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Different strategies for modeling Global Horizontal UltraViolet Erythemal irradiance ( G H U V E ) based on meteorological parameters measured in Burgos (Spain) have been developed. The experimental campaign ran from September 2020 to June 2022. The selection of relevant variables for modeling was based on Pearson's correlation coefficient. Multilinear Regression Model (M L R) and artificial neural network (A N N) techniques were employed to model G H U V E under different sky conditions (all skies, overcast, intermediate, and clear skies), classified according to the C I E standard on a 10 min basis. A N N models of G H U V E outperform those based on MLR according to the traditional statistical indices used in this study ( R 2 , M B E , and n R M S E ). Moreover, the work proposes a simple all-sky A N N model of G H U V E based on usually recorded variables at ground meteorological stations. [ABSTRACT FROM AUTHOR]

• Monthly IPAR is estimated for cereals in Castilla León using Beer Lambert's law. • Modeled PAR , satellite LAI , and bibliographic k data are used for calculations. • The methodology is applicable at different spatial and temporal scales. • The fIPAR estimate for wheat, barley and maize for the whole territory. • Average annual growth and yield patterns for large crop areas is determined. Agriculture is by far the most important economic activity in the Spanish autonomous region of Castilla y León. Numerous factors influence crop development but one of the most related variables to the photosynthetic process is Photosynthetically Active Radiation (PAR). Estimating Intercepted Photosynthetically Active Radiation (IPAR) in different crops through the Beer-Lambert law could be a relevant factor in crop season planning by enabling photosynthesis monitoring. The Beer-Lambert Law is applied in this study to the data for almost 2 million hectares of wheat, barley, and maize cultivated in Castilla y León in 2021. The fourteen-year data set of Global Horizontal Irradiance (GHI) used to calculate the monthly PAR data in the region was collected at 93 meteorological stations (46 in Castilla y León and 47 in neighboring Spanish and Portuguese regions). Two previously published global calibrated models were employed to calculate the PAR , with a relative Root Mean Square Error (rRMSE) below 6%, for the measured daily mean values of PAR in Burgos. Processing the various NASA Terra and Aqua satellite images yielded the monthly Leaf Area Index (LAI) and the literature review provided the light extinction coefficient (k). The Geographic Information System (GIS) facilitated visualization of IPAR estimates for the three cereal crops in all months of its growing season. Wheat and barley reach their IPAR peaks in June and July, while maize peaks in July and August. In addition, the fraction of Intercepted Photosynthetically Active Radiation (fIPAR) was calculated in different provinces to assess PAR interception for each cereal at different growing stages. In June, almost 50% of the wheat area in Burgos, Palencia and Soria displayed fIPAR values exceeding 45% while in the case of barley only the province of Burgos reached these percentages of area and. fIPAR. [ABSTRACT FROM AUTHOR]