, 2016), forecasting (e.g., Niziol, 1987), numerical simulations and morphology (e.g., Hjelmfelt, 1990; Laird, Kristovich, & Walsh, 2003; Lavoie, 1972), and field campaigns (e.g., Kristovich et al, 2000). Given the favourable environment and spatial patterns of snowfall within this canon of research, a reasonable estimation of scaled‐up monthly or seasonal lake‐effect snowfall contributions should be feasible given daily or event‐level environmental characteristics and snowfall distribution.…”