Method that improved area selection and consistently enhance forecast skill.
Two statistical models were used to evaluate the seasonal forecasts: Canonical Correlation Analysis (CCA) implemented in CPT, and Multiple Factorial Analysis (MFA), which allows integrating several regions or several predictors simultaneously. Using the results from the teleconnection analysis, fore...
| Autor principal: | |
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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
| Publicado: |
2017
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/123221 |
| _version_ | 1855523775361056768 |
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| author | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| author_browse | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| author_facet | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| author_sort | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Two statistical models were used to evaluate the seasonal forecasts: Canonical Correlation Analysis (CCA) implemented in CPT, and Multiple Factorial Analysis (MFA), which allows integrating several regions or several predictors simultaneously. Using the results from the teleconnection analysis, forecast skill in Colombia for the period form 1982-2013 was assessed. |
| format | Informe técnico |
| id | CGSpace123221 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| record_format | dspace |
| spelling | CGSpace1232212023-03-14T11:55:19Z Method that improved area selection and consistently enhance forecast skill. CGIAR Research Program on Climate Change, Agriculture and Food Security models development selection rural development analysis systems agrifood systems correlation factorial analysis Two statistical models were used to evaluate the seasonal forecasts: Canonical Correlation Analysis (CCA) implemented in CPT, and Multiple Factorial Analysis (MFA), which allows integrating several regions or several predictors simultaneously. Using the results from the teleconnection analysis, forecast skill in Colombia for the period form 1982-2013 was assessed. 2017-12-31 2022-10-06T14:26:49Z 2022-10-06T14:26:49Z Report https://hdl.handle.net/10568/123221 en Open Access application/pdf CGIAR Research Program on Climate Change, Agriculture and Food Security. 2017. Method that improved area selection and consistently enhance forecast skill. Reported in Climate Change, Agriculture and Food Security Annual Report 2017. Innovations. |
| spellingShingle | models development selection rural development analysis systems agrifood systems correlation factorial analysis CGIAR Research Program on Climate Change, Agriculture and Food Security Method that improved area selection and consistently enhance forecast skill. |
| title | Method that improved area selection and consistently enhance forecast skill. |
| title_full | Method that improved area selection and consistently enhance forecast skill. |
| title_fullStr | Method that improved area selection and consistently enhance forecast skill. |
| title_full_unstemmed | Method that improved area selection and consistently enhance forecast skill. |
| title_short | Method that improved area selection and consistently enhance forecast skill. |
| title_sort | method that improved area selection and consistently enhance forecast skill |
| topic | models development selection rural development analysis systems agrifood systems correlation factorial analysis |
| url | https://hdl.handle.net/10568/123221 |
| work_keys_str_mv | AT cgiarresearchprogramonclimatechangeagricultureandfoodsecurity methodthatimprovedareaselectionandconsistentlyenhanceforecastskill |