Comparison of three resistance methods for estimating heat flux under stable conditions

T. B. Ottoni, A. D. Matthias, A. F. Guerra, D. C. Slack

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14 Scopus citations

Abstract

Aerodynamic resistance to sensible heat transfer (rah) is an important parameter in bulk resistance models of energy exchange between the Earth's surface and the atmosphere. To estimate sensible heat flux density (H) over irrigated fields, it is often necessary to evaluate rah under stable atmospheric conditions. This is because irrigated fields are often cooler than air temperature as a result of net radiative cooling at night and advective influences. Sensible heat fluxes are generally small at night, but may become a relatively large component of the surface energy budget during advective conditions. The purpose of this paper was to compare H modeled for stable conditions over an extensive area of irrigated bermudagrass (Cynodon dactylon) cv. Midiron) using three rah methods from the literature, and to determine the sensitivities of the methods to the various parameter inputs. In addition to comparing modeled H values with each other, comparisons were made with H values measured by eddy correlation over the bermudagrass. The three methods studied were expressed as functions of the bulk Richardson number (RiB). The methods differ mainly in the stability correction function, and the added resistance term (kB-1, where k is von Kármán's constant and B-1 is a non-dimensional bulk parameter), which arises as a result of dissimilarities between heat and momentum transfer mechanisms near surface obstacles. Application of the methods to the bermudagrass data resulted in marked differences between the various modeled H values, and between modeled and measured H values. The modeled H values were more sensitive to surface emissivity and temperature inputs.

Original languageEnglish (US)
Pages (from-to)1-18
Number of pages18
JournalAgricultural and Forest Meteorology
Volume58
Issue number1-2
DOIs
StatePublished - Mar 1992

ASJC Scopus subject areas

  • Forestry
  • Global and Planetary Change
  • Agronomy and Crop Science
  • Atmospheric Science

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