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عنوان انگلیسی مقاله:
Models for estimating daily photosynthetically active radiation in oceanic and mediterranean climates and their improvement by site adaptation techniques
ترجمه فارسی عنوان مقاله:
مدل های تخمین روزانه اشعه فتوسنتزی فعال در آب و هوای اقیانوسی و مدیترانه و بهبود آنها توسط تکنیک های سازگاری سایت
Sciencedirect - Elsevier - Advances in Space Research, 65 (2020) 1894-1909. doi:10.1016/j.asr.2020.01.018
F. Ferrera-Cobos a,b,⇑, J.M. Vindel b, R.X. Valenzuela b, J.A. Gonza´lez c
In this work Photosynthetically Active Radiation (PAR) in oceanic and mediterranean climates is modeled. Twenty-two different
models have been developed and tested: eleven Multilinear Regression (MR) models and eleven Artificial Neuron Network (ANN) models,
using combinations of variables such as Global Horizontal Irradiance (GHI), Global Extraterrestrial Irradiance (G0), Temperature
(T) and Relative Humidity (RH). Data provided by Satellite Application Facility on Climate Monitoring (CM SAF) are used to develop
and train the models, while the models have been validated using field data from four stations located in Spain, covering the different
According to the results, zones with different climate conditions need different models, both for the case of MR and ANN. The results
show the need of including the GHI in all models in order to obtain accurate estimates; in fact, the presence of more variables only
improves slightly the results in mediterranean climate, while in oceanic climate no improvement is observed.
On the other hand, comparing MR and ANN models, ANN models did not show better results than those of MR models in no one of
the cases studied. Regarding the climate, both types of models are clearly better for the mediterranean case than for the oceanic one. In
order to improve the performance of the model for oceanic climate a correction based on the site adaptation technique was carried out.
The good results obtained by this technique fully justify its use.
The best proposed models provide better performance than other models which are restricted to certain locations. Besides, the clustering
technique based on the PAR variable, used in this work, allows obtaining useful models for a whole region. Finally, another
advantage of this methodology is that there is no need of ground measurements for its development, except for the site adaptation
Keywords: Photosynthetically active radiation | Site adaptation technique | Global horizontal irradiance | Artificial neuron network | Multilinear regression