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Publication Date
3 February 2024

Significance of Improved Initialization in Climate Models for Subseasonal-to-Seasonal Precipitation Prediction

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Non-zonal geopotential height (m) at 200 hPa from (a) ERAI reanalysis, (b) CIESM with nudging, (c) CIESM without nudging, (d) E3SMv1 with nudging and (e) E3SMv1 without nudging on April 30th, 2003.

Scientists at Lawrence Livermore National Laboratory within the Atmospheric, Earth, and Energy Division, along with collaborators from scientists from Pacific Northwest National Laboratory, University of California Los Angeles, and Tsinghua University, examined the impact of initial conditions on subseasonal-to-seasonal (S2S) precipitation prediction in two climate models, including E3SMv1. The focus is to reveal the importance of the nudging approach to generating more realistic initial conditions for S2S precipitation predictions.


This study highlights the important role that initial condition plays in the S2S prediction and suggests that data assimilation technique (e.g., nudging) should be adopted to initialize climate models to improve their S2S prediction.


They found that the nudging approach helps generate more realistic initial conditions and large-scale wave patterns in climate models. Simulations with nudged initial conditions are able to capture the impact of the springtime land temperature anomaly over the Tibetan Plateau on the summertime precipitation predictions, as observation showed. Further analyses show that the enhanced S2S prediction skill is largely attributable to the substantially improved initialization of the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train pattern in the atmosphere.

Point of Contact
Qi Tang
Lawrence Livermore National Laboratory
Funding Program Area(s)
Additional Resources:
NERSC (National Energy Research Scientific Computing Center)
Improved subseasonal-to-seasonal precipitation prediction of climate models with nudging approach for better initialization of Tibetan Plateau-Rocky Mountain Circumglobal wave train and land surface conditions
Qin, Yi, Qi Tang, Yongkang Xue, Ye Liu, and Yanluan Lin. 2024. “Improved Subseasonal-To-Seasonal Precipitation Prediction Of Climate Models With Nudging Approach For Better Initialization Of Tibetan Plateau-Rocky Mountain Circumglobal Wave Train And Land Surface Conditions”. Climate Dynamics. Springer Science and Business Media LLC. doi:10.1007/s00382-023-07082-1.