Open AccessDirectional Calibration of Wave Reanalysis Databases Using Instrumental Data
Author(s) -
Roberto Mı́nguez,
Antonio Guerrero Espejo,
Antonio Tomás,
Fernando J. Méndez,
Íñigo J. Losada
Publication year - 2011
Publication title -
journal of atmospheric and oceanic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.774
H-Index - 124
eISSN - 1520-0426
pISSN - 0739-0572
DOI - 10.1175/jtech-d-11-00008.1
Subject(s) - calibration , series (stratigraphy) , forcing (mathematics) , remote sensing , satellite , meteorology , time series , computer science , geology , climatology , mathematics , statistics , geography , paleontology , machine learning , aerospace engineering , engineering
Wave reanalysis databases (WRDBs) offer important advantages for the statistical characterization of wave climate (continuous time series, good spatial coverage, constant time span, homogeneous forcing, and more than a 40-yr-long time series) and for this reason, they have become a powerful tool for the design of offshore and coastal structures. However, WRDBs are not quantitatively perfect and corrections using instrumental observations must be addressed before they are used; this process is called calibration. The calibration is especially relevant near the coast and in areas where the orography is complex, since in these places the inaccuracy of WRDB is evident because of the bad description of the wind fields (i.e., insufficient forcing resolution). The quantitative differences between numerical and instrumental data suggest that different corrections should be applied depending on the mean direction of the sea state. This paper proposes a calibration method based on a nonlinear regression problem, where the corresponding correction parameters vary smoothly along the possible wave directions by means of cubic splines. The correction of significant wave height is performed using instrumental data: (i) buoy records and/or (ii) satellite data. The performance of the method is illustrated considering data from different locations around Spain.