Publicação
Using analog ensembles with alternative metrics for hindcasting with multistations
| Resumo: | This study concerns making weather predictions for a location where no data is available, using meteorological datasets from nearby stations. The hindcast with multiple stations is performed with different variants of the Analog Ensemble (AnEn) method. In addition to the traditional Monache metric used to identify analogs in datasets from one or two stations, several new metrics are explored, namely cosine similarity, normalization, and k-means clustering. These were analyzed and benchmarked to find the ones that bring improvements. The best results were obtained with the k-means metric, yielding between 3% and 30% of lower quadratic error when compared against the Monache metric. Also, by making the predictors to include two stations, the performance of the hindcast improved, decreasing the error up to 16%, depending on the correlation between the predictor stations. |
|---|---|
| Autores principais: | Balsa, Carlos |
| Outros Autores: | Rodrigues, Carlos Veiga; Lopes, Isabel Maria; Rufino, José |
| Assunto: | Analog ensembles Metrics Hindcasting Time series Meteorological data |
| Ano: | 2020 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| _version_ | 1867173244967059456 |
|---|---|
| author | Balsa, Carlos |
| author2 | Rodrigues, Carlos Veiga Lopes, Isabel Maria Rufino, José |
| author2_role | author author author |
| author_facet | Balsa, Carlos Rodrigues, Carlos Veiga Lopes, Isabel Maria Rufino, José |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Balsa, Carlos\",\"Person.identifier.orcid\":\"0000-0003-2431-8665\"},{\"Person.name\":\"Rodrigues, Carlos Veiga\"},{\"Person.name\":\"Lopes, Isabel Maria\",\"Person.identifier.orcid\":\"0000-0002-5614-3516\"},{\"Person.name\":\"Rufino, José\",\"Person.identifier.orcid\":\"0000-0002-1344-8264\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Balsa, Carlos Rodrigues, Carlos Veiga Lopes, Isabel Maria Rufino, José |
| datacite.date.Accepted.fl_str_mv | 2020-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-02-16T10:03:53Z |
| datacite.date.embargoed.fl_str_mv | 2023-02-16T10:03:53Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Analog ensembles Metrics Hindcasting Time series Meteorological data |
| datacite.titles.title.fl_str_mv | Using analog ensembles with alternative metrics for hindcasting with multistations |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Balsa, Carlos Rodrigues, Carlos Veiga Lopes, Isabel Maria Rufino, José |
| dc.date.Accepted.fl_str_mv | 2020-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-02-16T10:03:53Z |
| dc.date.embargoed.fl_str_mv | 2023-02-16T10:03:53Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/26978 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Analog ensembles Metrics Hindcasting Time series Meteorological data |
| dc.title.fl_str_mv | Using analog ensembles with alternative metrics for hindcasting with multistations |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | This study concerns making weather predictions for a location where no data is available, using meteorological datasets from nearby stations. The hindcast with multiple stations is performed with different variants of the Analog Ensemble (AnEn) method. In addition to the traditional Monache metric used to identify analogs in datasets from one or two stations, several new metrics are explored, namely cosine similarity, normalization, and k-means clustering. These were analyzed and benchmarked to find the ones that bring improvements. The best results were obtained with the k-means metric, yielding between 3% and 30% of lower quadratic error when compared against the Monache metric. Also, by making the predictors to include two stations, the performance of the hindcast improved, decreasing the error up to 16%, depending on the correlation between the predictor stations. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/feaf52fa-66cf-4ffe-85f8-b25b7c14d78c/download |
| id | ipb_dfcf75333f07b00a7c9e4cfe5e2e5088 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/26978 |
| instacron_str | ipb |
| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/26978 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Balsa, Carlos Balsa, Carlos https://www.ciencia-id.pt/DE1E-2F7A-AAB1 DE1E-2F7A-AAB1 http://orcid.org/0000-0003-2431-8665 0000-0003-2431-8665 Rodrigues, Carlos Veiga Lopes, Isabel Maria Lopes, Isabel Maria https://www.ciencia-id.pt/8812-AE1C-A316 8812-AE1C-A316 http://orcid.org/0000-0002-5614-3516 0000-0002-5614-3516 Rufino, José Rufino, José https://www.ciencia-id.pt/C414-F47F-6323 C414-F47F-6323 http://orcid.org/0000-0002-1344-8264 0000-0002-1344-8264 |
| publishDate | 2020 |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engpt_PTThis study concerns making weather predictions for a location where no data is available, using meteorological datasets from nearby stations. The hindcast with multiple stations is performed with different variants of the Analog Ensemble (AnEn) method. In addition to the traditional Monache metric used to identify analogs in datasets from one or two stations, several new metrics are explored, namely cosine similarity, normalization, and k-means clustering. These were analyzed and benchmarked to find the ones that bring improvements. The best results were obtained with the k-means metric, yielding between 3% and 30% of lower quadratic error when compared against the Monache metric. Also, by making the predictors to include two stations, the performance of the hindcast improved, decreasing the error up to 16%, depending on the correlation between the predictor stations.application/pdfpt_PTUsing analog ensembles with alternative metrics for hindcasting with multistationsPersonalBalsa, CarlosDSpacehttp://dspace.org/items/d0e5ccff-9696-4f4f-9567-8d698a6bf17dDSpacehttp://dspace.org/items/d0e5ccff-9696-4f4f-9567-8d698a6bf17dBalsaCarlosCiência IDhttps://www.ciencia-id.ptDE1E-2F7A-AAB1ORCIDhttp://orcid.org0000-0003-2431-8665Researcher IDhttps://www.researcherid.comM-8735-2013Scopus Author IDhttps://www.scopus.com23391719100Rodrigues, Carlos VeigaPersonalLopes, Isabel MariaDSpacehttp://dspace.org/items/111716db-94a0-4c24-b739-330dc2ae79fcDSpacehttp://dspace.org/items/111716db-94a0-4c24-b739-330dc2ae79fcLopesIsabel MariaCiência IDhttps://www.ciencia-id.pt8812-AE1C-A316ORCIDhttp://orcid.org0000-0002-5614-3516Researcher IDhttps://www.researcherid.comA-1728-2014Scopus Author IDhttps://www.scopus.com55211017300Scopus Author IDhttps://www.scopus.com57190212117Scopus Author IDhttps://www.scopus.com57207843433PersonalRufino, JoséDSpacehttp://dspace.org/items/1e24d2ce-a354-442a-bef8-eebadd94b385DSpacehttp://dspace.org/items/1e24d2ce-a354-442a-bef8-eebadd94b385RufinoJoséCiência IDhttps://www.ciencia-id.ptC414-F47F-6323ORCIDhttp://orcid.org0000-0002-1344-8264Scopus Author IDhttps://www.scopus.com55947199100Scopus Author IDhttps://www.scopus.com57188967176HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptDOIIsPartOfDOI: 10.55969/paradigmplus.v1n2a12023-02-16T10:03:53Z20202020-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/26978http://purl.org/coar/access_right/c_abf2open accessAnalog ensemblesMetricsHindcastingTime seriesMeteorological data790162 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal article2020http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/feaf52fa-66cf-4ffe-85f8-b25b7c14d78c/downloadJournal ParadigmPlus12117 |
| spellingShingle | Using analog ensembles with alternative metrics for hindcasting with multistations Balsa, Carlos Analog ensembles Metrics Hindcasting Time series Meteorological data |
| status | SINGLETON |
| subject.fl_str_mv | Analog ensembles Metrics Hindcasting Time series Meteorological data |
| title | Using analog ensembles with alternative metrics for hindcasting with multistations |
| title_full | Using analog ensembles with alternative metrics for hindcasting with multistations |
| title_fullStr | Using analog ensembles with alternative metrics for hindcasting with multistations |
| title_full_unstemmed | Using analog ensembles with alternative metrics for hindcasting with multistations |
| title_short | Using analog ensembles with alternative metrics for hindcasting with multistations |
| title_sort | Using analog ensembles with alternative metrics for hindcasting with multistations |
| topic | Analog ensembles Metrics Hindcasting Time series Meteorological data |
| topic_facet | Analog ensembles Metrics Hindcasting Time series Meteorological data |
| url | http://hdl.handle.net/10198/26978 |
| visible | 1 |