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Dore, A.J., Vieno, M., Fournier, N., Weston, K.J. and Sutton, M.A. (2006) Development of a New Wind-Rose for the British Isles Using Radiosonde Data, and Application to an Atmospheric Transport Model. Quarterly Journal of the Royal Meteorological Society, 132, 2769-2784.
http://dx.doi.org/10.1256/qj.05.198

has been cited by the following article:

• TITLE: A Statistical Analysis of Wind Speed and Power Density Based on Weibull and Rayleigh Models of Jumla, Nepal

  AUTHORS: Ayush Parajuli

  KEYWORDS: Mean Wind Speed, Rayleigh Distribution, Weibull Distribution, Wind Power Density

  JOURNAL NAME: Energy and Power Engineering, Vol.8 No.7, August 24, 2016

  ABSTRACT: In the present study, wind speed data of Jumla, Nepal have been statistically analyzed. For this purpose, the daily averaged wind speed data for 10 year period (2004-2014: 2012 excluded) provided by Department of Hydrology and Meteorology (DHM) was analyzed to estimate wind power density. Wind speed as high as 18 m/s was recorded at height of 10 m. Annual mean wind speed was ascertained to be decreasing from 7.35 m/s in 2004 to 5.13 m/s in 2014 as a consequence of Global Climate Change. This is a subject of concern looking at government’s plan to harness wind energy. Monthly wind speed plot shows that the fastest wind speed is generally in month of June (Monsoon Season) and slowest in December/January (Winter Season). Results presented Weibull distribution to fit measured probability distribution better than the Rayleigh distribution for whole years in High altitude region of Nepal. Average value of wind power density based on mean and root mean cube seed approaches were 131.31 W/m2/year and 184.93 W/m2/year respectively indicating that Jumla stands in class III. Weibull distribution shows a good approximation for estimation of power density with maximum error of 3.68% when root mean cube speed is taken as reference.