Nonlinear Conditional Model Bias Estimation for Data Assimilation

DOI10.1137/19M1294848zbMath1466.34050OpenAlexW3093361033MaRDI QIDQ4983533

A. S. Lawless, Jason A. Otkin, Roland W. E. Potthast

Publication date: 20 April 2021

Published in: SIAM Journal on Applied Dynamical Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/19m1294848

zbMATH Keywords

parameter estimationasymptotic expansionvariational data assimilationbias correctionmodel errorLorenz

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Sensitivity (robustness) (93B35) Numerical optimization and variational techniques (65K10) Qualitative investigation and simulation of ordinary differential equation models (34C60)

Uses Software

• EnKF
• NICAM

Cites Work

• Nonlinear data assimilation
• Inverse Modeling
• Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system
• Deterministic Nonperiodic Flow
• Probabilistic Forecasting and Bayesian Data Assimilation
• The ensemble Kalman filter for combined state and parameter estimation
• Adjoint methods in data assimilation for estimating model error
• Unnamed Item

This page was built for publication: Nonlinear Conditional Model Bias Estimation for Data Assimilation