scholarly journals Study of Atmospheric Turbidity in a Northern Tropical Region Using Models and Measurements of Global Solar Radiation

2021 ◽  
Vol 13 (12) ◽  
pp. 2271
Author(s):  
Mohamed Zaiani ◽  
Abdanour Irbah ◽  
Djelloul Djafer ◽  
Constantino Listowski ◽  
Julien Delanoe ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Real Data ◽  
Global Solar Radiation ◽  
Temporal Variations ◽  
Radiative Properties ◽  
Tropical Region ◽  
Atmospheric Turbidity ◽  
Two Parameters ◽  
Sky Conditions ◽  
Terra Satellite

Radiative transfer in the Earth’s atmosphere under clear-sky conditions strongly depends on turbidity due to aerosols and hydrometeors. It is therefore important to know its temporal radiative properties for a given site when the objective is to optimize the solar energy that is collected there. Turbidity can be studied via measurements and models of the global solar radiation reaching the ground in cloudless conditions. These models generally depend on two parameters, namely the Angström turbidity coefficient and the Linke factor. This article aims to do a comparative study of five models of global solar radiation, all dependent on the Linke factor, based on real data. The measurements are provided by the Tamanrasset Meteorological Center (Algeria), which has a long series of global solar radiation data recorded between 2005 and 2011. Additional data from AERONET and MODIS onboard the TERRA satellite were also used to perform the comparison between the two estimated parameters and those obtained from AERONET. The study shows that the ESRA models are the most reliable among the five models for estimating the Linke factor with a correlation coefficient R of the data fits of 0.9995, a RMSE of 13.44 W/m2, a MBE of −0.64 W/m2 and a MAPE of 6.44%. The maximum and minimum statistical values were reached, respectively, in June and during the autumn months. The best correlation is also observed in the case of ESRA models between the Linke parameter and the joint optical thickness of aerosols and the total column-integrated water vapor. The Angström turbidity coefficient β, calculated from the Linke factor and MODIS data, has values less than 0.02 at 9% of the cases, and 76% present values ranging between 0.02 and 0.15 and 13% higher than 0.15. These β values are validated by AERONET measurements since a very good correlation (R≈0.87) is observed between the two datasets. The temporal variations of β also show a maximum in June. Satellite observations confirm more aerosols during the summer season, which are mostly related to the African monsoon.

scholarly journals Analysis of Measurements of Direct Normal and Global Solar Radiation for Maceió, Alagoas State, Northeastern Brazil

2020 ◽  
Vol 35 (4) ◽  
pp. 659-674
Author(s):  
José Marcelo Lopes Júnior ◽  
José Leonaldo de Souza ◽  
Ricardo Araujo Ferreira Junior ◽  
Cícero Manoel dos Santos ◽  
Gustavo Bastos Lyra ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Solar Irradiance ◽  
Cloud Cover ◽  
Global Solar Radiation ◽  
Northeastern Brazil ◽  
Human Knowledge ◽  
Clearness Index ◽  
Study Region ◽  
Maximum Value ◽  
Sky Conditions

Abstract Studying solar radiation is essential for human knowledge, since it is present in practically all its activities. Thus, the aim of this work was to analyze the climatic and seasonal variation of direct normal and global solar radiation in the region of Maceió, Alagoas State, Northeastern Brazil with sky conditions characterized by clearness index (Kt). The Kt was determined by the ratio between global solar irradiance and solar irradiance at the top of the atmosphere. The highest occurrences of daily direct normal solar irradiance under conditions of Kt ≥ 0.6 were recorded between 400 W m−2 and 700 W m−2 for all seasons. Under conditions of 0.4 ≤ Kt < 0.6, the daily direct normal solar irradiance occurred between 200 W m−2 and 500 W m−2 and for conditions of Kt < 0.4, its maximum value was 200 W m−2. It was observed that the levels of solar incidence in the study region depend on cloud cover conditions, with little influence of seasonality.

Modeling hourly and daily fractions of UV, PAR and NIR to global solar radiation under various sky conditions at Botucatu, Brazil

2009 ◽  
Vol 86 (3) ◽  
pp. 299-309 ◽  
Author(s):  
João F. Escobedo ◽  
Eduardo N. Gomes ◽  
Amauri P. Oliveira ◽  
Jacyra Soares
Keyword(s):  
Solar Radiation ◽  
Global Solar Radiation ◽  
Sky Conditions

Variability of aerosol extinction of solar radiation in Antarctica

1994 ◽  
Vol 6 (3) ◽  
pp. 419-424 ◽  
Author(s):  
V. F. Radionov
Keyword(s):  
Solar Radiation ◽  
Volcanic Activity ◽  
Considerable Increase ◽  
Temporal Variations ◽  
Stratospheric Aerosol ◽  
Aerosol Extinction ◽  
Mount Pinatubo ◽  
Atmospheric Turbidity ◽  
Aerosol Pollution ◽  
Using Data

Temporal variations of the aerosol optical depth and transmission coefficient of the atmosphere are considered using data from Mirny Observatory, Antarctica. Year-to-year variability of these parameters is determined mainly by stratospheric aerosol pollution due to volcanic activity. A considerable increase of atmospheric turbidity has been observed since the end of September 1991. This phenomenon seems to be associated with the Mount Pinatubo volcanic eruption.

scholarly journals Statistical Analysis for Prognosis of a Photochemical Smog Episode

2013 ◽  
Vol 9 (2) ◽  
pp. 20-24
Author(s):  
Camelia Gavrilă ◽  
Florinela Ardelean ◽  
Adriana Coman ◽  
Elena Burchiu
Keyword(s):  
Statistical Analysis ◽  
Solar Radiation ◽  
Prognostic Value ◽  
Meteorological Parameters ◽  
Real Data ◽  
Global Solar Radiation ◽  
Photochemical Smog ◽  
Climatic Parameters ◽  
Essential Information ◽  
Pollutant Concentrations

Abstract In this paper we describe the evaluation of various climatic parameters in establishing their prognostic value in a photochemical smog episode. Our application was validated using real data from the “Cercul Militar National” and “Sos. Mihai Bravu nr. 47-49”, from April 2008 to May 2008. The study was performed on hour averages of pollutant concentrations and meteorological parameters and the statistical analysis was based on multiple regressions. We concluded by using mathematical and statistical methods, [1], that an accurate Global Solar Radiation is one of the most important and essential information in the pollution report.

Estimation of Solar Potential for Thailand Using Adaptive Neurofuzzy Inference System Models

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Jirasuwankul Nirudh ◽  
Jiriwibhakorn Somchat
Keyword(s):  
Solar Radiation ◽  
Real Data ◽  
Ground Level ◽  
Energy System ◽  
Global Solar Radiation ◽  
Inference System ◽  
Average Accuracy ◽  
Artificial Neural Network Ann ◽  
Adaptive Neurofuzzy Inference System ◽  
Energy System Planning

This research paper proposes a new method of global solar radiation prediction for Thailand using adaptive neurofuzzy inference system (ANFIS) models. Contrary to mathematical-based modeling approaches, the proposed models are able to estimate the monthly mean of daily global solar radiation at the ground level without using the earth's atmospheric layer model. The proposed technique alternately utilizes the 9-year long recorded spatiotemporal data of solar irradiance from meteorological ground stations in the modeling process. With a limited number of ground stations, it covered six regions of Thailand, ANFIS modeling; testing and restructuring have been performed repetitively; and finally, the best-fit models with minimum mean absolute percentage errors (MAPEs) corresponding to six regions of Thailand are obtained. Moreover, the ANFIS models have been tested comparatively to the measured data and the multilayer feed forward artificial neural network (ANN) models, which has a good agreement to real data for the proposed models, can be met with the average accuracy of 7.07% MAPE. By applying this model as a tool to estimate solar potential, the local government or the business sector can provide basic information, which is useful for solar energy system planning and project development.

scholarly journals Assessment of Global Solar Radiation at Selected Points in Nigeria Using Artificial Neural Network Model (ANNM)

2019 ◽  
pp. 376-390 ◽  
Author(s):  
Ibeh Gabriel Friday ◽  
Bernadette Chidomnso Udochukwu ◽  
Tertsea Igbawua ◽  
Tyovenda Alaxander ◽  
Ofoma John Ndubuisi
Keyword(s):  
Transfer Function ◽  
Solar Radiation ◽  
Global Solar Radiation ◽  
Activation Function ◽  
Temporal Variations ◽  
Dry Season ◽  
Coefficient Of Determination ◽  
Wet Season ◽  
North West ◽  
North East

In this study, spatial distribution, temporal variations, annual distribution, estimation and prediction of solar radiation in Nigeria was carried out using ANNs. Levenberg-Marquardt backpropagation algorithms was used for the training of the network using solar radiation data along the years (1979-2014). The data records were divided into three portions (training, testing and validation). The network processed the available data by dividing it into three portions randomly: 70% for the training, 15% for validation and the remaining 15% for testing. Input parameters were chosen as latitude, longitude, day of the year, year while observed solar radiation was chosen as targeted data (from a processed file). The output parameter was the estimated solar radiation. The network designs were tested with root mean square error and then the most successful network (taken to be best network) which is network with less error was used to carry out the study. The hyperbolic tangent sigmoid transfer function was also used between the input and the hidden layers as activation function, while the linear transfer function was used from hidden layers to the output layer as the activation function. The performance of ANNs was validated by; estimating the difference between the annual measured and estimated values were determined using coefficient of determination (R2). Results revealed that the R2 result was 0.82 (82%). The result of spatial variations indicated that both wet and dry seasons have their highest concentration in North-East of Nigeria. It is pertinent to also note that the lowest concentration occurred in North-West during wet season, while the lowest occurred at the South-South and South-West of Nigeria in dry season. In addition, the lowest in dry season is about 25W/m2, while that of wet season is about 15W/m2. The agreement between the temporal and annual variation of observed and estimated solar radiation reveals that the model exhibits good performance in studying solar radiation. The model was further used to predict two years ahead of the years of study.

scholarly journals Chaotic Signatures and Global Solar Radiation model estimate over Nigeria, a Tropical region

2020 ◽  
Author(s):  
Adedayo Adelakun ◽  
Folasade Adelakun
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Temperature Difference ◽  
Solar Irradiance ◽  
Meteorological Parameters ◽  
Global Solar Radiation ◽  
Tropical Region ◽  
Radiation Model ◽  
Model Estimate ◽  
Solar Radiation Model

Abstract. In a tropical region like Nigeria, accurate estimation and chaotic signatures of global solar radiation (Rs) are essential to the design of solar energy utilization systems in PV technology companies and one of the plant growth determinants in Agriculture. The Rs model is a function of solar declination angle, temperature difference, and relative humidity. In this paper, the daily re-analyzed atmospheric data obtained from the archive of ERA-Interim was used to estimate the nonlinear Global Solar radiation model and investigated chaotic signatures across the tropical climatic regions of Nigeria. The well-known statistical tools were used to analyze the chosen meteorological parameters and the correlation was found to be perfect, close with low values of RMSE across the selected regions over Nigeria. For proper modeling and prediction of the underlying dynamics, the extensive chaotic measures of phase space reconstruction using recurrence plots and recurrence quantification analyses are also presented, analyzed and discussed with the appropriate choice of embedded dimension, m, and time delay τ. The radiant energy from the sun is one of the most available and renewable resources across the season in a tropical region like Nigeria. The information, therefore, suggests how vital the solar irradiance can be useful in Agriculture and Photovoltaic technology companies. Based on the scarcely gauged of global solar radiation (GSR) at meteorological stations in developing countries. This demand necessitates a better understanding of the underlying dynamics for better prediction mostly by the nonlinear Global Solar radiation model estimate and chaotic signature measurement. The optimum usage of meteorological parameters such as solar radiation, relative humidity and temperature difference needs further studies, using RPs and RQA measures. However, several data such as rainfall data, geomagnetic data, ionospheric data, wind speed data etc obtained from different parts of the world have been estimated with several models and applied to RQA measures for better prediction and modeling. Using RPs and RQA, features due to external effects such as harmattan and intertropical discontinuity (ITD) on solar radiation data in this tropical region were uniquely identified. Meanwhile, the inverse characteristic behavior of solar radiation and relative humidity were vividly maintained. The results show a very low value of RMSE while the value of R2 is very closed to 1, which depicts a good prediction for all locations. However, the highest values of both SSE and RMSE, as well as the lowest value of R2 were observed in kano station, which indicates high solar irradiance location. The RPs reviewed the observed clusters points around the parallel diagonal lines with short segments, which implies the presence of chaos. Additional complex measure, the RQA also shows that the solar radiation during the dry season of the months has lower values of Lmax, determinism and entropy, and higher values during the wet season of the months.

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