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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/44KJMJ2
Repositorysid.inpe.br/mtc-m21c/2021/05.04.14.15   (restricted access)
Last Update2021:05.04.14.15.38 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2021/05.04.14.15.38
Metadata Last Update2022:04.03.22.28.36 (UTC) administrator
DOI10.1007/s00703-020-00738-1
ISSN0177-7971
Citation KeyMoretoRolEstVanCho:2021:SuDeSu
TitleSugarcane decision-making support using Eta Model precipitation forecasts
Year2021
MonthApr.
Access Date2024, May 19
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size1572 KiB
2. Context
Author1 Moreto, Victor B.
2 Rolim, Glauco de S.
3 Esteves, João T.
4 Vanuytrecht, Eline
5 Chou, Sin Chan
Group1
2
3
4
5 DIMNT-CGCT-INPE-MCTI-GOV-BR
Affiliation1 Universidade de São Paulo (USP)
2 Universidade de São Paulo (USP)
3 Universidade de São Paulo (USP)
4 Flemish Institute for Technological Research (VITO)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 victor.moreto@hotmail.com
2
3
4
5 chou.sinchan@gmail.com
JournalMeteorology and Atmospheric Physics
Volume133
Number2
Pages181-191
Secondary MarkB1_INTERDISCIPLINAR B1_GEOCIÊNCIAS B1_CIÊNCIAS_AMBIENTAIS B5_ASTRONOMIA_/_FÍSICA
History (UTC)2021-05-04 14:15:38 :: simone -> administrator ::
2021-05-04 14:15:39 :: administrator -> simone :: 2021
2021-05-04 14:16:47 :: simone -> administrator :: 2021
2022-04-03 22:28:36 :: administrator -> simone :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractAgricultural activity is largely influenced by climatic conditions. Rainfall is essential for crop production, and precipitation events also interfere with soil preparation, planting, application of pesticides and harvesting. Weather forecast models are tools to facilitate decision making for agricultural activities, hence high accuracy is desired. Farmers often criticize the accuracy of weather forecasts, which sometimes fail to predict precipitation events, leading to yield loss and environmental harm. In this study, precipitation forecasts of the Eta Model were evaluated for 28 of Brazils most productive sugarcane areas, considering a grid of 15 × 15 km. Using a combination of different indicators of forecast success, observed and forecasted daily precipitation data were compared for consecutive days of all 10-day periods in a course of 6 years (20052010). Skill scores and performance diagrams based on the indicators were used to evaluate the goodness and robustness of the model forecasts. The Eta Model forecasts showed overall accuracies ranging between 55 and 71% for the Atlantic forest biomes (located North-West and South-East of São Paulo) and the Cerrado biomes (located in the Goiás State and in the Center-North São Paulo State), respectively. The forecasts were most reliable for up to 4 days, showing an accuracy of 60%. Forecasts for periods of more than 4 days had an average accuracy of 4050%. The probability of detecting rainfall correctly was the strongest characteristic of Eta Model, with more than 70% hits.
AreaMET
Arrangementurlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Sugarcane decision-making support...
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4. Conditions of access and use
Languageen
Target Filemoreto-sugarcane.pdf
User Groupsimone
Reader Groupadministrator
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Visibilityshown
Archiving Policydenypublisher denyfinaldraft12
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/46KUATE
Citing Item Listsid.inpe.br/bibdigital/2022/04.03.22.23 1
DisseminationWEBSCI; PORTALCAPES; COMPENDEX.
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
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