Satellite-retrieved sea ice concentration uncertainty and its effect on modelling wave evolution in marginal ice zones

Nose, Takehiko; Waseda, Takuji; Kodaira, Tsubasa; Inoue, Jun

doi:https://doi.org/10.5194/tc-14-2029-2020

Articles | Volume 14, issue 6

https://doi.org/10.5194/tc-14-2029-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-14-2029-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 6

Research article

|

24 Jun 2020

Research article |

| 24 Jun 2020

Satellite-retrieved sea ice concentration uncertainty and its effect on modelling wave evolution in marginal ice zones

Takehiko Nose, Takuji Waseda, Tsubasa Kodaira, and Jun Inoue

Data sets

Swiss Early Meteorological Observations Y. Brugnara https://doi.org/10.1594/PANGAEA.909141

Early instrumental meteorological measurements in Switzerland L. Pfister https://doi.org/10.5281/zenodo.3066836

Model code and software

dataresqc: Quality control tools for climate data developedby the C3S Data Rescue Servic Y. Brugnara, A. Gilabert, C. Ventura, and S. Hunziker https://github.com/c3s-data-rescue-service/dataresqc

Short summary

Accurate wave modelling in and near ice-covered ocean requires true sea ice concentration mapping of the model region. The information derived from satellite instruments has considerable uncertainty depending on retrieval algorithms and sensors. This study shows that the accuracy of satellite-retrieved sea ice concentration estimates is a major error source in wave–ice models. A similar feedback effect of sea ice concentration uncertainty may also apply to modelling lower atmospheric conditions.