Data assimilation with model errors
COMPUTERS & MATHEMATICS WITH APPLICATIONS, cilt.213, ss.172-189, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 213
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.camwa.2026.04.023
- Dergi Adı: COMPUTERS & MATHEMATICS WITH APPLICATIONS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Compendex, INSPEC, MathSciNet, MLA - Modern Language Association Database, zbMATH, MLA International Bibliography, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO), Technology Collection (ProQuest)
- Sayfa Sayıları: ss.172-189
- Gazi Üniversitesi Adresli: Evet
Özet
Nudging is a data assimilation method amenable to both analysis and implementation. It also has the (reported) advantage of being insensitive to model errors compared to other assimilation methods, such as Kalman filter variants. However, nudging behavior in the presence of model errors is little analyzed. This report gives an analysis of nudging to correct one type of model error. The analysis indicates that the error contribution due to the model error decays as the nudging parameter %- infinity like O(%-21), Theorem 3.1. Numerical tests verify the predicted convergence rates and validate the nudging correction to model errors.