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A Spatial and Temporal Analysis of 30-Day Heavy Snowfall Amounts in the Eastern United States, 1900–2016
Author(s) -
David Chang
Publication year - 2018
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/jamc-d-17-0217.1
Subject(s) - snow , environmental science , climatology , period (music) , latitude , physical geography , geography , meteorology , geology , physics , geodesy , acoustics
Heavy 30-day snowfall amounts were evaluated to identify spatial and temporal characteristics east of the Rocky Mountains in the United States during the period 1900–2016. An extensive data assessment identified 507 stations for use in this long-term climate study. The top 30-day heavy snowfall amount and the average of the top five 30-day heavy snowfall amounts were examined. Both amounts generally increased with latitude; however, much higher amounts were found downwind of the Great Lakes, at higher elevations, or in locations impacted by topographic features (e.g., Rockies, Black Hills, and Appalachians). When compared with the 1981–2010 average winter snowfall, the top 30-day amount was found to be greater than the winter average in most areas of the eastern United States. The number of stations experiencing a top-five 30-day heavy snowfall period in a winter ranged from 1 to 128 (1959/60), with a greater overall occurrence in the second half of the 117-yr period. Six episodes had 10% or more stations experiencing one of the top five 30-day snowfall amounts, with the February–March 1960 episode impacting 124 stations, and these episodes were associated with large negative 500-hPa height anomalies. The northern Great Plains, Great Lakes, Midwest, and Northeast experienced more top-five periods in the second half of the 117-yr period, whereas most of the southern states experienced top-five periods throughout the study’s time frame. Examining extremes at periods beyond the daily event and less than the season contributes to our knowledge of climate and provides useful information to snow-sensitive sectors.