The 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.

Arctic cyclones (ACs) are synoptic scale features that can be associated with strong, intense winds over the Arctic region for long periods of time, potentially leading to rapid declines of sea ice during the summer. As a consequence, sea ice predictions may rely on the predictability of cyclone-related wind speed and direction, which critically depends on the cyclone track and intensity. Despite this, there are relatively few studies that have documented the predictability of ACs during the summer, beyond a few case studies, nor has there been an extensive comparison of whether these cyclones are more or less predictable relative to comparable midlatitude cyclones, which have been studied in greater detail. The goal of this study is to document the practical predictability of AC position and intensity forecasts over 100 cases and compare it to 89 Atlantic basin midlatitude cyclones using the Global Ensemble Forecast System (GEFS) Reforecast V2. This dataset contains 11-member ensemble forecasts initialized daily from 1985-present using a fixed model. In this study, 1 and 3 day forecast hours are compared, where predictability is defined as the ensemble mean root mean square error and ensemble standard deviation (SD). Although Atlantic basin cyclone tracks are characterized by higher predictability relative to comparable ACs, intensity predictability is higher for ACs. In addition, storms characterized by low ensemble SD and predictability are found in regions of higher baroclinic instability than storms characterized by high predictability. There appears to be little, if any, relationship between latent heat release and precipitable water and predictability.