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Validation of an empirical model for photosynthetically active radiation
Author(s) -
Alados I.,
AladosArboledas L.
Publication year - 1999
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/(sici)1097-0088(199908)19:10<1145::aid-joc428>3.0.co;2-3
Subject(s) - photosynthetically active radiation , environmental science , flux (metallurgy) , irradiance , atmospheric sciences , mean squared error , meteorology , climatology , remote sensing , statistics , mathematics , geography , geology , physics , photosynthesis , botany , materials science , quantum mechanics , metallurgy , biology
Knowledge of the photosynthetically active radiation is necessary in different applications dealing with plant physiology, biomass production and natural illumination in greenhouses. Nevertheless, as a result of the absence of widespread measurements of this radiometric flux, it is often calculated as a constant ratio of the broadband solar radiation. This ratio is affected by many parameters. In a previous study, the authors analysed the global horizontal component of this flux. In this work, they validate the model against two independent data sets, one acquired at the same place where the previous model was developed and the other acquired at another location characterised by different climatic conditions. The first one is located at the University of Almería, a seashore location (36.83°N, 2.41°W, 20 m a.m.s.l.), while the second one is located at Granada (37.18°N, 3.58°W, 660 m a.m.s.l.), an inland location. The database includes hourly values of the relevant variables that cover the years 1993 and 1994 in Almería and 1994 and 1995 in Granada. The use of data sets registered in two different climatic conditions allows for the verification of the local independence of the proposed technique. The proposed models can provide estimates of the photosynthetically active radiation with negligible bias and root mean square deviations close to instrumental errors. Copyright © 1999 Royal Meteorological Society