The effect of data filtering on turbulence integral scales for bora flows

Abstract

Integralna skala turbulencije važna je varijabla u teoriji turbulencije, kao i u numeričkim prognostičkim modelima. Ona je dobar pokazatelj veličine vrtloga koji dominiraju turbulentnim spektrom. Integralne skale određuju se iz mjerenja brzine vjetra koristeći autokorelacijsku funkciju (ACF) i Fourierov spektar. Omjer skala dobivenih na ta dva načina bi trebao u teoriji biti konstantan. Vrijednosti dobivene na oba načina izrazito su osjetljive na filtriranje podataka, što je u praksi prvi korak u analizi atmosferske turbulencije. Podaci korišteni u ovom radu dobiveni su mjerenjima na tornju blizu Masleničkog mosta, sjeverno od Zadra, frekvencijom uzorkovanja od 20 Hz. Za razdoblje od 9. listopada 2015. do 9. listopada 2016. izdvojeno je 48 epizoda bure, jakog i mahovitog vjetra čije su mikroskalne karakteristike još uvijek nedovoljno istražene. Glavni ciljevi ovog diplomskog rada su proučiti utjecaj filtriranja na integralne skale turbulencije bure, dobivene preko ACF-a i Fourierovog spektra, utjecaj na njihov omjer i eventualno utvrditi prikladan period visokopropusnog (HP) filtriranja. Rezultati pokazuju da integralne skale dobivene filtriranim podacima perioda filtriranja bliskima skali usrednjavanja (30 min) nisu značajno osjetljive na filtriranje. Kod kraćih perioda filtriranja bolje je koristiti integralnu skalu dobivenu preko Fourierovog spektra. S obzirom na to da je omjer relativno očuvan u odnosu na duljinu filtera, teško je reći treba li sirove podatke filtrirati ili ne.Integral scale is an important variable in the theory of turbulence and in numerical weather prediction models. It is a good indicator of the size of the eddies that dominate the turbulence spectrum. Integral scales are estimated from the atmospheric wind speed measurements using autocorrelation functions (ACF) and Fourier spectrum. In theory, their ratio should be a constant. However, the values of integral scales obtained from ACF and Fourier spectrum are very sensitive to data filtering, which is in practice a first step in the analysis of the atmospheric turbulence in general. The measurements that were used were performed on a micrometeorological tower installed near the Maslenica Bridge north of the city of Zadar with a sampling frequency of 20 Hz. For the period from October 9, 2015 to October 9, 2016, 48 events of bora flow were abstracted. Bora is a strong, gusty wind, whose microscale characteristics are not fully explored yet. The main objectives of this work are to examine the effect of data filtering on integral scale values for bora flows, obtained from ACF and from Fourier spectrum, the effect on their ratio and to try to find out a suitable high-pass filter period. The results show that integral scales obtained by the filtered data using filter periods close to averaging time scale (30 min) are not significantly sensitive to filtering. When using shorter filter periods, it is better to estimate integral scales from Fourier spectrum. Given that the ratio is relatively conserved over the length of the filter, it is difficult to say whether the raw data should be filtered or not