Estimation of Hourly and Daily Global Solar Radiation at Clear Days Using an Approach Based on Modified Version of Gaussian Distribution

The performance of two models,Jam and Baig,based on the modified version of Gaussian distribution function in estimating the daily total of global solar radiation and its distribution through the hours of the day from sunrise to sunset al any clear day is evaluated with our own measured data in the period from June 1992 to May 1993 in Qena Egypt The results show a high relative deviation of calculated values from measured ones,especially for Jain model,in the most hours of the day,except for those near to local noon.This misfit behavior is quite obvious in the early morning and late afternoon A new approach has been proposed in this paper to estimate the daily and hourly global solar radiation This model performs with very high accuracy on the recorded data in our region.The validity of this approach was verified with new measurements in some clear days in June and August 1994.The resultant very low relative deviation of the calculated values of global solar radiation from the measured ones confirms the high performance of the approach proposed in this work

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses

Objective:To study the number of leptospirosis cases in relations to the seasonal pattern,and its association with climate factors.Methods:Time series analysis was used to study the time variations in the number of leptospirosis cases.The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. Results:We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest,namely the northern and northeastern region of Thailand,while the temperature played a role in the northeastern region only.The use of multivariate ARIMA(ARIMAX) model showed that factoring in rainfall(with an 8 months lag) yields the best model for the northern region while the model,which factors in rainfall(with a 10 months kg) and temperature(with an 8 months lag) was the best for the northeaslern region.Conclusions:The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions.The models can also be used to predict the next seasonal peak quite accurately.