Though, it is obvious that the above settings are not optimal ones for many of the investigated sites, for the sake of simplicity, these were used for all of the 109 locations.Nutrient stresses were switched off during the simulations. Cumulative evapotranspiration, yield as well as biomass outputs obtained with measured and estimated radiation were compared using R2, RMSE, high throughput screening the mean relative error (MRE), and paired t-test results. A study of [31] on the sensitivity of crop models to the inaccuracies of meteorological observations showed that the uncertainty caused by the systematic errors of the measured global radiation can be up to 10% relative error for the calculated yield. This threshold (acceptance limit) was used for deciding whether the radiation estimation is acceptable for the crop model or not.

If the difference between the model results obtained by using estimated radiation and the ones obtained by using measured radiation is less than 10%, the radiation estimation was said to be acceptable.2.5. Extend the Estimations for Sites without Radiation MeasurementFurther simplification of the 0-2-1-4 version (Table 1) of the S-shape method, (13) was investigated for a subset of the database of the 109 stations covering an area of about 1,000,000km2 in the central part of the US mainland between the Rocky Mountains and the Appalachian Mountains (Figure 2).Figure 2Location of the 20 and 10 stations in the central territory of the USA whose data were used for calibrating and validating the S-shape method. Squares and triangles denote the calibration and validation sites, +f?cos??(i?4��365)+g?sin??(i?4��365).

(15)Data?respectively.Rs=Ra?��?(1?1?a1+(b?��T)2.285)?(1+c?R)?Fs,(13)��=0.00591?��Tavg+0.6758,(14)Fs=1+d?cos??(i?2��365)+e?sin??(i?2��365) of 20 stations were used for model calibration (Figure 2). The parameters a�Cg in (13) were determined by site specific parameterization. Since the coefficient of variation (CV) of parameters a, b, c, and d was relatively low (ranging between 6.7 and 16.9%), these parameters were approximated by their simple means. The rest of the parameters (CV = 28.5 ? 104.7%) were correlated to the geographical data (latitude, altitude) and meteorological metadata (average temperature, average diurnal temperature difference, and average annual precipitation) of the stations as it was proposed by [2]. The 0-2-1-4 version of the S-shape method calibrated with the previously introduced procedure was then validated using the data of 10 stations (Figure 1). The performance of this version of the S-shape method (having zero parameters to be determined by site-specific parameterization) was compared to those of the DC, DB, HKS, and LS models using the introduced error Dacomitinib indicators.