8 citations as recorded by crossref.

1. A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund–Potsdam–Jena (LPJ) model as an example G. Sun & M. Mu https://doi.org/10.1007/s00704-015-1690-9
2. Application of Graphic and Image Technology in Strong Convective Weather Monitoring and Early-Warning System F. Jiao & T. Huang https://doi.org/10.1134/S1054661819040060
3. Predicting PM2.5 Concentration in the Yangtze River Delta Region Using Climate System Monitoring Indices and Machine Learning J. Ma et al. https://doi.org/10.1007/s13351-024-3099-9
4. Inverse differential equation modeling of ENSO prediction based on memory kernel functions S. Wan et al. https://doi.org/10.1007/s00382-025-07719-3
5. Limitations of BCC_CSM's ability to predict summer precipitation over East Asia and the Northwestern Pacific Z. Gong et al. https://doi.org/10.1016/j.atmosres.2017.04.016
6. Objective identification research on cold vortex and mid-summer rainy periods in Northeast China Z. Gong et al. https://doi.org/10.1088/1674-1056/24/4/049204
7. An improved method for nonlinear parameter estimation: a case study of the Rössler model W. He et al. https://doi.org/10.1007/s00704-015-1528-5
8. A new method for parameter estimation in nonlinear dynamical equations L. Wang et al. https://doi.org/10.1007/s00704-014-1113-3