Aligning Initial Conditions With Long‐Term Model Dynamics to Enhance 4DVar‐Driven Medium‐Range Global Forecasts
Year: 2026
Type: article
Abstract: Applying the four‐dimensional variational (4DVar) method in nonlinear systems faces conflicts between a lack of long‐term dynamical information using a short assimilation window and a trap of local minima using a long window. Here, an adjusted analysis approach that incorporates a thought of pseudo‐orbit analysis adjusting into 4DVar was proposed, resulting in the enhanced consistency between the initial condition (IC) and the long‐term dynamics of model, and the reduced risk of falling into local minima. This approach tries to find a truer orbit of weather state by minimizing the distance from the 4DVar‐based pseudo‐orbit to the long‐term model trajectory. Sensitivity experiments based on observing system simulation experiment reveal that the new approach with a proper iterative number can produce more reasonable analysis than 4DVar. Real observation experiments further exhibit that this approach can help 4DVar produce ICs that are more consistent with the long‐term dynamics and benefit the forecast skills.
Source: Geophysical Research Letters
DOI: 10.1029/2025gl119753
Institutions: Chinese Academy of Sciences, Institute of Atmospheric Physics, University of Chinese Academy of Sciences, Tsinghua University, China Meteorological Administration, State Key Laboratory of Severe Weather, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $3,190
Award: G8033499945
OpenAlex ID: W7162800562
