Quantification of Optimal Choices of Parameters in Lognormal Variational Data Assimilation and Their Chaotic Behavior
| Autor: | S. J. Fletcher, Anton J. Kliewer, Andrew S. Jones |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Multivariate statistics
0208 environmental biotechnology Chaotic Multivariate normal distribution 02 engineering and technology Solver 010502 geochemistry & geophysics 01 natural sciences Decimal 020801 environmental engineering Mathematics (miscellaneous) Data assimilation Log-normal distribution General Earth and Planetary Sciences Applied mathematics A priori and a posteriori 0105 earth and related environmental sciences Mathematics |
| Zdroj: | Mathematical Geosciences. 51:187-207 |
| ISSN: | 1874-8953 1874-8961 |
| DOI: | 10.1007/s11004-018-9765-7 |
| Popis: | An important property of variational-based data assimilation is the ability to define a functional formulation such that the minimum of that functional can be any state that is desired. Thus, it is possible to define cost functions such that the minimum of the background error component is the mean, median or the mode of a multivariate lognormal distribution, where, unlike the multivariate Gaussian distributions, these statistics are not equivalent. Therefore, for lognormal distributions it is shown here that there are regions where each one of these three statistics are optimal at minimizing the errors, given estimates of an a priori state. Also, as part of this work, a chaotic signal was detected with respect to the first guess to the Newton–Raphson solver that affect the accuracy of the solution to several decimal places. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink