Implications of the OEN mixture model of the mean wind vector for the generation of synthetic timeseries and for the assessment of extremes.

This paper extends the results of the "fuzzy" OEN mixture model to estimate the probability densities, autocorrelations and spectra of the individual wind mechanisms within the mixed climates of Rome: Fiumicino and Ciampino, and discusses the implications for synthesising long-term simulation of the surface wind vector and for the assessment of extreme mean wind speeds. The paper confirms, from observations, that the strong diurnal effects observed at these locations are confined to a low range of wind speeds and do not significantly affect the extreme wind speeds for annual, or longer, epochs. A procedure is proposed to simulate exceptionally long timeseries of the mean wind vector from the OEN mixture model to examine convergence of the upper tail of the extreme wind speed distribution to the presumed asymptote. Every observation is assigned a fuzzy probability of belonging to each ellipse mechanism of the OEN model and sorted into nominally diurnal (sea-land breeze, transient coastal jet or nocturnal downslope wind) and nominally non-diurnal (pressure-driven geostrophic wind) sets. All the 200 largest independent daily-maximum 10-min mean wind speeds belong to the non-diurnal set. Diurnal variations have no significant effect on the distribution of annual maximum mean wind speeds. Key: All – All daily maxima. Hard D , Hard ND – Daily maxima of uncorrected Diurnal and Non-diurnal sets. Serial D , Serial ND – Independent maxima separated by at least 4 days of serially-corrected Diurnal and Non-diurnal sets.The paper presents the groundwork necessary to define a procedure to generate very long synthetic timeseries of wind speed and direction that correctly reproduce seasonal-diurnal variations. Image 1 • The fuzzy model extends to estimate the PDFs, ACFs and PSDFs of the OEN model components. • Diurnal variation is confined to low wind speeds and does not contribute to the annual maxima. • The OEN random perturbation PDFs can be represented by a hyperbolic probability distribution. • The OEN random perturbation PSDFs can be represented by a bandwidth-limited pink noise model. • The Harris (2014) simulation method is adapted to generate seasonal/diurnal timeseries of each OEN component. [ABSTRACT FROM AUTHOR]