Adventures with November Snowfall: Time Series, Synoptic Classification, and Modeling of Snow Days in the Lake Michigan Region

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Monday, 5 January 2015
Craig Clark, Valparaiso Univ., Valparaiso, IN; and A. Young, E. Delap, K. Heinlein, R. Connelly, A. Caruthers, A. VanDe Guchte, Z. Sefcovic, D. Koning, A. Carne, H. Boney, B. Ganesh-Babu, K. H. Goebbert, and S. Fingerle

A climatological data set of snowfall characteristics since 1950 was previously developed for the Lake Michigan region. Along with copious inter-annual variability, a clear feature of the evaluation is a marked decrease of November snowfall in recent decades. A similar decrease has not occurred during the core winter months, while the November change has been primarily driven by a decreased frequency of cold days. The change has been greater in the eastern and southeastern sub-regions, implying a diminution in the frequency of November lake-effect snowfall. However, snowfall data are vexed by data quality issues and even the adjudication of lake-effect and synoptic system contributions to snowfall is a challenge. The topic warrants additional exploration, with a focus of individual snow events.

Multifaceted investigations are evaluating the November days with reported snowfall since 1950. The center of the work is a synoptic climatology of each snow day, using a detailed classification system to delineate between snowfall from synoptic systems and lake-effect events. Complimentary projects include the analysis of composites with NCEP/NCAR Reanalysis data in order to glean statistical properties and WRF numerical simulations for additional case assessment and the development of a modeled climatology. These results will be summarized, along with implications regarding the relative changes of lake-effect and system snowfall coincident with the reduction in November snowfall.