| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | mtc-m16d.sid.inpe.br |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP7W/3E9B8AF |
| Repository | sid.inpe.br/mtc-m19/2013/06.09.02.20.10 (restricted access) |
| Last Update | 2013:07.08.11.52.53 (UTC) administrator |
| Metadata Repository | sid.inpe.br/mtc-m19/2013/06.09.02.20.11 |
| Metadata Last Update | 2021:01.02.22.17.32 (UTC) administrator |
| DOI | 10.1007/s00382-013-1779-8 |
| ISSN | 0930-7575 |
| Label | scopus |
| Citation Key | RodriguesDoblCoel:2014:MuCaCo |
| Title | Multi-model calibration and combination of tropical seasonal sea surface temperature forecasts  |
| Year | 2014 |
| Access Date | 2024, Apr. 24 |
| Type of Work | journal article |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 2138 KiB |
| 2. Context | |
| Author | 1 Rodrigues, L. R. L. 2 Doblas-Reyes, F. J. 3 Coelho, Caio Augusto dos Santos |
| Group | 1 2 3 DOP-CPT-INPE-MCTI-GOV-BR |
| Affiliation | 1 Institut Català de Ciències del Clima (IC3), Doctor Trueta 203, Barcelona, 08005, Spain 2 Institut Català de Ciències del Clima (IC3), Doctor Trueta 203, Barcelona, 08005, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, 08010, Spain 3 Centro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais (CPTEC/INPE), Rodovia Presidente Dutra Km 40, Cachoeira Paulista, 12630-000, Brazil |
| Author e-Mail Address | 1 luis.rodrigues@ic3.cat 2 3 caio.coelho@cptec.inpe.br |
| e-Mail Address | marcelo.pazos@inpe.br |
| Journal | Climate Dynamics |
| Volume | 42 |
| Number | 3-4 |
| Pages | 597-616 |
| Secondary Mark | A1_CIÊNCIAS_BIOLÓGICAS_I A1_INTERDISCIPLINAR A1_CIÊNCIAS_AMBIENTAIS A1_BIODIVERSIDADE A1_GEOCIÊNCIAS A2_ASTRONOMIA_/_FÍSICA A2_ENGENHARIAS_I B1_CIÊNCIA_DA_COMPUTAÇÃO |
| History (UTC) | 2014-01-14 11:04:42 :: administrator -> marcelo.pazos@sid.inpe.br :: 2013 2014-01-14 15:36:48 :: marcelo.pazos@sid.inpe.br -> administrator :: 2013 -> in press 2014-06-02 12:02:56 :: administrator :: in press -> 2014 2021-01-02 22:17:32 :: administrator -> marcelo.pazos@inpe.br :: 2014 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Version Type | publisher |
| Keywords | seasonal prediction |
| Abstract | Different combination methods based on multiple linear regression are explored to identify the conditions that lead to an improvement of seasonal forecast quality when individual operational dynamical systems and a statistical-empirical system are combined. A calibration of the post-processed output is included. The combination methods have been used to merge the ECMWF System 4, the NCEP CFSv2, the Météo-France System 3, and a simple statistical model based on SST lagged regression. The forecast quality was assessed from a deterministic and probabilistic point of view. SSTs averaged over three different tropical regions have been considered: the Niño3.4, the Subtropical Northern Atlantic and Western Tropical Indian SST indices. The forecast quality of these combinations is compared to the forecast quality of a simple multi-model (SMM) where all single models are equally weighted. The results show a large range of behaviours depending on the start date, target month and the index considered. Outperforming the SMM predictions is a difficult task for linear combination methods with the samples currently available in an operational context. The difficulty in the robust estimation of the weights due to the small samples available is one of the reasons that limit the potential benefit of the combination methods that assign unequal weights. However, these combination methods showed the capability to improve the forecast reliability and accuracy in a large proportion of cases. For example, the Forecast Assimilation method proved to be competitive against the SMM while the other combination methods outperformed the SMM when only a small number of forecast systems have skill. Therefore, the weighting does not outperform the SMM when the SMM is very skilful, but it reduces the risk of low skill situations that are found when several single forecast systems have a low skill. |
| Area | MET |
| Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDOP > Multi-model calibration and... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| Language | en |
| User Group | administrator marcelo.pazos@inpe.br self-uploading-INPE-MCTI-GOV-BR |
| Visibility | shown |
| Archiving Policy | denypublisher denyfinaldraft12 |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Linking | Trabalho não Vinculado à Tese/Dissertação |
| Mirror Repository | iconet.com.br/banon/2006/11.26.21.31 |
| Next Higher Units | 8JMKD3MGPCW/43SQKNE |
| Dissemination | WEBSCI; PORTALCAPES; AGU; COMPENDEX; SCOPUS. |
| Host Collection | sid.inpe.br/mtc-m19@80/2009/08.21.17.02 |
| 6. Notes | |
| Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup resumeid rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject targetfile tertiarytype url |
| 7. Description control | |
| e-Mail (login) | marcelo.pazos@inpe.br |
| update | |