Status: this preprint has been withdrawn by the authors.
Potential Artifacts of Sequential State Estimation Invariants
Abstract. In sequential estimation methods often used in general climate or oceanic calculations of the state and of forecasts, observations act mathematically and statistically as forcings as is obvious in the innovation form of the equations. For purposes of calculating changes in important functions of state variables such as total mass and energy, or in volumetric current transports, results are sensitive to mis-representation of a large variety of parameters including initial conditions, prior uncertainty covariances, and systematic and random errors in observations. Errors are both stochastic and systematic, with the latter, as usual, being the most intractable. Here some of the consequences of such errors are first analyzed in the context of a simplified mass-spring oscillator system exhibiting many of the issues of far more complicated realistic problems. The same methods are then applied to a more geophysical barotropic Rossby wave plus western boundary current system. The overall message is that convincing trend and other time-dependent determinations in "reanalyis" like estimates requires a full understanding of both models and observations.
This preprint has been withdrawn.
How to cite. Wunsch, C.: Potential Artifacts of Sequential State Estimation Invariants, Ocean Sci. Discuss. [preprint], https://doi.org/10.5194/os-2021-113, 2021.
Received: 17 Nov 2021 – Discussion started: 03 Dec 2021
Combinations of observations with dynamical, chemical, etc, models are essential tools for understanding of climate change. By "climate" is meant all of the sub-elements including ocean, atmosphere, ice, et al. A common form of combination arises from sequential estimation theory, a methodology susceptible to a variety of errors that can accumulate through time for long records. Using two simple analogues, many of these errors are identified here, with suggestions for accommodating them.
Combinations of observations with dynamical, chemical, etc, models are essential tools for...