A global atlas of ocean wave spectra is developed and presented. The development is based on a new technique for deriving wave spectral statistics, which is applied to the extensive ERA-Interim database from European Centre of Medium-Range Weather Forecasts. Spectral statistics is based on the idea of long-term wave systems, which are unique and distinct at every geographical point. The identification of those wave systems allows their separation from the overall spectrum using the partition technique. Their further characterization is made using standard integrated parameters, which turn out much more meaningful when applied to the individual components than to the total spectrum. The parameters developed include the density distribution of spectral partitions, which is the main descriptor; the identified wave systems; the individual distribution of the characteristic frequencies, directions, wave height, wave age, seasonal variability of wind and waves; return periods derived from extreme value analysis; and crossing-sea probabilities. This information is made available in web format for public use at http://www.modemat.epn.edu.ec/#/nereo. It is found that wave spectral statistics offers the possibility to synthesize data while providing a direct and comprehensive view of the local and regional wave conditions.
|Original language||English (US)|
|Number of pages||10|
|Journal||Geophysical Research Letters|
|State||Published - Dec 28 2017|
Bibliographical noteKAUST Repository Item: Exported on 2022-06-03
Acknowledgements: This work was funded by Escuela Politécnica Nacional (project PIJ-1503) and supported by ModeMat-EPN (Centro de Modelización Matemática). Part of this work was done during research visits to ISMAR-CNR in Venice (Italy) and KAUST University (Saudi Arabia). I am very grateful to Luigi Cavaleri, Ibrahim Hoteit, and Sabique Langodan for the interaction and useful comments during these visits. The collaboration of Jeison Sosa, Andrés Salazar, Cristhian Valladares, and Edwin Jácome is highly appreciated. I am also grateful to Brian Blaton for providing the read_grib software and also for his prompt support. This development was possible by the public release of the ERA-Interim spectral data by ECMWF. In particular, Jean Bidlot provided guide and support with data processing. The dedicated work of the anonymous reviewers helped improve the final quality of the manuscript.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.