Low-Dimensional Reduced-Order Models for Statistical Response and Uncertainty Quantification: Two-Layer Baroclinic Turbulence

• Published in: Journal of the atmospheric sciences Vol. 73; no. 12; pp. 4609 - 4639
• Main Authors: Qi, Di, Majda, Andrew J.
• Format: Journal Article
• Language: English
• Published: Boston American Meteorological Society 01.12.2016
• Subjects: Approximation; Atmosphere; Atmospheric models; Climate; Climate change; Climate science; Climate system; Computational fluid dynamics; Corrections; Damping; Dimensional changes; Dynamical systems; Earth; Earth atmosphere; Efficiency; Energy; Energy conservation; Frameworks; General circulation models; Interactions; Jets; Latitude; Loads (forces); Mathematical models; Meandering; Modes; Noise; Nonlinear systems; Nonlinearity; Ocean circulation; Reduced order models; Scaling; Scaling factors; Science; Sensitivity; Statistical analysis; Statistical methods; Statistical models; Studies; Training; Turbulence; Uncertainty; Variability; Variance; Wavelengths

Accurate uncertainty quantification for the mean and variance about forced responses to general external perturbations in the climate system is an important subject in understanding Earth’s atmosphere and ocean in climate change science. A low-dimensional reduced-order method is developed for uncert...