Modular Data Assimilation for Flow Prediction

Çıbık A., Fang R., Layton W.

Numerical Methods for Partial Differential Equations, vol.42, no.1, 2026 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 42 Issue: 1
  • Publication Date: 2026
  • Doi Number: 10.1002/num.70066
  • Journal Name: Numerical Methods for Partial Differential Equations
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, MathSciNet, zbMATH, DIALNET
  • Keywords: data assimilation, Navier Stokes, nudging, predictability
  • Gazi University Affiliated: Yes

Abstract

Modular nudging algorithms (inspired by Kalman filters) are presented. (Formula presented.) There are 3 main results. 1. If (Formula presented.), analysis has implicit stability and explicit complexity: (Formula presented.) 2. For (Formula presented.) small and (Formula presented.) large, predictability horizons are infinite. 3. For any (Formula presented.) and (Formula presented.), errors decrease and predictability horizons increase. Numerics confirm the method's effectiveness.