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

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.

Author(s):  
D. O. Akpootu ◽  
B. I. Tijjani ◽  
U. M. Gana

In this study, time series statistical analysis was carried out on the monthly average daily meteorological parameters of global solar radiation, sunshine hours, wind speed, mean temperature, rainfall, cloud cover and relative humidity during the period of thirty one years (1980 – 2010) using IBM SPSS Statistics version 20 with expert modeler to determine the level, trend and seasonal variations for Ogoja and Maiduguri. Seasonal Auto Regressive Integrated Moving Average models were determined for the two locations along with their respective statistical indicators of coefficient of determination, Root Mean Square Error, Mean Absolute Percentage Error and Mean Absolute Error and are found suitable for one step ahead forecast for the studied area. The factor analysis (empirical orthogonal transformation) and descriptive statistical analysis was also carried out for the study areas under investigation. The results indicated that the model type for all the meteorological parameters for Ogoja is simple seasonal while that for Maiduguri is simple seasonal except for rainfall and cloud cover with winter’s additive and ARIMA models respectively. The correlation matrix obtained from the factor analysis for the studied area indicated that the global solar radiation and wind speed are more correlated with the mean temperature. The sunshine hours and mean temperature are more correlated with the global solar radiation. The rainfall is more correlated with the relative humidity; similarly, the relative humidity is more correlated with the rainfall. However, the cloud cover is more correlated to the rainfall for Ogoja while for Maiduguri the cloud cover is more correlated to the relative humidity. The component matrix analysis revealed that two seasons are identified for Ogoja; the rainy and dry seasons while for Maiduguri three seasons are identified; the rainy, cool dry (harmattan) and hot dry seasons. The skewness and kurtosis test for Ogoja indicated that the global solar radiation, sunshine hours, cloud cover and relative humidity are negatively skewed and the wind speed, mean temperature and rainfall are positively skewed while the global solar radiation, sunshine hours, wind speed, cloud cover and relative humidity indicates possibility of a leptokurtic distribution and the mean temperature and rainfall indicates possibility of a platykurtic distribution. The skewness and kurtosis for Maiduguri indicated that the solar radiation, rainfall and relative humidity are positively skewed and the sunshine hours, wind speed, mean temperature and cloud cover are negatively skewed while the global solar radiation, rainfall and cloud cover indicates possibility of a leptokurtic distribution and the sunshine hours, wind speed, mean temperature and relative humidity indicates possibility of a platykurtic distribution.


2015 ◽  
Vol 52 ◽  
pp. 1869-1880 ◽  
Author(s):  
Milan Despotovic ◽  
Vladimir Nedic ◽  
Danijela Despotovic ◽  
Slobodan Cvetanovic

2021 ◽  
Vol 9 (2) ◽  
Author(s):  
Mohammed Ali Jallal ◽  
◽  
Samira Chabaa ◽  
Abdelouhab Zeroual ◽  
◽  
...  

Precise global solar radiation (GSR) measurements in a given location are very essential for designing and supervising solar energy systems. In the case of rarity or absence of these measurements, it is important to have a theoretical or empirical model to compute the GSR values. Therefore, the main goal of this work is to offer, to designers and engineers of solar energy systems, an appropriate and accurate way to predict the half-hour global solar radiation (HHGSR) time series from some available meteorological parameters (relative humidity, air temperature, wind speed, precipitation, and acquisition time vector in half-hour scale). For that purpose, two intelligent models are developed: the first one is a multivariate dynamic neural network with feedback connection, and the second is a multivariate static neural network. The database used to build these models was recorded in Agdal’s meteorological station in Marrakesh, Morocco, during the years of 2013 and 2014, and it was divided into two subsets. The first subset is used for training and validating the models, and the second subset is used for testing the efficiency and the robustness of the developed models. The obtained results, in terms of the statistical performance indicators, demonstrate the efficiency of the developed forecasting models to accurately predict the HHGSR parameter in the city of Marrakesh, Morocco.


The Batuk ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 72-80
Author(s):  
Prakash M. Shrestha ◽  
Khem N. Poudyal ◽  
Narayan P. Chapagain ◽  
Indra B. Karki

Solar radiation data are great significance for solar energy systems. This study aimed to estimate monthly and seasonal average daily global solar radiation on a horizontal surface in Kathmandu (27.7oN, 85.5oE, 1350 masl), Nepal, by using CMP6 pyranometer in 2012. The influence of the global solar irradiation from different physical as well as meteorological parameters was analyzed. Besides this, the research highlighted that there is high level of fluctuation of the measured value of global solar irradiance due to local weather conditions. As a result of this measurement, the maximum, minimum monthly and yearly mean solar radiation values were (21.32 ± 4.14) MJ/m2/day in May,(10.93 ± 2.03) MJ/m2/day in January and (16.68 ± 4.60)MJ/m2/day found respectively. Annual average of clearness index, maximum temperature, minimum temperature, relative sunshine hour, air mass are 0.51 ± 0.12, (26.23 ± 4.96)oC, (12.38 ± 6.83)oC, 0.57 ± 0.165 and 1.54 ± 0.42 respectively. There is positive correlation of maximum temperature and negative correlation of air mass with global solar radiation.


2020 ◽  
pp. 45-52
Author(s):  
Prakash M. Shrestha ◽  
Jeevan Regmi ◽  
Usha Joshi ◽  
Khem N. Poudyal ◽  
Narayan P. Chapagain ◽  
...  

Solar radiation data are of great significance for solar energy systems. This study aimed to estimate monthly and seasonal average of daily global solar radiation on a horizontal surface in Pokhara (Lat.:28.21o N, Long.: 84o E and alt. 827 m above sea level), Nepal, by using CMP6 pyranometer in 2015. As a result of this measurement, monthly and yearly mean solar radiation values were 20.37 ±5.62 MJ/m2/ day in May, 11.37 ± 2.38 MJ/m2/ day in December and 16.82 ±5.24 MJ/m2/ day respectively. Annual average of clearness index and extinction coefficient are 0.51±0.14 and 0.53±0.31 respectively. There is positive correlation of maximum temperature and negative correlation of with global solar radiation.


Author(s):  
D. O. Akpootu ◽  
B. I. Tijjani ◽  
U. M. Gana

Time series and empirical orthogonal transformation analysis was carried out for four (4) selected tropical sites, which are situated across the four different climatic zones, viz. Sahelian, Midland, Guinea savannah and Coastal region in Nigeria using measured monthly average daily global solar radiation, maximum and minimum temperatures, sunshine hours, rainfall, wind speed, cloud cover and relative humidity meteorological data during the period of thirty one years (1980-2010). Seasonal Auto Regressive Integrated Moving Average (ARIMA) models were developed along with their respective statistical indicators of coefficient of determination (R2), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). The results indicated that the models were found suitable for one step ahead global solar radiation forecast for the studied locations. Furthermore, the results of the time series analysis revealed that the model type for all the meteorological parameters show a combination of simple seasonal with one or more of either ARIMA, winter’s additive and winter’s multiplicative with the level been more significant as compared to the trend and seasonal variations for the exponential smoothing model parameters in all the locations. The results of the correlation matrix revealed that the global solar radiation is more correlated to the mean temperature except for Akure where it is more correlated to the sunshine hours; the mean temperature is more correlated to the global solar radiation; the rainfall is more correlated to the relative humidity and the relative humidity is more correlated to the rainfall in all the locations. The results of the component matrix revealed that three seasons are identified in Nguru located in the Sahelian region namely, the rainy, the cool dry (harmattan) and the hot dry seasons while in Zaria, Makurdi and Akure located in the Midland, Guinea savannah and Coastal zones two distinct seasons are identified namely, the rainy and dry seasons.


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