Development of a model for the estimation of photosynthetically active radiation from geostationary satellite data in a tropical environment

Observing and understanding the Southeast Asian aerosol system by remote sensing: An initial review and analysis for the Seven Southeast Asian Studies (7SEAS) program

“…We fully acknowledge that many other algorithms exist and are applied to the region; these include for AVHRR, the Global Aerosol Climatology Project (GACP) product of Mishchenko et al (1999), the Indian AVHRR products of Hashim et al (2004) and Parameswaran et al (2004), and a large collection of ocean sensor products as outlined by Myhre et al (2004Myhre et al ( , 2005a. There has been sporadic use of geostationary data as well (e.g., Janjai and Wattan, 2011).…”

Relationship between photosynthetically active radiation with global solar radiation using empirical model over selected climatic zones in Nigeria

“…PAR can also been estimated using irradiative transfer models [5], [12]. Notwithstanding, the accuracy of these latter methods is not good enough for large areas [13][14]. Another widely used method is to estimate PAR from the routinely measured global solar radiation (H) by considering the PAR fraction as a constant for a specific area [15][16].…”

Modeling and analysis of the spatiotemporal variations of photosynthetically active radiation in China during 1961–2012

“…PAR has to be estimated through either empirical/semiphysical methods or remote sensing techniques (e.g. [24,1]), for example, Van Laake and Sanchez-Azofeifa [37] proposed a method (PARcalc) for mapping instantaneous PAR from MODIS data based on radiative transfer equations, they further calculated the daily integrated PAR in Costa Rica and the average errors were 5-8% [38,27] mapped the incident PAR from MODIS data over China by matching the computed TOA (top of atmosphere) reflectance from a look-up table with the TOA values from the satellite observation; Janjai and Wattan [22] developed a model for estimating PAR from geostationary satellite in a tropical environment (Thailand) and the monthly average hourly root mean square error (RMSE) was about 9.8%; Leuchner et al [25] analyzed the spatial variability of PAR in European beech and Norway spruce; Qin et al [31] estimated the daily mean PAR at seven widely distributed Surface Radiation Budget Network (SUR-FRAD) stations around the world using relative sunshine data, and the RMSE was ranging from 6.03 to 6.83 W m À 2 ; Mizoguchi et al [30] estimated PAR using general meteorological elements at five sites in Japan and found that the RMSE was smaller than 5.2%. However, it was reported that many of many studies were focused on clear sky conditions (e.g.…”