Net radiation dynamics: Performance of 20 daily net radiation models as related to model structure and intricacy in two climates

S. Irmak, D. Mutiibwa, J. O. Payero

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18 Scopus citations

Abstract

We compared daily net radiation (R n) estimates from 19 methods with the ASCE-EWRI R n estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI R n method, were then evaluated against R n data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (R nl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 R n methods with measured R n, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in R n and grass-and alfalfa-reference evapotranspiration (ET n and ET n) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using α = 0.19 instead of α = 0.23 resulted in 6% overestimation of R n. Using α = 0.19 instead of α = 0.23 for ET o and ET r estimations, the 6% difference in R n translated to only 4% and 3% differences in ET o and ET n respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI R n (r 2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m -2 d -1 between 12 methods and the ASCE-EWRI R n at Clay Center and between 14 methods and the ASCE-EWRI R n at Davis. The performance of some methods showed variations between the two climates. In general, r 2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic ε as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated R n values had one of the best agreements with the measured R n (r 2 = 0.93, RMSD = 1.44 MJ m -2 d-1), and estimates were within 7% of the measured R n. The R n estimates from six methods, including the ASCE-EWRI, were not significantly different from measured R n. Most methods underestimated measured R n by 6% to 23%. Some of the differences between measured and estimated R n were attributed to the poor estimation of R n1. We conducted sensitivity analyses to evaluate the effect of R n1 on R n, ET o, and ETr. The Rnl effect on R n was linear and strong, but its effect on ET o and ET r was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative R n data source for ET estimations when measured R n data over the reference surface are not available. In the absence of measured R n, another alternative would be using one of the R n models that we analyzed when all the input variables are not available to solve the ASCE-EWRI R n equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily R n in climates similar to Clay Center and Davis.

Original languageEnglish (US)
Pages (from-to)1059-1076
Number of pages18
JournalTransactions of the ASABE
Volume53
Issue number4
StatePublished - Jul 2010

All Science Journal Classification (ASJC) codes

  • Forestry
  • Food Science
  • Biomedical Engineering
  • Agronomy and Crop Science
  • Soil Science

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