
Determining Regional Weather Patterns from a Historical Diary
Author(s) -
Jase Bernhardt
Publication year - 2015
Publication title -
weather, climate, and society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.014
H-Index - 35
eISSN - 1948-8335
pISSN - 1948-8327
DOI - 10.1175/wcas-d-15-0016.1
Subject(s) - covert , weather patterns , precipitation , geography , climatology , climate change , order (exchange) , meteorology , history , environmental science , ecology , philosophy , linguistics , finance , geology , economics , biology
Prior to the twentieth century, there was a dearth of official local weather and climate observations for much of the United States outside of major cities. Useful information can be gleaned, however, from primary accounts, such as historical diaries kept by farmers and others whose interests were tied to the land. Herman Smith, a farmer in west-central New York State, kept a detailed record of daily life, including weather characteristics such as temperature, precipitation, and wind, for his farm near Covert. Two full years of his diary, 1884 and 1886, were recently published and selected for study. Although typically not numeric data, the lexicon used in the diary to describe relative heat and cold allow Smith’s observations to be analyzed semiquantitatively in order to determine the weather experienced that year including factors affecting the growing season, as well as significant weather and climatic events. The analysis demonstrates that for Covert—located in an area of topographic variability and proximal to the Finger Lakes—microclimatic effects occasionally dominated over the synoptic circulation. This finding was further reinforced by comparison of Smith’s 1886 records with those of a nearby farmer. Meanwhile, Smith’s accounts also establish an inextricable link between his agricultural practices and the weather and climate patterns he observed. These findings underscore the value of acquiring climatic data from nonconventional sources for places and times when reliable data may be nonexistent in order to better understand how climate, and its impacts on the environment, have varied over time, across multiple scales.