FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2093529471> ?p ?o ?g. }

• W2093529471 endingPage "633" @default.
• W2093529471 startingPage "623" @default.
• W2093529471 abstract "The ensemble Kalman filter (EnKF) approximates background error covariance by using a finite number of ensemble members. Although increasing the ensemble size consistently improves the EnKF analysis, typical applications of the EnKF to realistic atmospheric simulations are conducted with a small ensemble size due to limited computational resources. The finite ensemble size introduces a sampling error into the background error covariance, leading to a degradation of the accuracy of the analysis fields. As a representative of EnKF applications, a local ensemble transform Kalman filter (LETKF) was implemented on the K computer, the flagship supercomputer in Japan, which enables demanding computations with larger ensembles. This study investigated the performance of the LETKF on the K computer and evaluated the influence of sampling noise on the background error covariance estimated from 1000-member ensemble forecasting with the Japan Meteorological Agency nonhydrostatic model covering Japan with a 15-km horizontal resolution. The LETKF on the K computer achieved a high peak performance ratio of 14.7 % without special optimization, showing the suitability of the LETKF for high-performance parallel computing. The background error covariance estimated from 1000 ensemble members contained negligible sampling noise even at distant locations without covariance localization. The results indicated that for the case in the current study, an ensemble size of 500 would be large enough to approximate the error covariance under the configuration with a horizontal resolution of 15 km. The results also suggest that improving input/output performance will become a primary goal in the design of next-generation supercomputers." @default.
• W2093529471 created "2016-06-24" @default.
• W2093529471 creator A5071194157 @default.
• W2093529471 date "2014-01-01" @default.
• W2093529471 modified "2023-10-07" @default.
• W2093529471 title "The 1000-Member Ensemble Kalman Filtering with the JMA Nonhydrostatic Mesoscale Model on the K Computer" @default.
• W2093529471 cites W1568554934 @default.
• W2093529471 cites W1964139182 @default.
• W2093529471 cites W1965287458 @default.
• W2093529471 cites W1979566020 @default.
• W2093529471 cites W1980785126 @default.
• W2093529471 cites W1985623131 @default.
• W2093529471 cites W1998901243 @default.
• W2093529471 cites W2001735641 @default.
• W2093529471 cites W2005855731 @default.
• W2093529471 cites W2020075017 @default.
• W2093529471 cites W2022085144 @default.
• W2093529471 cites W2026177294 @default.
• W2093529471 cites W2029926580 @default.
• W2093529471 cites W2079854164 @default.
• W2093529471 cites W2086478855 @default.
• W2093529471 cites W2098115494 @default.
• W2093529471 cites W2101981609 @default.
• W2093529471 cites W2102343006 @default.
• W2093529471 cites W2105934661 @default.
• W2093529471 cites W2123116982 @default.
• W2093529471 cites W2123940107 @default.
• W2093529471 cites W2126202478 @default.
• W2093529471 cites W2132600099 @default.
• W2093529471 cites W2147119488 @default.
• W2093529471 cites W2157098139 @default.
• W2093529471 cites W2160444846 @default.
• W2093529471 cites W2163837020 @default.
• W2093529471 cites W2166317254 @default.
• W2093529471 cites W2167349853 @default.
• W2093529471 cites W2174784159 @default.
• W2093529471 cites W2176150232 @default.
• W2093529471 cites W2179584279 @default.
• W2093529471 cites W3147864287 @default.
• W2093529471 cites W4242642094 @default.
• W2093529471 cites W4327494016 @default.
• W2093529471 doi "https://doi.org/10.2151/jmsj.2014-607" @default.
• W2093529471 hasPublicationYear "2014" @default.
• W2093529471 type Work @default.
• W2093529471 sameAs 2093529471 @default.
• W2093529471 citedByCount "18" @default.
• W2093529471 countsByYear W20935294712015 @default.
• W2093529471 countsByYear W20935294712016 @default.
• W2093529471 countsByYear W20935294712017 @default.
• W2093529471 countsByYear W20935294712018 @default.
• W2093529471 countsByYear W20935294712019 @default.
• W2093529471 countsByYear W20935294712020 @default.
• W2093529471 countsByYear W20935294712021 @default.
• W2093529471 countsByYear W20935294712023 @default.
• W2093529471 crossrefType "journal-article" @default.
• W2093529471 hasAuthorship W2093529471A5071194157 @default.
• W2093529471 hasBestOaLocation W20935294711 @default.
• W2093529471 hasConcept C105795698 @default.
• W2093529471 hasConcept C106131492 @default.
• W2093529471 hasConcept C11413529 @default.
• W2093529471 hasConcept C115961682 @default.
• W2093529471 hasConcept C119898033 @default.
• W2093529471 hasConcept C140779682 @default.
• W2093529471 hasConcept C153294291 @default.
• W2093529471 hasConcept C154945302 @default.
• W2093529471 hasConcept C157286648 @default.
• W2093529471 hasConcept C178650346 @default.
• W2093529471 hasConcept C205649164 @default.
• W2093529471 hasConcept C206833254 @default.
• W2093529471 hasConcept C24552861 @default.
• W2093529471 hasConcept C31972630 @default.
• W2093529471 hasConcept C33923547 @default.
• W2093529471 hasConcept C41008148 @default.
• W2093529471 hasConcept C45374587 @default.
• W2093529471 hasConcept C79334102 @default.
• W2093529471 hasConcept C83042196 @default.
• W2093529471 hasConcept C99498987 @default.
• W2093529471 hasConceptScore W2093529471C105795698 @default.
• W2093529471 hasConceptScore W2093529471C106131492 @default.
• W2093529471 hasConceptScore W2093529471C11413529 @default.
• W2093529471 hasConceptScore W2093529471C115961682 @default.
• W2093529471 hasConceptScore W2093529471C119898033 @default.
• W2093529471 hasConceptScore W2093529471C140779682 @default.
• W2093529471 hasConceptScore W2093529471C153294291 @default.
• W2093529471 hasConceptScore W2093529471C154945302 @default.
• W2093529471 hasConceptScore W2093529471C157286648 @default.
• W2093529471 hasConceptScore W2093529471C178650346 @default.
• W2093529471 hasConceptScore W2093529471C205649164 @default.
• W2093529471 hasConceptScore W2093529471C206833254 @default.
• W2093529471 hasConceptScore W2093529471C24552861 @default.
• W2093529471 hasConceptScore W2093529471C31972630 @default.
• W2093529471 hasConceptScore W2093529471C33923547 @default.
• W2093529471 hasConceptScore W2093529471C41008148 @default.
• W2093529471 hasConceptScore W2093529471C45374587 @default.
• W2093529471 hasConceptScore W2093529471C79334102 @default.
• W2093529471 hasConceptScore W2093529471C83042196 @default.
• W2093529471 hasConceptScore W2093529471C99498987 @default.
• W2093529471 hasIssue "6" @default.

• next