Evaluation of nonidentical versus identical twin approaches for observation impact assessments: an ensemble-Kalman-filter-based   ocean assimilation application for the Gulf of Mexico

Yu, Liuqian; Fennel, Katja; Wang, Bin; Laurent, Arnaud; Thompson, Keith R.; Shay, Lynn K.

doi:https://doi.org/10.5194/os-15-1801-2019

Articles | Volume 15, issue 6

https://doi.org/10.5194/os-15-1801-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/os-15-1801-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 6

Research article

|

20 Dec 2019

Research article |

| 20 Dec 2019

Evaluation of nonidentical versus identical twin approaches for observation impact assessments: an ensemble-Kalman-filter-based ocean assimilation application for the Gulf of Mexico

Liuqian Yu, Katja Fennel, Bin Wang, Arnaud Laurent, Keith R. Thompson, and Lynn K. Shay

Data sets

Gulf of Mexico regional ocean model at 5km horizontal resolution assimilating satellite and float data with Ensemble Kalman Filter (EnKF) from 2010-04-01 to 2010-10-01 L. Yu, K. Fennel, B. Wang, A. Laurent, K. R. Thompson, and L. K. Shay https://doi.org/10.7266/n7-zc10-mz49

Short summary

We present a first direct comparison of nonidentical versus identical twin approaches for an ocean data assimilation system. We show that the identical twin approach overestimates the value of assimilating satellite observations and undervalues the benefit of assimilating temperature and salinity profiles. Misleading assessments such as undervaluing the impact of observational assets are problematic and can lead to misguided decisions on balancing investments among different observing assets.