Estimating soil temperatures and frost in the lake effect snowbelt region, Michigan, USA

Scott A. Isard, Randall J. Schaetzl

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

A physically-based computer model is developed for estimating soil temperatures at 0.05, 0.1, 0.2, and 0.5 m in sandy, forested soils, using only daily precipitation and minimum and maximum air temperatures as input data. The algorithm is evaluated by comparing its output to 490 soil temperature observations for 1990-1993 at 10 sites in Michigan, USA. The mean bias of the errors of the soil temperature estimates ranges from +0.6° to- .6°C, depending upon depth and season, thus comparing favorably to models requiring more detailed input. The model is applied to 14 stations across lower Michigan, using 1951-1991 US National Weather Service data, in order to examine regional trends in soil temperature and freezing and to compare these trends to patterns of snow thickness and air temperature. Simulations reveal that soils seldom freeze within the deep lake-effect snow belt of southern Michigan and along the coast of Lake Michigan. Soil freezing is more common at non-snowbelt, interior locations. Based on simulation data, new "potential freeze day" indices are presented that correlate better with annual minimum soil temperatures and "number of days frozen" than do other, more commonly used indices of freezing not specifically formulated for soils.

Original languageEnglish (US)
Pages (from-to)317-332
Number of pages16
JournalCold Regions Science and Technology
Volume23
Issue number4
DOIs
StatePublished - Aug 1995

Fingerprint

frost
soil temperature
Lakes
Soils
lake
freezing
Freezing
soil
Temperature
air temperature
snow
Snow
simulation
effect
Interiors (building)
weather
Air
coast
Coastal zones
trend

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Earth and Planetary Sciences(all)

Cite this

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abstract = "A physically-based computer model is developed for estimating soil temperatures at 0.05, 0.1, 0.2, and 0.5 m in sandy, forested soils, using only daily precipitation and minimum and maximum air temperatures as input data. The algorithm is evaluated by comparing its output to 490 soil temperature observations for 1990-1993 at 10 sites in Michigan, USA. The mean bias of the errors of the soil temperature estimates ranges from +0.6° to- .6°C, depending upon depth and season, thus comparing favorably to models requiring more detailed input. The model is applied to 14 stations across lower Michigan, using 1951-1991 US National Weather Service data, in order to examine regional trends in soil temperature and freezing and to compare these trends to patterns of snow thickness and air temperature. Simulations reveal that soils seldom freeze within the deep lake-effect snow belt of southern Michigan and along the coast of Lake Michigan. Soil freezing is more common at non-snowbelt, interior locations. Based on simulation data, new {"}potential freeze day{"} indices are presented that correlate better with annual minimum soil temperatures and {"}number of days frozen{"} than do other, more commonly used indices of freezing not specifically formulated for soils.",
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Estimating soil temperatures and frost in the lake effect snowbelt region, Michigan, USA. / Isard, Scott A.; Schaetzl, Randall J.

In: Cold Regions Science and Technology, Vol. 23, No. 4, 08.1995, p. 317-332.

Research output: Contribution to journalArticle

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