| 1. Identity statement | |
| Reference Type | Book Section |
| Site | plutao.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP3W/45U87QL |
| Repository | sid.inpe.br/plutao/2021/12.09.15.12 |
| Metadata Repository | sid.inpe.br/plutao/2021/12.09.15.12.28 |
| Metadata Last Update | 2022:04.03.19.23.53 (UTC) administrator |
| DOI | 10.1007/978-3-030-77722-7_8 |
| ISBN | 9783030777227 |
| Label | lattes: 2306964700488382 28 SatterfieldWKHHEMMFISMHJLMELBYLRSMMTMB:2021:ApMeRa |
| Citation Key | SatterfieldWKHHEMMFISMHJLMELBYLBRSMMTM:2021:ApMeRa |
| Title | Statistical Parameter Estimation for Observation Error Modelling: Application to Meteor Radars  |
| Year | 2021 |
| Access Date | 2024, May 23 |
| Secondary Type | PRE LI |
| 2. Context | |
| Author | 1 Satterfield, Elizabeth A. 2 Waller, Joanne A. 3 Kuhl, David D. 4 Hodyss, Dan 5 Hoppel, Karl W. 6 Eckermann, Stephen D. 7 McCormack, John P. 8 Ma, Jun 9 Fritts, David C 10 Iimura, Hiroiyuki 11 Stober, Gunter 12 Meek, Chris E. 13 Hall, Chris 14 Jacobi, Christoph 15 Latteck, Ralph 16 Mitchell, Nicholas J. 17 Espy, Patrick J. 18 Li, Guozhu 19 Brown, Peter 20 Yi, Wen 21 Li, Na 22 Batista, Paulo Prado 23 Reid, Ian 24 Sunkara, Eswaraiah 25 Moffat-Griffin, Tracy 26 Murphy, Damian 27 Tsutsumi, Masaki 28 Marino, John |
| Resume Identifier | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 8JMKD3MGP5W/3C9JJ3H |
| Group | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 DIHPA-CGCE-INPE-MCTI-GOV-BR |
| Affiliation | 1 U.S. Naval Research Laboratory 2 Met Office 3 U.S. Naval Research Laboratory 4 U.S. Naval Research Laboratory 5 U.S. Naval Research Laboratory 6 U.S. Naval Research Laboratory 7 U.S. Naval Research Laboratory 8 CPI 9 GATS 10 GATS 11 GATS 12 University of Saskatchewan 13 University of Tromsø 14 University of Leipzig 15 University of Rostock 16 University of Bath 17 Norwegian University of Science and Technology 18 Chinese Academy of Sciences 19 University of Western Ontario 20 University of Science and Technology of China 21 China Research Institute of Radiowave Propagation 22 Instituto Nacional de Pesquisas Espaciais (INPE) 23 The University of Adelaide 24 Chungnam National University 25 British Antarctic Survery 26 Australian Antarctic Division of Sustainability 27 National Institute of Polar Research 28 University of Colorado Boulder |
| Author e-Mail Address | 1 elizabeth.satterfield@nrlmry.navy.mil 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 paulopradobatista@yahoo.com |
| Editor | Park, S. K. Xu, L. |
| Book Title | Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV) |
| Publisher | Springer |
| Pages | 185-213 |
| History (UTC) | 2021-12-14 11:45:19 :: lattes -> administrator :: 2021 2022-04-03 19:23:53 :: administrator -> simone :: 2021 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Keywords | meteor radar data assimilation |
| Abstract | Data assimilation schemes blend observational data, with limited coverage, with a short term forecast to produce an analysis, which is meant to be the best estimate of the current state of the atmosphere. Appropriately specifying observation error statistics is necessary to obtain an optimal analysis. Observation error can originate from instrument error as well as the error of representation. While representation error is most commonly associated with unresolved scales and processes, this term is often considered to include contributions from pre-processing or quality control and errors associated with the observation operator. With a focus on practical operational implementation, this chapter aims to define the components of observation error, discusses their sources and characteristics, and provides an overview of current methods for estimating observation error statistics. We highlight the implicit assumptions of these methods, as well as their shortcomings. We will detail current operational practice for diagnosing observation error and accounting for correlated observation error. Finally, we provide a practical methodology for using these diagnostics, as well as the associated innovation-based observation impact, to optimize the assimilation of meteor radar observations in the upper atmosphere. |
| Area | CEA |
| Arrangement | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCE > Statistical Parameter Estimation... |
| doc Directory Content | there are no files |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| Language | en |
| User Group | lattes |
| Visibility | shown |
| Read Permission | deny from all and allow from 150.163 |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPCW/46KTFK8 |
| URL (untrusted data) | https://link.springer.com/book/10.1007/978-3-030-77722-7 |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Empty Fields | archivingpolicy archivist callnumber city copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition format issn lineage mark mirrorrepository nextedition notes numberoffiles numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor seriestitle session shorttitle size sponsor subject targetfile tertiarymark tertiarytype translator versiontype volume |
| 7. Description control | |
| e-Mail (login) | simone |
| update | |