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Volume 14, issue 4 | Copyright
Ocean Sci., 14, 911-921, 2018
https://doi.org/10.5194/os-14-911-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 30 Aug 2018

Research article | 30 Aug 2018

Estimation of extreme wave height return periods from short-term interpolation of multi-mission satellite data: application to the South Atlantic

Julio Salcedo-Castro1, Natália Pillar da Silva2, Ricardo de Camargo2, Eduardo Marone3, and Héctor H. Sepúlveda4 Julio Salcedo-Castro et al.
  • 1Centro de Estudios Avanzados, Universidad de Playa Ancha, Traslaviña 450, Viña del Mar, Chile
  • 2Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, Rua do Matão, 1226, 05508-900, São Paulo, SP, Brazil
  • 3Centro de Estudos do Mar, Universidade Federal do Paraná, Av. Beira Mar s/n, 83255-000, Pontal do Sul, PR, Brazil
  • 4Departamento de Geofísica, Universidad de Concepción, Avenida Esteban Iturra s/n, Barrio Universitario, Concepción, Chile

Abstract. We analyzed the spatial pattern of wave extremes in the South Atlantic Ocean by using multiple altimeter platforms spanning the period 1993–2015. Unlike the traditional approach adopted by previous studies, consisting of computing the monthly mean, median or maximum values inside a bin of certain size, we tackled the problem with a different procedure in order to capture more information from short-term events. All satellite tracks occurring during a 2-day temporal window were gathered in the whole area and then gridded data were generated onto a mesh size of 2° × 2° through optimal interpolation. The peaks over threshold (POT) method was applied, along with the generalized Pareto distribution (GPD). The results showed a spatial distribution comparable to previous studies and, additionally, this method allowed for capturing more information on shorter timescales without compromising spatial coverage. A comparison with buoy observations demonstrated that this approach improves the representativeness of short-term events in an extreme events analysis.

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This paper is focused on a new treatment to along-track satellite data so as to improve the processing of information related to the occurrence of extreme values. The main objective is to preserve information concerning the occurrence of short-term extreme events (2-5 days), like cyclones. In this way, the representativeness of these events is enhanced when applying extreme value return analyses. This method allows us to improve our estimation of return periods for risk analyses.
This paper is focused on a new treatment to along-track satellite data so as to improve the...
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