1457 Enabling Comparison of Manual and Automated Observations for an Updated Climatology of Freezing Rain in the Great Lakes Region of North America

Wednesday, 25 January 2017
4E (Washington State Convention Center )
Matthew C. Irish, University of Michigan, Ann Arbor, MI; and W. Baule

Despite the expensive and deadly impacts that freezing rain (FZRA) events have had upon major population centers in the Great Lakes region of North America, little research has been devoted toward better understanding the spatial and temporal distribution of these events and their recent trends. This work presents instrumentation-related challenges in extending the most recent Great Lakes FZRA climatology, which focused on manual surface observations recorded from 1976-90, to analyze trends and strengthen conclusions by incorporating observations made through 2014. A central challenge in achieving this was to address continuity issues brought about by a transition from manual observation-making to the Automated Surveillance Observation System (ASOS) that began after 1990 and, later, the automated observations by sensitive new FZRA instruments that joined the ASOS suite in 2005. This complicated analysis that was already made difficult by the highly infrequent nature of FZRA events. Exhaustive filtering and quality control measures were taken to remove special observations and normalize the number of total yearly observations at each station. The resulting data showed close similarity to the earlier work for the period of time in which both studies overlap, and the entire 1976-2014 dataset appears to be robust.

While surface observations after the advent of automated freezing rain sensing were shown to have utility and be comparable to previous manual observations after careful filtering, work is ongoing to determine the changes in underlying synoptic-scale processes that are driving recent trends and the extent to which climate change may be playing a role.

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