Modeling photosynthetically active radiation: A review

Abstract

Photosynthetically active radiation (PAR) is important in applications related to plant physiology or the carbon cycle. However, despite its importance, a global network for its measurement has not yet been established. This work consists of the revision of a series of works related to the development of empirical models for the estimation of PAR in places where it is not regularly measured, using for this purpose measurements of meteorological and radiation parameters available in weather stations. A list of the models developed, the study site, the results obtained, and the nomenclature used in each of them is made. The most common way to develop empirical estimation models is by studying spatio-temporal changes in the relationship between PAR and global solar radiation. Other estimation methods include the use of satellite-derived products such as MODIS-derived products and the use of artificial neural networks. Despite being more efficient for estimating PAR, the use of artificial neural networks is not as widespread because its use is more complex than the development of empirical models. The PAR to global solar radiation ratio reached its maximum in the summer months and the minimum in the winter months; in addition, the daily values per hour reached their maximum at sunrise and sunset, and their minimum around noon.