An alternative approach to estimate any subdaily extreme of rainfall and wind from usually available records

Pérez-Bella, José M. (Universidad de Zaragoza) ; Domínguez-Hernández, Javier (Universidad de Zaragoza) ; Martínez-Martínez, Juan E. ; Alonso-Martínez, Mar ; Coz-Díaz, Juan J.

Resumen: A wide variety of engineering applications requires the use of maximum values of rainfall intensity and wind speed related to short recording intervals, which can often only be estimated from available less exhaustive records. Given that many locations lack exhaustive climatic records that would allow accurate empirical correlations between different recording intervals to be identified, generic equations are often used to estimate these extreme values. The accuracy of these generic estimates is especially important in fields such as the study of wind-driven rain, in which both climatic variables are combined to characterise the phenomenon. This work assesses the reliability and functionality of some of these most widespread generic equations, analysing climatic datasets gathered since 2008 in 109 weather stations in Spain and the Netherlands. Considering multiple recording intervals at each location, it is verified that most of these generic estimations, used especially in the study of wind-driven rain, have functional limitations and can cause significant errors when characterising both variables for subdaily intervals and extreme conditions. Finally, an alternative approach is proposed to accurately extrapolate extreme values of both variables related to any subdaily recording interval in a functional manner and from any available records. © 2021, The Author(s).

Idioma: Inglés

DOI: 10.1007/s00477-021-02144-4

Año: 2022

Publicado en: STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 36 (2022), [15 pp]
ISSN: 1436-3240

Factor impacto JCR: 4.2 (2022)

Categ. JCR: STATISTICS & PROBABILITY rank: 10 / 125 = 0.08 (2022) - Q1 - T1
Categ. JCR: WATER RESOURCES rank: 27 / 103 = 0.262 (2022) - Q2 - T1
Categ. JCR: ENGINEERING, CIVIL rank: 37 / 139 = 0.266 (2022) - Q2 - T1
Categ. JCR: ENVIRONMENTAL SCIENCES rank: 104 / 275 = 0.378 (2022) - Q2 - T2
Categ. JCR: ENGINEERING, ENVIRONMENTAL rank: 28 / 55 = 0.509 (2022) - Q3 - T2

Factor impacto CITESCORE: 6.5 - Environmental Science (Q1) - Engineering (Q1)

Factor impacto SCIMAGO: 0.814 - Environmental Science (miscellaneous) (Q1) - Environmental Engineering (Q1) - Water Science and Technology (Q1) - Safety, Risk, Reliability and Quality (Q1) - Environmental Chemistry (Q2)

Tipo y forma: Article (Published version)

Área (Departamento): Area Ingeniería Construcción (Dpto. Ingeniería Mecánica)