Abstract
Crop growth models and other environmental analyses require the input of daily global solar radiation values. Unfortunately many locations lack long-term solar radiation data. Most agricultural experiment stations, however, have daily temperature records. Also they are often the locations for which crop growth simulations are conducted. In an unpublished manuscript in the field of agricultural meteorology, researchers wanted to address this need. Specifically they wanted to estimate historical daily global solar radiation using daily air temperature data records by adapting a single published empirical intrinsically nonlinear model, a form of the Weibull curve. In order to help future research in the given field, this paper argues that the selected model is a poor choice. Two independent long-term data sets that come from a similar climate to that of the researchers' are used, one for model development and the other for testing model prediction. Through the use of performance statistics on the cross-validation, three alternative models are offeredfor comparison (the performance statistics are accepted by researchers in the agricultural meteorology discipline). The results give no reason to favor the researchers' selected model. Furthermore no model performed well under advective conditions. Future research should consider finding a better means to account for advection, developing and evaluating other models, and justifying the assumptions of the methodology to be employed.
Keywords
Bristow-Campbell Model, Fox Statistics, cross-validation
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Meek, D. W.
(1998).
"DAILY SOLAR RADIATION ESTIMATED FROM TKMPERA TURE RECORDS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1282
DAILY SOLAR RADIATION ESTIMATED FROM TKMPERA TURE RECORDS
Crop growth models and other environmental analyses require the input of daily global solar radiation values. Unfortunately many locations lack long-term solar radiation data. Most agricultural experiment stations, however, have daily temperature records. Also they are often the locations for which crop growth simulations are conducted. In an unpublished manuscript in the field of agricultural meteorology, researchers wanted to address this need. Specifically they wanted to estimate historical daily global solar radiation using daily air temperature data records by adapting a single published empirical intrinsically nonlinear model, a form of the Weibull curve. In order to help future research in the given field, this paper argues that the selected model is a poor choice. Two independent long-term data sets that come from a similar climate to that of the researchers' are used, one for model development and the other for testing model prediction. Through the use of performance statistics on the cross-validation, three alternative models are offeredfor comparison (the performance statistics are accepted by researchers in the agricultural meteorology discipline). The results give no reason to favor the researchers' selected model. Furthermore no model performed well under advective conditions. Future research should consider finding a better means to account for advection, developing and evaluating other models, and justifying the assumptions of the methodology to be employed.