Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts

Shen, Zheqi; Chen, Yihao; Li, Xiaojing; Song, Xunshu

doi:https://doi.org/10.5194/gmd-17-1651-2024

Articles | Volume 17, issue 4

https://doi.org/10.5194/gmd-17-1651-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-17-1651-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 4

Development and technical paper

|

26 Feb 2024

Development and technical paper |

| 26 Feb 2024

Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts

Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song

Data sets

Data and code for gmd-2023-113 "Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on ENSO forecast" Z. Shen https://doi.org/10.5281/zenodo.8115394

Model code and software

Data and code for gmd-2023-113 "Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on ENSO forecast" Z. Shen https://doi.org/10.5281/zenodo.8115394

Short summary

Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.