Browsing by Author "Saenz, Jon"
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Item Analysis of atmospheric thermodynamics using the R package aiRthermo(Elsevier, 2019-01) Saenz, Jon; González-Rojí, Santos J.; Carreno-Madinabeitia, Sheila; Ibarra-Berastegi, GabrielThe publicly available R package aiRthermo is presented in this study, which allows the user to process information relative to atmospheric thermodynamics, ranging from calculating the density of dry or moist air and converting data between moisture indices to processing a full sounding, obtaining factors such as the convective available potential energy, additional instability indices, or adiabatic evolutions of particles. The package also provides the possibility to present information using customisable Stüve diagrams. Many of the functions are written inside a C extension to ensure that the computations are fast. The results of applying this package to five years of real soundings measured over the Iberian Peninsula are also presented as an example. The package considerably extends the capabilities of R to process atmospheric soundings or model results. This will be useful for many practical environmental forecasting applications at different scales, such as statistical downscaling for climate analysis, quantitative precipitation forecasting (particularly precipitation extremes), diagnosing storms, flash floods, and lightning, and in aviation and other fields where computing atmospheric convection and its related parameters is important.Item Calculation of Lebanon offshore wind energy potential using ERA5 reanalysis: impact of seasonal air density changes(IEEE. Institute of Electrical and Electronics Engineers Inc., 2019) Ibarra-Berastegi, Gabriel; Gonzalez-Roji, Santos J.; Ulazia, Alain; Carreno-Medinabeitia, Sheila; Saenz, JonIn this work, data from the ERA5 reanalysis (2010-2017) have been used to estimate the seasonal offshore wind energy potential for the Lebanese coast. Additionally, for this estimation, the effect of seasonal changes of air density has been incorporated. As a reference, the SIEMENS 160/6 turbine has been adopted and wind energy potential has been expressed as the capacity factor (CF) associated to this turbine. The spatial distribution of CF provides an idea of available wind energy potential in the Lebanese coast. The impact of seasonal air density changes has been assessed as percentage reduction in this indicator. In summer, the CF reduction due to high temperatures and lower air density, reaches in some Southern regions of the Lebanese coast to values around 5.5%. The use of such reanalyses is likely to increase in the future, thus making consultancy work easier since a lot of computational work with state-of-the-art meteorological models like WRF or MC2 (used to draw the National Wind Atlas of Lebanon) may not be necessary. Therefore, most likely in the future, for wind potential estimations, rather than heavy calculation efforts, the know-how for consultancy companies will focus into deeper analysis and interpretation of readily-available data from reanalyses.Item Seasonal Air Density Variations over The East of Scotland and The Consequences for Offshore Wind Energy(IEEE, 2018-12) Ulazia, Alain; Gonzalez-Roji, Santos J.; Ibarra-Berastegi, Gabriel; Carreno-Madinabeitia, Sheila; Saenz, Jon; Nafarrate, AnderIn this communication, offshore wind energy is studied around the East of Scotland, where, among other farms, the pioneering floating wind farm Hywind-Scotland is located. SIEMENS 160/6 turbines have been implemented in this farm, and we have thus used this turbine for our study. The main purpose is to compute the Capacity Factor (CF) changes due to air density variations in the study area. The impact of seasonal air density changes has been assessed as percentage reduction, but individual extreme cases have also been considered at Hywind-Scotland farm. Temperature, pressure, and wind speed data from the reanalysis ERA5 have been used for that. As a results, in winter, the CF increment due to low temperatures and denser air reaches values around 3% and summer-winter difference can reach the 4%, that is, 0.52 GWh of energy production for one SIEMENS 160/6.