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Registro Completo |
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
09/01/2002 |
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Data da última atualização: |
16/03/2023 |
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Autoria: |
JONES, P. G.; THORNTON, P. K. |
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Afiliação: |
CIAT. |
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Título: |
MarkSim:software to generate daily weather data for latin america and Africa. |
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Ano de publicação: |
2000 |
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Fonte/Imprenta: |
Agronomy Journal, v.92, n.3, p.445-453, 2000. |
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Idioma: |
Inglês |
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Conteúdo: |
A software package to generate daily weather data for Latin America and Africa is described. The program is based on a stochastic weather generator that uses a third-order Markov process to model daily weather data. The model has been fitted to data from more than 9200 stations with long runs of daily data throughout the world. The climate normals for these stations were assembled into 664 groups using a clustering algorithm. For each of these groups, rainfall model parameters are predicted from monthly means of rainfall, air temperature, diurnal temperature range, and station elevation and latitude. The program identifies the cluster relevant to any required point using interpolated climate surfaces at a resolution of 10 min of arc (18 km2) and evaluates the model parameters for that point. The application currently contains surfaces for Latin America and Africa, and other regions will later be added. Use of the software is demonstrated by generating daily weather data files for running one of the DSSAT crop models. |
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Thesagro: |
Clima. |
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Categoria do assunto: |
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Marc: |
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100 1 $aJONES, P. G.
245 $aMarkSim$bsoftware to generate daily weather data for latin america and Africa.$h[electronic resource]
260 $c2000
520 $aA software package to generate daily weather data for Latin America and Africa is described. The program is based on a stochastic weather generator that uses a third-order Markov process to model daily weather data. The model has been fitted to data from more than 9200 stations with long runs of daily data throughout the world. The climate normals for these stations were assembled into 664 groups using a clustering algorithm. For each of these groups, rainfall model parameters are predicted from monthly means of rainfall, air temperature, diurnal temperature range, and station elevation and latitude. The program identifies the cluster relevant to any required point using interpolated climate surfaces at a resolution of 10 min of arc (18 km2) and evaluates the model parameters for that point. The application currently contains surfaces for Latin America and Africa, and other regions will later be added. Use of the software is demonstrated by generating daily weather data files for running one of the DSSAT crop models.
650 $aClima
700 1 $aTHORNTON, P. K.
773 $tAgronomy Journal$gv.92, n.3, p.445-453, 2000.
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