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| Registros recuperados : 29 | |
| 15. |  | MAIA, A. H. N.; MEINKE, H.; LENNOX, S.; STONE, R. Inferential, nonparametric statistics to assess the quality of probabilistic forecast systems. Monthly Weather Review, Boston, v. 135, n. 2, p. 351-362, 2007.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 17. | | VAN OORT, P. A. J.; ZHANG, T.; VRIES, M. E. de; HEINEMANN, A. B.; MEINKE, H. Correlation between temperature and phenology prediction error in rice (Oryza sativa L.). Agricultural and Forest Meteorology, Amsterdam, v. 151, n. 12, p. 1545-1555, Dec. 2011.| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 19. | | GOYNE, P. J.; MEINKE, H.; MILROY, S. P.; HAMMER, G. L.; HARE, J. M. Development and use of a barley crop simulation model to evaluate production management strategies in north-eastern Australia. Australian Journal of Agricultural Research, Melbourne, v. 47, n. 7, p. 997-1015, 1996.| Biblioteca(s): Embrapa Trigo. |
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| 20. | | DONALD, L.; MEINKE, H.; POWER, B.; WHEELER, M.; MAIA, A. de H. N.; WHITE, N.; STONE, R.; RIBBE, J. Intra-seasonal climate prediction: linking weather and climate forecasts. In: INTERNATIONAL CONFERENCE ON SOUTHERN HEMISPHERE METEOROLOGY AND OCEANOGRAPHY, 8., 2006, Foz do Iguaçu,PR. [Anais?]. Foz do Iguaçu,PR: ICSHMO, 2006. p. 553-555.| Biblioteca(s): Embrapa Meio Ambiente. |
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| Registros recuperados : 29 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
28/05/2015 |
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Data da última atualização: |
19/08/2015 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MAIA, A. de H. N.; MEINKE, H.; LENNOX, S.; STONE, R. |
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Afiliação: |
ALINE DE HOLANDA NUNES MAIA, CNPMA; H. MEINKE, Queensland Department of Primary lndustries and Fisheries, P.O. Box 102, Toowoomba, Australia, Qld 4350.; S. LENNOX, Queensland Department of Primary lndustries and Fisheries, P.O. Box 102, Toowoomba, Australia, Qld 4350.; R. STONE, Queensland Department of Primary lndustries and Fisheries, P.O. Box 102, Toowoomba, Australia, Qld 4350. |
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Título: |
P-Values as analytical tools in probabilistic forecast assessments. |
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Ano de publicação: |
2005 |
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Fonte/Imprenta: |
In: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 14., 2005, Campinas/SP. Agrometeorologia, agroclimatologia e agronegócio. Campinas/SP: CBAgro, 2005. p. 1-2. |
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Idioma: |
Inglês |
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Conteúdo: |
Much has been written about ?quality? of probabilistic forecasts. Often, providers and users of such forecasts are unclear about what ?quality? entails, leading to confusion and misinformation. Here we try to provide some guidance and suggest a general approach to communicate aspects of probabilistic forecast quality related to discriminatory ability (DA) and skill (S). In our opinion, these two components of forecast quality should be considered independently. DA represents the additional knowledge about future states arising from some forecast system (FS) over and above the total variability of the prognostic variable while S quantifies changes in the agreement between observed and predicted values when using a specific FS instead of a FS based on ?climatology? only. The major concerns are: generally poor distinction between DA and S; inappropriate use of significance testing to quantify DA and use of DA and S measures that do not account for the series lengths and/or number of classes of the FS. To address all of these issues, we propose the use of p-values derived from non-parametric tests as direct measures of DA and S. We illustrate this approach by quantifying DA and S of the Southern Oscillation Index applied to forecasting rainfall across Australia. |
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Palavras-Chave: |
Avaliação da previsão do tempo. |
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Thesaurus NAL: |
Probability analysis; Weather forecasting. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/127011/1/2005AA-007.pdf
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Marc: |
LEADER 01939nam a2200181 a 4500
001 2016658
005 2015-08-19
008 2005 bl uuuu u00u1 u #d
100 1 $aMAIA, A. de H. N.
245 $aP-Values as analytical tools in probabilistic forecast assessments.$h[electronic resource]
260 $aIn: CONGRESSO BRASILEIRO DE AGROMETEOROLOGIA, 14., 2005, Campinas/SP. Agrometeorologia, agroclimatologia e agronegócio. Campinas/SP: CBAgro, 2005. p. 1-2.$c2005
520 $aMuch has been written about ?quality? of probabilistic forecasts. Often, providers and users of such forecasts are unclear about what ?quality? entails, leading to confusion and misinformation. Here we try to provide some guidance and suggest a general approach to communicate aspects of probabilistic forecast quality related to discriminatory ability (DA) and skill (S). In our opinion, these two components of forecast quality should be considered independently. DA represents the additional knowledge about future states arising from some forecast system (FS) over and above the total variability of the prognostic variable while S quantifies changes in the agreement between observed and predicted values when using a specific FS instead of a FS based on ?climatology? only. The major concerns are: generally poor distinction between DA and S; inappropriate use of significance testing to quantify DA and use of DA and S measures that do not account for the series lengths and/or number of classes of the FS. To address all of these issues, we propose the use of p-values derived from non-parametric tests as direct measures of DA and S. We illustrate this approach by quantifying DA and S of the Southern Oscillation Index applied to forecasting rainfall across Australia.
650 $aProbability analysis
650 $aWeather forecasting
653 $aAvaliação da previsão do tempo
700 1 $aMEINKE, H.
700 1 $aLENNOX, S.
700 1 $aSTONE, R.
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