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The Weibull probability distribution function using a long-term data source, consisting of 6 years (2005 2010) of 3-h period measured mean wind data, is adopted and analyzed.
Twenty one years of three-hourly mean wind data at 10-m height from the Nigeria meteorological department, Oshodi, Nigeria were assessed and subjected to Weibull two-parameter and other statistical analyses.
The Weibull probability distribution function is employed using a long-term data source consisting of 6 years (2005 2010) of 3-h period measured mean wind data, taken at a height of 10 m aboveground level.
This short communication extends the previous method for generating correlated synthetic mean wind data with a Rayleigh parent to the case where the parent can be a Forward Weibull distribution of arbitrarily chosen index with arbitrarily chosen auto-correlation.
The correlation between the different datasets at the tropics and zonal mean wind data at mid latitudes is examined for period February March 1993, when series of stratospheric warming events were observed at middle and high latitudes.
Four years of 10 min mean wind data from the offshore measuring platform FINO1 (Forschung in Nord-und Ostsee 1) in the German Bight have been analyzed to obtain the dependence of turbulence intensity on the wind speed.
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For the present purpose, we use the daily mean of zonal mean zonal wind data nearest to our observing station latitude (22.75°S) at 10 hPa pressure level (approximately 31 km) for the temporal span from January 1999 to December 2008.
The input data (hourly mean wind speed data of Tehran) is applied to the ANN-PSO hybrid algorithm.
It is a particularly good fit to mean wind speed data arising from a wind climate dominated by temperate depressions.
Ten-minute mean wind speed data recorded at 5 m above the sea level are used for present studies.
(e) Cross-correlations of each NS and EW component of the short-term velocity vectors with the daily mean wind velocity data recorded at Syowa Station.
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