Matches in SemOpenAlex for { <https://semopenalex.org/work/W2345290765> ?p ?o ?g. }
- W2345290765 endingPage "2323" @default.
- W2345290765 startingPage "2314" @default.
- W2345290765 abstract "The local correlation tensor (LCT), also referred to as the local correlation Hessian, the inverse of which is known as the Daley tensor, has proven a useful diagnostic of the spatial variability of background‐error correlations in data assimilation. The LCT (or its inverse) is also used in several correlation models, including those based on recursive filters, the diffusion equation and spatial deformations. It can be estimated from the variances of the background errors and of their spatial derivatives. Additional terms involving the spatial derivatives of the standard deviations are often neglected. This approximation is first discussed for ensembles of forecasts at the global scale. In the context of numerical weather prediction (NWP), only limited ensemble sizes are computationally affordable, meaning that the LCT is affected by sampling noise. The estimation of the LCT may be improved by an efficient spatial filtering designed to remove this sampling noise. Recently, a linear filtering theory was developed by the authors for the purpose of filtering background‐error covariances objectively, with applications to variance filtering and localization (in a convective‐scale model). We discuss several practical filters for the LCT that are designed to preserve its symmetric positive‐definite character. This can be achieved by filtering the raw LCT itself, or by filtering the numerator and the denominator separately within the aforementioned approximation. This also requires a positive filter, a feature not present in earlier attempts. Finally, it is shown that the LCT can be estimated robustly from small ensembles and that this estimation benefits from our objective spatial filtering, equivalent to increasing the sample size by a factor of 1.5–3 depending on the model variable and the vertical level at which it is defined." @default.
- W2345290765 created "2016-06-24" @default.
- W2345290765 creator A5034705960 @default.
- W2345290765 creator A5046044727 @default.
- W2345290765 creator A5064804738 @default.
- W2345290765 date "2016-06-28" @default.
- W2345290765 modified "2023-09-30" @default.
- W2345290765 title "Objective filtering of the local correlation tensor" @default.
- W2345290765 cites W1824241068 @default.
- W2345290765 cites W1959706794 @default.
- W2345290765 cites W1983461984 @default.
- W2345290765 cites W1988927531 @default.
- W2345290765 cites W2000849814 @default.
- W2345290765 cites W2001410644 @default.
- W2345290765 cites W2005407621 @default.
- W2345290765 cites W2007339479 @default.
- W2345290765 cites W2009104157 @default.
- W2345290765 cites W2018294169 @default.
- W2345290765 cites W2027156186 @default.
- W2345290765 cites W2035331188 @default.
- W2345290765 cites W2037932868 @default.
- W2345290765 cites W2041134504 @default.
- W2345290765 cites W2048163104 @default.
- W2345290765 cites W2052637410 @default.
- W2345290765 cites W2058703564 @default.
- W2345290765 cites W2066455064 @default.
- W2345290765 cites W2076116040 @default.
- W2345290765 cites W2089876500 @default.
- W2345290765 cites W2092705724 @default.
- W2345290765 cites W2098930828 @default.
- W2345290765 cites W2107054232 @default.
- W2345290765 cites W2128115843 @default.
- W2345290765 cites W2134928158 @default.
- W2345290765 cites W2138087223 @default.
- W2345290765 cites W2146803308 @default.
- W2345290765 cites W2152498685 @default.
- W2345290765 cites W2163649185 @default.
- W2345290765 cites W2169025229 @default.
- W2345290765 cites W2169926060 @default.
- W2345290765 cites W2173190456 @default.
- W2345290765 cites W2175400375 @default.
- W2345290765 cites W4249145583 @default.
- W2345290765 cites W2119327250 @default.
- W2345290765 doi "https://doi.org/10.1002/qj.2824" @default.
- W2345290765 hasPublicationYear "2016" @default.
- W2345290765 type Work @default.
- W2345290765 sameAs 2345290765 @default.
- W2345290765 citedByCount "5" @default.
- W2345290765 countsByYear W23452907652018 @default.
- W2345290765 countsByYear W23452907652020 @default.
- W2345290765 countsByYear W23452907652022 @default.
- W2345290765 countsByYear W23452907652023 @default.
- W2345290765 crossrefType "journal-article" @default.
- W2345290765 hasAuthorship W2345290765A5034705960 @default.
- W2345290765 hasAuthorship W2345290765A5046044727 @default.
- W2345290765 hasAuthorship W2345290765A5064804738 @default.
- W2345290765 hasConcept C105795698 @default.
- W2345290765 hasConcept C106131492 @default.
- W2345290765 hasConcept C11413529 @default.
- W2345290765 hasConcept C115961682 @default.
- W2345290765 hasConcept C121332964 @default.
- W2345290765 hasConcept C121475858 @default.
- W2345290765 hasConcept C140779682 @default.
- W2345290765 hasConcept C150060386 @default.
- W2345290765 hasConcept C151730666 @default.
- W2345290765 hasConcept C153294291 @default.
- W2345290765 hasConcept C154945302 @default.
- W2345290765 hasConcept C155281189 @default.
- W2345290765 hasConcept C202444582 @default.
- W2345290765 hasConcept C203616005 @default.
- W2345290765 hasConcept C24552861 @default.
- W2345290765 hasConcept C2779343474 @default.
- W2345290765 hasConcept C28826006 @default.
- W2345290765 hasConcept C31972630 @default.
- W2345290765 hasConcept C33923547 @default.
- W2345290765 hasConcept C41008148 @default.
- W2345290765 hasConcept C86803240 @default.
- W2345290765 hasConcept C99498987 @default.
- W2345290765 hasConceptScore W2345290765C105795698 @default.
- W2345290765 hasConceptScore W2345290765C106131492 @default.
- W2345290765 hasConceptScore W2345290765C11413529 @default.
- W2345290765 hasConceptScore W2345290765C115961682 @default.
- W2345290765 hasConceptScore W2345290765C121332964 @default.
- W2345290765 hasConceptScore W2345290765C121475858 @default.
- W2345290765 hasConceptScore W2345290765C140779682 @default.
- W2345290765 hasConceptScore W2345290765C150060386 @default.
- W2345290765 hasConceptScore W2345290765C151730666 @default.
- W2345290765 hasConceptScore W2345290765C153294291 @default.
- W2345290765 hasConceptScore W2345290765C154945302 @default.
- W2345290765 hasConceptScore W2345290765C155281189 @default.
- W2345290765 hasConceptScore W2345290765C202444582 @default.
- W2345290765 hasConceptScore W2345290765C203616005 @default.
- W2345290765 hasConceptScore W2345290765C24552861 @default.
- W2345290765 hasConceptScore W2345290765C2779343474 @default.
- W2345290765 hasConceptScore W2345290765C28826006 @default.
- W2345290765 hasConceptScore W2345290765C31972630 @default.
- W2345290765 hasConceptScore W2345290765C33923547 @default.
- W2345290765 hasConceptScore W2345290765C41008148 @default.