Scale Utilization and Optimization from Wavelet Analysis for Data Assimilation: SUgOiWADAi

Abstract

The second generation of a new approach to data assimilation where wavelet analysis is used for error estimation is presented here. The first generation is known as EEWADAi. This modified and optimized method uses wavelet analysis to not only estimate numerical error but to also acquire an estimate of the variation at various scales of the model simulation. In the original EEWADAi, wavelet analysis on the finest scale was used to estimate numerical error. In the second-generation version, called SUgOiWADAi, wavelet analysis is used on a variety of scales to not only obtain an estimate of numerical error, finest-scale information, but to also obtain an estimate of model variation, information from coarser scales. This new algorithm is computationally very inexpensive and is very effective.