This works reports the quantification and forecasting of Cumulonimbus (Cb) clouds direction, nebulosity and occurrence with auto regression using 2018-2020 dataset from Yaoundé –Nsimalen of Cameroon. Data collected for October 2018-2020 consisted of 2232 hourly observations. Codes were written to automatically align, multi-find and replace data points in excel to facilitate treating big datasets. The approach included quantification of direction generating time series from data and determination of model orders using the correlogram. The coefficients of the SARIMA model were determined using Yule-Walker equations in matrix form, the Augmented Dickey Fuller test (ADF) was used to check for stationarity assumption, Portmanteau test to check for white noise in residuals and Shapiro-Wilk test to check normality assumptions. After writing several algorithms to test different models, an Autoregressive Neural Network (ANN) was fitted and used to predict the parameters over window of 2 weeks. Autocorrelation Function (ACF) shows no correlation between residuals, with p ≤ 0.05, fitting the stationarity assumption. Average performance is 80%. A stationary wavelike occurrence of the direction has been observed, with East as the most frequented sector. Forecast of Cb parameters is important in effective air traffic management, creating situational awareness and could serve as reference for future research. The method of decomposition could be made applicable in future research to quantify/forecast cloud directions.
In this study, the wind shear vector variability likely to mitigate the flights activities at the Cameroon Airport and in particular Garoua has been analyzed. This research is based on a statistical method R of pilot probe and observation synoptic station data, April–July 2021 period. The results show that Garoua Airport has recorded more than 55[Formula: see text]percent of the intensities of the wind shear vector greater than 10[Formula: see text]kt/100[Formula: see text]ft with dominant directions in the North-South sector. The intensities of the headwind/tailwind shear vector are at 60[Formula: see text]percent moderate; the probability density distribution shows 40[Formula: see text]percent strong to very strong shear with moderate to strong probability. This fact may represent a problem for lighter aircrafts, whose crosswind rates are lower. In this context, the forecast of high wind speed values and directions becomes very important. The schedule distribution of the various wind during this period displays that the most sheared month is the month of May, the sounding that presents the strongest to very strong shears is that of 5 p.m. and the most sheared slice is the ground surface layer where the frictional force has a very large impact on the wind. In addition, the convective system’s formation and the geographical discontinuities effects contributed to the recording of shear types during the period not only at ground level but also at the superior levels.
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