Evaluating anemometer drift: A statistical approach to correct biases in wind speed measurement

Azorin-Molina, C. ; Asin, J. (Universidad de Zaragoza) ; McVicar, T.R. ; Minola, L. ; Lopez-Moreno, J.I. ; Vicente-Serrano, S.M. ; Chen, D.

Resumen: Recent studies on observed wind variability have revealed a decline (termed “stilling”) of near-surface wind speed during the last 30–50 years over many mid-latitude terrestrial regions, particularly in the Northern Hemisphere. The well-known impact of cup anemometer drift (i.e., wear on the bearings) on the observed weakening of wind speed has been mentioned as a potential contributor to the declining trend. However, to date, no research has quantified its contribution to stilling based on measurements, which is most likely due to lack of quantification of the ageing effect. In this study, a 3-year field experiment (2014–2016) with 10-minute paired wind speed measurements from one new and one malfunctioned (i.e., old bearings) SEAC SV5 cup anemometer which has been used by the Spanish Meteorological Agency in automatic weather stations since mid-1980s, was developed for assessing for the first time the role of anemometer drift on wind speed measurement. The results showed a statistical significant impact of anemometer drift on wind speed measurements, with the old anemometer measuring lower wind speeds than the new one. Biases show a marked temporal pattern and clear dependency on wind speed, with both weak and strong winds causing significant biases. This pioneering quantification of biases has allowed us to define two regression models that correct up to 37% of the artificial bias in wind speed due to measurement with an old anemometer.

Idioma: Inglés

DOI: 10.1016/j.atmosres.2017.12.010

Año: 2018

Publicado en: ATMOSPHERIC RESEARCH 203 (2018), 175-188
ISSN: 0169-8095

Factor impacto JCR: 4.114 (2018)

Categ. JCR: METEOROLOGY & ATMOSPHERIC SCIENCES rank: 13 / 86 = 0.151 (2018) - Q1 - T1

Factor impacto SCIMAGO: 1.464 - Atmospheric Science (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/Modelos Estocásticos
Financiación: info:eu-repo/grantAgreement/EC/H2020/703733/EU/Towards improved understanding of the worldwide decline of wind speed in a climate change scenario/STILLING

Tipo y forma: Article (Published version)

Área (Departamento): Área Estadís. Investig. Opera. (Dpto. Métodos Estadísticos)