Title of article :
Estimation of photosynthetically active radiation under cloudy conditions
Author/Authors :
I Alados، نويسنده , , F.J Olmo Reyes، نويسنده , , I. Foyo-Moreno، نويسنده , , L Alados-Arboledas، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2000
Abstract :
Clouds are the largest modulators of the solar radiative flux reaching the Earth’s surface. The amount and type of cloud cover prevailing at a given time and location largely determines the amount and type of solar radiation received at the Earth’s surface. This cloud radiative forcing is different for the different solar spectral bands. In this work, we analysed the influence of cloud radiative forcing over the photosynthetically active radiation. Knowledge of the photosynthetically active radiation is necessary in different applications, but due to the absence of widespread measurements of this radiometric flux, it must be estimated from available variables. Cloudless sky parametric models compute the global photosynthetically active radiation at surface level by addition of its direct beam and diffuse components. To compute this flux under all sky conditions one must consider the influence of clouds. This could be done by defining a cloud transmittance function. We have developed such a cloud transmittance function considering three different types of clouds. The efficacy of the cloud radiative forcing scheme has been tested in combination with a cloudless sky parametric model using independent data sets. For this purpose, data recorded at two radiometric stations are used. The combination of an appropriate cloudless sky parametric model with the cloud transmittance scheme provides estimates of photosynthetically active radiation with mean bias deviation about 4% that is close to experimental errors. Comparisons with similar formulations of the cloud radiative effect over the whole solar spectrum shows the spectral dependency of the cloud radiative effect.
Keywords :
Photosynthetically active radiation , Solar irradiance , Cloud radiative effect , Modelling , Estimation model , Parametric models
Journal title :
Agricultural and Forest Meteorology
Journal title :
Agricultural and Forest Meteorology