The Sea State CCI dataset v1: towards a sea state climate data record based on satellite observations

Dodet, Guillaume; Piolle, Jean-François; Quilfen, Yves; Abdalla, Saleh; Accensi, Mickaël; Ardhuin, Fabrice; Ash, Ellis; Bidlot, Jean-Raymond; Gommenginger, Christine ORCID: https://orcid.org/0000-0002-6941-1671; Marechal, Gwendal; Passaro, Marcello; Quartly, Graham; Stopa, Justin; Timmermans, Ben ORCID: https://orcid.org/0000-0003-2220-8489; Young, Ian; Cipollini, Paolo; Donlon, Craig. 2020 The Sea State CCI dataset v1: towards a sea state climate data record based on satellite observations. Earth System Science Data, 12 (3). 1929-1951. https://doi.org/10.5194/essd-12-1929-2020

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Official URL: http://dx.doi.org/10.5194/essd-12-1929-2020

Abstract/Summary

Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent, and sea state data users still mostly rely on numerical wave models for research and engineering applications. Facing the urgent need for a sea state climate data record, the Global Climate Observing System has listed “Sea State” as an Essential Climate Variable (ECV), fostering the launch in 2018 of the Sea State Climate Change Initiative (CCI). The CCI is a programme of the European Space Agency, whose objective is to realise the full potential of global Earth observation archives established by ESA and its member states in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset, the implementation and benefits of a high-level denoising method, its validation against in situ measurements and numerical model outputs, and the future developments considered within the Sea State CCI project.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.5194/essd-12-1929-2020
ISSN:	1866-3516
Date made live:	10 Nov 2020 14:24 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/528919

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.5194/essd-12-1929-2020

ISSN:

1866-3516

Date made live:

10 Nov 2020 14:24 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/528919