FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3171537893> ?p ?o ?g. }

• W3171537893 abstract "Studies have shown advantages of the hybrid ensemble-variational data assimilation (DA) algorithms over pure ensemble or variational algorithms, although such advantages at the convective scale, in the presence of complex ice microphysics and for radar data assimilation, have not yet been clearly demonstrated, if the advantages do exist. A hybrid ensemble-3DVar (En3DVar) system is developed recently based on the ARPS 3DVar and EnKF systems at the Center for Analysis and Prediction of Storms (CAPS). In this dissertation, hybrid En3DVar is compared with 3DVar, EnKF, and pure En3DVar for radar DA through observing system simulation experiments (OSSEs) under both perfect and imperfect model assumptions. It is also applied to a real case including multiple tornadic supercells. For the real case, radar radial velocity and reflectivity data are assimilated every 5 minutes for 1 hour that is followed by short-term forecasts. DfEnKF that updates a single deterministic background forecast using the EnKF updating algorithm is introduced to have an algorithm-wise parallel comparison between EnKF and pure En3DVar. In the perfect-model OSSEs, DfEnKF and pure En3DVar are compared and are found to perform differently when using the same localization radii. The serial (EnKF) versus global (pure En3DVar) nature of the algorithms, and direct filter update (EnKF) versus variational minimization (En3DVar) are the major reasons for the differences. Hybrid En3DVar for radar DA is also compared with 3DVar, EnKF, DfEnKF, and pure En3DVar. Experiments are conducted first to obtain the optimal configurations for different algorithms before they are compared; the optimal configurations include the optimal background decorrelation scales for 3DVar, optimal localization radii for EnKF, DfEnKF, and pure En3DVar, as well as the optimal hybrid weights for hybrid En3DVar. When the algorithms are tuned optimally, hybrid En3DVar does not outperform EnKF or pure En3DVar, although their analyses are all much better than 3DVar. When ensemble background error covariance is a good estimation of the true error distribution, pure ensemble-based DA methods can do a good job, and the advantage of including static background error covariance B in hybrid DA is not obvious.In the imperfect-model OSSEs, model errors are introduced by using different microphysical schemes in the truth run (Lin scheme) and in the ensemble forecasts (WSM6 scheme). Experiments are conducted to obtain the optimal configurations for different algorithms, similar to those in perfect-model OSSEs. Hybrid En3DVar is then found to outperform EnKF and pure En3DVar (3DVar) for better capturing the hail analyses below the freezing level (intensity of the storm). The advantage of hybrid En3DVar over pure ensemble-based methods is most obvious when ensemble background errors are systematically underestimated. In addition, the impact of adding a mass continuity constraint in 3DVar, pure and hybrid En3DVar is also examined. Overall, adding the mass continuity constraint improving the analyses by…" @default.
• W3171537893 created "2021-06-22" @default.
• W3171537893 creator A5089649629 @default.
• W3171537893 date "2017-01-01" @default.
• W3171537893 modified "2023-09-23" @default.
• W3171537893 title "HYBRID EN3DVAR RADAR DATA ASSIMILATION AND COMPARISONS WITH 3DVAR AND ENKF WITH OSSES AND A REAL CASE" @default.
• W3171537893 hasPublicationYear "2017" @default.
• W3171537893 type Work @default.
• W3171537893 sameAs 3171537893 @default.
• W3171537893 citedByCount "0" @default.
• W3171537893 crossrefType "journal-article" @default.
• W3171537893 hasAuthorship W3171537893A5089649629 @default.
• W3171537893 hasConcept C11413529 @default.
• W3171537893 hasConcept C119898033 @default.
• W3171537893 hasConcept C153294291 @default.
• W3171537893 hasConcept C154945302 @default.
• W3171537893 hasConcept C157286648 @default.
• W3171537893 hasConcept C205649164 @default.
• W3171537893 hasConcept C206833254 @default.
• W3171537893 hasConcept C24552861 @default.
• W3171537893 hasConcept C39432304 @default.
• W3171537893 hasConcept C41008148 @default.
• W3171537893 hasConcept C554190296 @default.
• W3171537893 hasConcept C76155785 @default.
• W3171537893 hasConcept C79334102 @default.
• W3171537893 hasConceptScore W3171537893C11413529 @default.
• W3171537893 hasConceptScore W3171537893C119898033 @default.
• W3171537893 hasConceptScore W3171537893C153294291 @default.
• W3171537893 hasConceptScore W3171537893C154945302 @default.
• W3171537893 hasConceptScore W3171537893C157286648 @default.
• W3171537893 hasConceptScore W3171537893C205649164 @default.
• W3171537893 hasConceptScore W3171537893C206833254 @default.
• W3171537893 hasConceptScore W3171537893C24552861 @default.
• W3171537893 hasConceptScore W3171537893C39432304 @default.
• W3171537893 hasConceptScore W3171537893C41008148 @default.
• W3171537893 hasConceptScore W3171537893C554190296 @default.
• W3171537893 hasConceptScore W3171537893C76155785 @default.
• W3171537893 hasConceptScore W3171537893C79334102 @default.
• W3171537893 hasLocation W31715378931 @default.
• W3171537893 hasOpenAccess W3171537893 @default.
• W3171537893 hasPrimaryLocation W31715378931 @default.
• W3171537893 hasRelatedWork W1981154177 @default.
• W3171537893 hasRelatedWork W1983882727 @default.
• W3171537893 hasRelatedWork W1988097696 @default.
• W3171537893 hasRelatedWork W1990088363 @default.
• W3171537893 hasRelatedWork W2031745599 @default.
• W3171537893 hasRelatedWork W2083824439 @default.
• W3171537893 hasRelatedWork W2100902913 @default.
• W3171537893 hasRelatedWork W2119670763 @default.
• W3171537893 hasRelatedWork W2156221689 @default.
• W3171537893 hasRelatedWork W2352203084 @default.
• W3171537893 hasRelatedWork W2740328455 @default.
• W3171537893 hasRelatedWork W2763359318 @default.
• W3171537893 hasRelatedWork W2771424845 @default.
• W3171537893 hasRelatedWork W2954554765 @default.
• W3171537893 hasRelatedWork W3034139443 @default.
• W3171537893 hasRelatedWork W3087124796 @default.
• W3171537893 hasRelatedWork W3106780918 @default.
• W3171537893 hasRelatedWork W3145553695 @default.
• W3171537893 hasRelatedWork W3197153656 @default.
• W3171537893 hasRelatedWork W3143325713 @default.
• W3171537893 isParatext "false" @default.
• W3171537893 isRetracted "false" @default.
• W3171537893 magId "3171537893" @default.
• W3171537893 workType "article" @default.