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Understanding Coupling of Global and...

Hamdan, Lubna.

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Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability./
作者:	Hamdan, Lubna.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	115 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
Contained By:	Dissertation Abstracts International77-10B(E).
標題:	Industrial engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10110172
ISBN:	9781339734323

Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability.
Hamdan, Lubna.

Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 115 p.

Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.

Thesis (Ph.D.)--West Virginia University, 2016.

Global solar radiation data is very important for wide variety of applications and scientific studies. However, this data is not readily available because of the cost of measuring equipment and the tedious maintenance and calibration requirements. Wide variety of models have been introduced by researchers to estimate and/or predict the global solar radiations and its components (direct and diffuse radiation) using other readily obtainable atmospheric parameters. The goal of this research is to understand the coupling of global and diffuse solar radiation with climatic variability, by investigating the relationships between these radiations and atmospheric parameters. For this purpose, we applied multilinear regression analysis on the data of National Solar Radiation Database 1991--2010 Update.

ISBN: 9781339734323Subjects--Topical Terms:

526216
Industrial engineering.

Understanding Coupling of Global and Diffuse Solar Radiation with Climatic Variability.
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500 $a Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
500 $a Advisers: Majid Jaridi; Antarpreet Jutla.
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520 $a Global solar radiation data is very important for wide variety of applications and scientific studies. However, this data is not readily available because of the cost of measuring equipment and the tedious maintenance and calibration requirements. Wide variety of models have been introduced by researchers to estimate and/or predict the global solar radiations and its components (direct and diffuse radiation) using other readily obtainable atmospheric parameters. The goal of this research is to understand the coupling of global and diffuse solar radiation with climatic variability, by investigating the relationships between these radiations and atmospheric parameters. For this purpose, we applied multilinear regression analysis on the data of National Solar Radiation Database 1991--2010 Update.
520 $a The analysis showed that the main atmospheric parameters that affect the amount of global radiation received on earth's surface are cloud cover and relative humidity. Global radiation correlates negatively with both variables. Linear models are excellent approximations for the relationship between atmospheric parameters and global radiation. A linear model with the predictors total cloud cover, relative humidity, and extraterrestrial radiation is able to explain around 98% of the variability in global radiation.
520 $a For diffuse radiation, the analysis showed that the main atmospheric parameters that affect the amount received on earth's surface are cloud cover and aerosol optical depth. Diffuse radiation correlates positively with both variables. Linear models are very good approximations for the relationship between atmospheric parameters and diffuse radiation. A linear model with the predictors total cloud cover, aerosol optical depth, and extraterrestrial radiation is able to explain around 91% of the variability in diffuse radiation. Prediction analysis showed that the linear models we fitted were able to predict diffuse radiation with efficiency of test adjusted R2 values equal to 0.93, using the data of total cloud cover, aerosol optical depth, relative humidity and extraterrestrial radiation. However, for prediction purposes, using nonlinear terms or nonlinear models might enhance the prediction of diffuse radiation.
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