EGU21-15014
https://doi.org/10.5194/egusphere-egu21-15014
EGU General Assembly 2021
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Sea state trends and variability: consistency between the ESA Sea State Climate Change Inititative dataset, ERA5 winds and microseisms

Matias Alday1,2, Marine De Carlo1, Guillaume Dodet3, Mickael Accensi3, Eleonore Stutzmann4, Fabrice Ardhuin3, and Jean Bidlot5
Matias Alday et al.
  • 1Laboratoire d'Océanographie Physique et Spatiale (LOPS), Centre national de la recherche scientifique (CNRS) , Brest, France (malday@ifremer.fr)
  • 2Université de Bretagne Occidentale (UBO), Brest, France
  • 3Laboratoire d’Océanographie Physique et Spatiale (LOPS), CNRS, IRD, Ifremer, IUEM,Univ. Brest, France
  • 4Institut de Physique du Globe de Paris (IPGP), Paris, France (stutz@ipgp.fr)
  • 5European Centre for Medium-range Weather Forecasts, Reading, United Kingdom (Jean.Bidlot@ecmwf.int)

Abstract: Wave hindcasts of long time series ( > 30 years) have been instrumental in understanding the wave climate. However, it is still difficult to have a consistent reanalysis suitable for study of trends and interannual variability. Here we explore the consistency of wave hindcast with independent observations from moored buoys, satellite altimeters, and  microseism data. We use the ECMWF 5th generation re-analysis (ERA5) winds to drive two wave models, using either ECMWF WAM (Bidlot et al. 2019) or WAVEWATCH III (The WAVEWATCH III Develoment Group 2019, Alday et al. 2020). We also use seismic data in the dominant double-frequency band, around 5 s period, that are generated by opposing waves of equal frequencies and compare these to modeled microseims. We find that the inter-platform corrections in the ESA CCI Version 1.1 dataset (Dodet et al. 2020) introduced a trend that differs from the microseism trends. However, the results converge when using a revised correction of this dataset. We also look at the microseism spectral signature of large storms in the North Atlantic and discuss how we may compare the severity of different storms that move over different ocean bathymetry with different wave to microseism conversions. 

References: Stopa, J. E., Ardhuin, F., Stutzmann, E., & Lecocq, T. (2019).  Sea state trends and variability: Consistency between models, altimeters, buoys, and seismic data (1979–2016). Journal of Geophysical Research: Oceans, 124. https://doi.org/10.1029/2018JC014607 

Dodet, G., Piolle, J.-F., Quilfen, Y., Abdalla, S., Accensi, M., Ardhuin, F., Ash, E., Bidlot, J.-R., Gommenginger, C., Marechal, G., Passaro, M., Quartly, G., Stopa, J., Timmermans, B., Young, I., Cipollini, P., and Donlon, C.: The Sea State CCI dataset v1: towards a sea state climate data record based on satellite observations, Earth Syst. Sci. Data, 12, 1929–1951, https://doi.org/10.5194/essd-12-1929-2020 , 2020.

How to cite: Alday, M., De Carlo, M., Dodet, G., Accensi, M., Stutzmann, E., Ardhuin, F., and Bidlot, J.: Sea state trends and variability: consistency between the ESA Sea State Climate Change Inititative dataset, ERA5 winds and microseisms, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15014, https://doi.org/10.5194/egusphere-egu21-15014, 2021.