Development of the Nonstationary Incremental Analysis Update Algorithm for Sequential Data Assimilation System
Autor: | Jaehee Jung, Yoo-Geun Ham, Gyu-Ho Lim, Hyo-Jong Song |
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Rok vydání: | 2016 |
Předmět: |
Atmospheric Science
Forcing (recursion theory) Article Subject 010504 meteorology & atmospheric sciences 010505 oceanography Property (programming) Computer science Linear system Interval (mathematics) lcsh:QC851-999 01 natural sciences Pollution Field (computer science) Geophysics Operator (computer programming) Data assimilation Simple (abstract algebra) lcsh:Meteorology. Climatology Algorithm 0105 earth and related environmental sciences |
Zdroj: | Advances in Meteorology, Vol 2016 (2016) ADVANCES IN METEOROLOGY |
ISSN: | 1687-9317 1687-9309 |
Popis: | This study introduces a modified version of the incremental analysis updates (IAU), called the nonstationary IAU (NIAU) method, to improve the assimilation accuracy of the IAU while keeping the continuity of the analysis. Similar to the IAU, the NIAU is designed to add analysis increments at every model time step to improve the continuity in the intermittent data assimilation. However, unlike the IAU, the NIAU procedure uses time-evolved forcing using the forward operator as corrections to the model. The solution of the NIAU is superior to that of the forward IAU, of which analysis is performed at the beginning of the time window for adding the IAU forcing, in terms of the accuracy of the analysis field. It is because, in the linear systems, the NIAU solution equals that in an intermittent data assimilation method at the end of the assimilation interval. To have the filtering property in the NIAU, a forward operator to propagate the increment is reconstructed with only dominant singular vectors. An illustration of those advantages of the NIAU is given using the simple 40-variable Lorenz model. |
Databáze: | OpenAIRE |
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