| bibtype |
J -
Journal Article
|
| ARLID |
0367533 |
| utime |
20240103195854.9 |
| mtime |
20111125235959.9 |
| WOS |
000296475700014 |
| SCOPUS |
84855783419 |
| DOI |
10.1175/2011MWR3586.1 |
| title
(primary) (eng) |
Marginalized Particle Filtering Framework for Tuning of Ensemble Filters |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0254414 |
| ISSN |
0027-0644 |
| title
|
Monthly Weather Review |
| volume_id |
139 |
| volume |
11 (2011) |
| page_num |
3589-3599 |
|
| keyword |
ensemble finter |
| keyword |
marginalized particle filter |
| keyword |
data assimilation |
| author
(primary) |
| ARLID |
cav_un_auth*0101207 |
| name1 |
Šmídl |
| name2 |
Václav |
| full_dept (cz) |
Adaptivní systémy |
| full_dept (eng) |
Department of Adaptive Systems |
| department (cz) |
AS |
| department (eng) |
AS |
| institution |
UTIA-B |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0228606 |
| name1 |
Hofman |
| name2 |
Radek |
| full_dept (cz) |
Adaptivní systémy |
| full_dept |
Department of Adaptive Systems |
| department (cz) |
AS |
| department |
AS |
| institution |
UTIA-B |
| full_dept |
Department of Adaptive Systems |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
VG20102013018 |
| agency |
GA MV |
| ARLID |
cav_un_auth*0265869 |
|
| project |
| project_id |
GP102/08/P250 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0241640 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
Marginalized particle ltering (MPF), also known as Rao-Blackwellized particle filtering has been recently developed as a hybrid method combining analytical lters with particle filters. In this paper, we investigate the prospects of this approach in enviromental modelling where the key concerns are nonlinearity, high-dimensionality, and computational cost. In our formulation, exact marginalization in the MPF is replaced by approximate marginalization yielding a framework for creation of new hybrid lters. In particular, we propose to use the MPF framework for on-line tuning of nuisance parameters of ensemble filters. Strength of the framework is demonstrated on the joint estimation of the inflation factor, the measurement error variance and the length-scale parameter of covariance localization. It is shown that accurate estimation can be achieved with a moderate number of particles. Moreover, this result was achieved with naively chosen proposal densities leaving space for further improvements. |
| reportyear |
2012 |
| RIV |
BB |
| mrcbC52 |
4 A 4a 20231122134755.0 |
| permalink |
http://hdl.handle.net/11104/0202179 |
| mrcbT16-e |
METEOROLOGYATMOSPHERICSCIENCES |
| mrcbT16-f |
3.004 |
| mrcbT16-g |
0.635 |
| mrcbT16-h |
>10.0 |
| mrcbT16-i |
0.0326 |
| mrcbT16-j |
1.418 |
| mrcbT16-k |
16821 |
| mrcbT16-l |
230 |
| mrcbT16-s |
2.835 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
69.237 |
| mrcbT16-C |
75.352 |
| mrcbT16-D |
Q2 |
| mrcbT16-E |
Q1 |
| arlyear |
2011 |
| mrcbTft |
\nSoubory v repozitáři: smidl-0367533.pdf |
| mrcbU14 |
84855783419 SCOPUS |
| mrcbU34 |
000296475700014 WOS |
| mrcbU63 |
cav_un_epca*0254414 Monthly Weather Review 0027-0644 1520-0493 Roč. 139 č. 11 2011 3589 3599 |
|