Matches in SemOpenAlex for { <https://semopenalex.org/work/W3127730307> ?p ?o ?g. }
- W3127730307 endingPage "101317" @default.
- W3127730307 startingPage "101317" @default.
- W3127730307 abstract "Ensemble optimal interpolation (EnOI) is a variant of the ensemble Kalman filter (EnKF) that operates with a static ensemble to drastically reduce its computational cost. The idea is to use a pre-selected ensemble to parameterize the background covariance matrix, which avoids the costly integration of the ensemble members with the dynamical model during the forecast step of the filtering process. To better represent the pronounced time-varying circulation of the Red Sea, we propose a new adaptive EnOI approach in which the ensemble members are adaptively selected at every assimilation cycle from a large dictionary of ocean states describing the Red Sea variability. We implement and test different schemes to select the ensemble members (i) based on the similarity to the forecast state according to some criteria, or (ii) in term of best representation of the forecast in an ensemble subspace using an Orthogonal Matching Pursuit (OMP) algorithm. The relevance of the schemes is first demonstrated with the Lorenz 63 and Lorenz 96 models. Then results of numerical experiments assimilating real remote sensing data into a high resolution MIT general circulation model (MITgcm) of the Red Sea using the Data Assimilation Research Testbed (DART) system are presented and discussed." @default.
- W3127730307 created "2021-02-15" @default.
- W3127730307 creator A5005418728 @default.
- W3127730307 creator A5015336386 @default.
- W3127730307 creator A5057808532 @default.
- W3127730307 creator A5059933283 @default.
- W3127730307 creator A5078664036 @default.
- W3127730307 creator A5089073067 @default.
- W3127730307 date "2021-04-01" @default.
- W3127730307 modified "2023-09-23" @default.
- W3127730307 title "Adaptive ensemble optimal interpolation for efficient data assimilation in the red sea" @default.
- W3127730307 cites W1876204689 @default.
- W3127730307 cites W1920371256 @default.
- W3127730307 cites W1963549306 @default.
- W3127730307 cites W1967603806 @default.
- W3127730307 cites W1971037529 @default.
- W3127730307 cites W1977219044 @default.
- W3127730307 cites W1978648105 @default.
- W3127730307 cites W1980342161 @default.
- W3127730307 cites W1980785126 @default.
- W3127730307 cites W1987308763 @default.
- W3127730307 cites W2006688772 @default.
- W3127730307 cites W2009104157 @default.
- W3127730307 cites W2011985632 @default.
- W3127730307 cites W2017644515 @default.
- W3127730307 cites W2023348710 @default.
- W3127730307 cites W2025179796 @default.
- W3127730307 cites W2029905393 @default.
- W3127730307 cites W2043654662 @default.
- W3127730307 cites W2044392877 @default.
- W3127730307 cites W2049013344 @default.
- W3127730307 cites W2059389250 @default.
- W3127730307 cites W2059670821 @default.
- W3127730307 cites W2060478682 @default.
- W3127730307 cites W2064130482 @default.
- W3127730307 cites W2092294382 @default.
- W3127730307 cites W2098552783 @default.
- W3127730307 cites W2105934661 @default.
- W3127730307 cites W2110582201 @default.
- W3127730307 cites W2121745948 @default.
- W3127730307 cites W2127271355 @default.
- W3127730307 cites W2131070146 @default.
- W3127730307 cites W2131541922 @default.
- W3127730307 cites W2134222107 @default.
- W3127730307 cites W2141394518 @default.
- W3127730307 cites W2151693816 @default.
- W3127730307 cites W2157098139 @default.
- W3127730307 cites W2162266044 @default.
- W3127730307 cites W2171652164 @default.
- W3127730307 cites W2173190456 @default.
- W3127730307 cites W2174784159 @default.
- W3127730307 cites W2179229003 @default.
- W3127730307 cites W2179584279 @default.
- W3127730307 cites W2255975795 @default.
- W3127730307 cites W2266194112 @default.
- W3127730307 cites W2291415704 @default.
- W3127730307 cites W2415980165 @default.
- W3127730307 cites W2558042419 @default.
- W3127730307 cites W2570138886 @default.
- W3127730307 cites W2589800576 @default.
- W3127730307 cites W2606993449 @default.
- W3127730307 cites W2617034617 @default.
- W3127730307 cites W2617713127 @default.
- W3127730307 cites W2627957529 @default.
- W3127730307 cites W2749058995 @default.
- W3127730307 cites W2786932587 @default.
- W3127730307 cites W2800745722 @default.
- W3127730307 cites W2809372845 @default.
- W3127730307 cites W2810447632 @default.
- W3127730307 cites W2899463183 @default.
- W3127730307 cites W2904625235 @default.
- W3127730307 cites W2914426703 @default.
- W3127730307 cites W2970404950 @default.
- W3127730307 doi "https://doi.org/10.1016/j.jocs.2021.101317" @default.
- W3127730307 hasPublicationYear "2021" @default.
- W3127730307 type Work @default.
- W3127730307 sameAs 3127730307 @default.
- W3127730307 citedByCount "0" @default.
- W3127730307 crossrefType "journal-article" @default.
- W3127730307 hasAuthorship W3127730307A5005418728 @default.
- W3127730307 hasAuthorship W3127730307A5015336386 @default.
- W3127730307 hasAuthorship W3127730307A5057808532 @default.
- W3127730307 hasAuthorship W3127730307A5059933283 @default.
- W3127730307 hasAuthorship W3127730307A5078664036 @default.
- W3127730307 hasAuthorship W3127730307A5089073067 @default.
- W3127730307 hasConcept C105795698 @default.
- W3127730307 hasConcept C11413529 @default.
- W3127730307 hasConcept C119898033 @default.
- W3127730307 hasConcept C121332964 @default.
- W3127730307 hasConcept C147947694 @default.
- W3127730307 hasConcept C153294291 @default.
- W3127730307 hasConcept C154945302 @default.
- W3127730307 hasConcept C157286648 @default.
- W3127730307 hasConcept C178650346 @default.
- W3127730307 hasConcept C206833254 @default.
- W3127730307 hasConcept C24552861 @default.
- W3127730307 hasConcept C33923547 @default.
- W3127730307 hasConcept C41008148 @default.