Estimating Solar Irradiance for Crop Modeling Using Daily Air Temperature Data

Abstract

stricting their application in retrospective or validation studies (Hutchinson, 1991). Crop growth models require solar irradiance as input data, yetThe need for solar irradiance data for crop models there are few places where such data are routinely measured. For has led researchers to develop a number of methods for locations where measured values are not available, solar irradiance simulating such data. For example, some crop modelers can be estimated using empirical models such as the Bristow-(e.g., Rosenthal et al., 1989) have incorporated stochas-Campbell (B-C) model. This study was conducted to assess the spatial and seasonal accuracy of the B-C model for midcontinental locations tic weather generators into their simulations. These in Kansas. A 30-year data set from Manhattan, KS, was used to weather generators simulate irradiance and other metecalibrate and evaluate unmodified and modified forms of the B-C orological and climatological inputs based on probabilismodel. The effect of seasonality was investigated by subdividing the tic criteria. This approach eliminates the need for meayearly data into two subsets, a high noontime solar elevation angle sured solar irradiance; however, it seems reasonable period, ranging from DOY 121 to 273, and a low noontime elevation that estimated, rather than randomly generated, solar angle period comprising the remainder of the year. The B-C model irradiance values would also result in improved yield eswas also evaluated without seasonal division of the year. The calitimates. brated models were then tested against measured solar irradiance A number of techniques are available for estimating values for 10 sites distributed across the state of Kansas. Results solar irradiance. These vary in sophistication from simindicate that, for the calibration site at Manhattan, irradiance was ple empirical formulations based on common weather more accurately estimated using a modified form of the B-C model. For the yearly data, root mean square error (RMSE) was 3.9 MJ m Ϫ2 or climate data to complex radiative transfer schemes d Ϫ1 (25% error), compared with 5.2 MJ m Ϫ2 d Ϫ1 (24% error) for the that explicitly model the absorption and scattering of high solar elevation angle period and 3.6 MJ m Ϫ2 d Ϫ1 (32% error) the solar beam as it passes through the atmosphere. for the low solar elevation angle period. The RMSE for the 10 test Hall, Kansas State University, Manhattan, KS 66506-0801; R.L. Vanwhere A, B, and C are empirical coefficients. Although derlip,

Global radiation by simplified models for the state of Mato Grosso, Brazil

“…Figure 2 shows the correlation behavior of these two models at the weather station of the municipality of Sinop. In this case, due to temporal partition, these values were lower than those found by Goodin (1999) in the United States and by Silva et al (2012) under the climatic conditions of the state of Minas Gerais, but were similar to those reported by Liu et al (2009) and Almorox et al (2011) under the climatic conditions of China and Spain, respectively.…”

“…The best statistical performance in estimating the global radiation for the state of Mato Grosso, Brazil, is obtained by the Bristow & Campbell (1984) and Goodin et al (1999) models.…”

“…In this case, 1 is attributed to the best model and 15 to the worst one. Models: ABS, Abraha & Savage ( Donatelli & Campbell (1998); GOO, Goodin et al (1999); HAR, Hargreaves (1981); HU1, Hunt et al (1998); HU2, Hunt et al (1998); MAH, Mahmood & Hubbard (2002); MEV, Meza & Varas (2000); and THR, Thornton & Running (1999). Table 6.…”

Temperature-based solar radiation models for use in simulated soybean potential yield

“…Although empirically derived and conceptually simple, air temperature-based empirical models are founded on theoretical concepts for energy exchange on the surface boundary layer (Goodin et al, 1999). These models are based on the assumptions that (a) clear skies will increase the daily maximum temperature because of the greater short wave radiation input, while resulting in decreased minimum air temperature due to reduced long wave emission from the atmosphere; and (b) cloudy conditions will decrease the daily maximum air temperature due to reduced air transmissivity, while resulting in increased minimum air temperature due to increased long wave radiation from the clouds (Allen, 1997;Donatelli and Campbell, 1998;Almorox et al, 2013).…”

Assessment of reference evapotranspiration and global solar radiation in Yucatán Peninsula Mexico

“…These methods are based on empirical modelling related to variables such as temperature Bristow and Campbell, 1984;Donatelli and Campbell, 1998;Goodin et al,1999;Mahmood and Hubbard, 2002;Benghanem and Mellit, 2014), sunshine duration ( Angstrom, 1924;Prescott, 1940;Al-Mostafa et al, 2014;Despotovic et al, 2015;Lockart et al, 2015;Teke et al, 2015), rainfall ( McCaskill, 1990;Liu and Scott, 2001;Chen et al, 2006;Wu et al, 2007;Kirmani et al, 2015), cloudiness ( Supit and van Kappel, 1998;Gu et al, 2001;Badescu, 2002), elevation (Allen, 1995;Winslow et al, 2001;Annandale et al, 2002), humidity (Gu et al, 2001;Chen et al, 2006;Almorox et al, 2011;Li et al, 2013;Antonanzas-Torres et al, 2013;Li et al, 2015) and latitude (Toğrul and Onat, 1999;Skeiker, 2006). Several studies have shown that the best performing models use sunshine duration data, followed by those utilizing cloudiness and then temperature data (Bakirci, 2009;Chen and Li, 2013).…”