估算光合有效辐射的全球经验模型综述

S. C. Nwokolo, S. O. Amadi
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引用次数: 13

摘要

在陆地光合作用、初级生产力计算、生态系统-大气二氧化碳、植物生理学、生物量生产、温室自然光照、辐射气候、植被遥感、植被冠层辐射制度、光合作用、植被生产力模型等方面,具备良好的光合有效辐射(PAR)知识是至关重要的。然而,在全球大多数感兴趣的地区,常规的PAR测量是不可用的。在过去的77年中,为了在每小时、每天和每月的平均基础上估计PAR,在全球许多地点开发了几个经验模型。因此,使用了大量的输入参数,并应用了不同的函数形式。本研究旨在对全球范围内用于估算PAR的经验模型进行分类和回顾。将目前使用的经验模型分为十大类,并根据所使用的输入参数进行介绍。将这些模型进一步划分为许多主要的子类(组),并根据它们的发展年份进行分类。总的来说,文献报道了757个经验模型,62个功能形式和32个类群用于估计全球PAR。将所采用的经验模型与采用不同人工神经网络(ANN)建立的模型进行比较;结果表明,人工神经网络模型更适合全球PAR的估计。因此,本综述将为太阳能研究人员提供迄今为止广泛使用的输入参数和功能形式,并认识到它们在全球PAR估计中的重要性。引文:Nwokolo, S. C. and Amadi, S. O.(2018)。估算光合有效辐射的全球经验模型综述。可再生能源发展趋势,4(2),236-327。DOI: 10.17737 / tre.2018.4.2.0079
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A Global Review of Empirical Models for Estimating Photosynthetically Active Radiation
A good working knowledge of photosynthetically active radiation (PAR) is of vital requirement for determining the terrestrial photosynthesis, primary productivity calculation, ecosystem-atmosphere carbon dioxide, plant physiology, biomass production, natural illumination in greenhouses, radiation climate, remote sensing of vegetation, and radiation regimes of plant canopy, photosynthesis, productivity models of vegetation, etc. However, routine measurement of PAR is not available in most location of interest across the globe. During the past 77 years in order to estimate PAR on hourly, daily and monthly mean basis, several empirical models have been developed for numerous locations globally. As a result, numerous input parameters have been utilized and different functional forms applied. This study was aim at classifying and reviewing the empirical models employed for estimating PAR across the globe. The empirical models so far utilized were classified into ten main categories and presented base on the input parameters applied. The models were further reclassified into numerous main sub-classes (groups) and finally presented according to their developing year. In general, 757 empirical models, 62 functional forms and 32 groups were reported in literature for estimating PAR across the globe. The empirical models utilized were equally compared with models developed using different artificial neural network (ANN); and the result revealed that ANN models are more suitable for estimating PAR across the globe. Thus, this review would provide solar energy researchers with input parameters and functional forms that have been widely used to up to date, and recognizing their importance in estimating PAR globally.  Citation:  Nwokolo, S. C., and Amadi, S. O. (2018). A Global Review of Empirical Models for Estimating Photosynthetically Active Radiation. Trends in Renewable Energy, 4(2), 236-327. DOI: 10.17737/tre.2018.4.2.0079
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