Review of weather and climate forecast-based advisory frameworks for rice-based systems
This report reviews weather and climate forecast-based advisory tools for rice-based agriculture, including WeRise, ORYZA, Climate+, PRiSM, PRiME, PICSA, PRISE, and IRAS. Each tool provides science-based, actionable recommendations to help users anticipate and manage risks associated with climate va...
| Main Authors: | , |
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| Format: | Informe técnico |
| Language: | Inglés |
| Published: |
International Rice Research Institute
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/178803 |
| _version_ | 1855515780063428608 |
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| author | Mabilangan, Abigail Saito, Kazuki |
| author_browse | Mabilangan, Abigail Saito, Kazuki |
| author_facet | Mabilangan, Abigail Saito, Kazuki |
| author_sort | Mabilangan, Abigail |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This report reviews weather and climate forecast-based advisory tools for rice-based agriculture, including WeRise, ORYZA, Climate+, PRiSM, PRiME, PICSA, PRISE, and IRAS. Each tool provides science-based, actionable recommendations to help users anticipate and manage risks associated with climate variability and extreme weather events. The report evaluates their architectures, core algorithms, required weather inputs, and integration potential into AgWise. The findings support a modular, risk-aware, and evidence-driven approach to generating advisories that can be applied not only in rice systems but also adapted for other crops and farming contexts. |
| format | Informe técnico |
| id | CGSpace178803 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | International Rice Research Institute |
| publisherStr | International Rice Research Institute |
| record_format | dspace |
| spelling | CGSpace1788032025-12-15T02:01:42Z Review of weather and climate forecast-based advisory frameworks for rice-based systems Mabilangan, Abigail Saito, Kazuki innovation systems innovation adoption impact scaling up digital agriculture climate models This report reviews weather and climate forecast-based advisory tools for rice-based agriculture, including WeRise, ORYZA, Climate+, PRiSM, PRiME, PICSA, PRISE, and IRAS. Each tool provides science-based, actionable recommendations to help users anticipate and manage risks associated with climate variability and extreme weather events. The report evaluates their architectures, core algorithms, required weather inputs, and integration potential into AgWise. The findings support a modular, risk-aware, and evidence-driven approach to generating advisories that can be applied not only in rice systems but also adapted for other crops and farming contexts. 2025-11-28 2025-12-15T01:15:09Z 2025-12-15T01:15:09Z Report https://hdl.handle.net/10568/178803 en Open Access application/pdf International Rice Research Institute Mabilangan, A. and Saito, K. 2025. Review of Weather and Climate Forecast‑Based Advisory Frameworks for Rice-based Systems. CGIAR Sustainable Farming Science Program Report | AoW 2.1.1 Evaluating Weather Advisory Tools for AgWise Integration: International Rice Research Institute, Los Baños, Philippines. 19 p. |
| spellingShingle | innovation systems innovation adoption impact scaling up digital agriculture climate models Mabilangan, Abigail Saito, Kazuki Review of weather and climate forecast-based advisory frameworks for rice-based systems |
| title | Review of weather and climate forecast-based advisory frameworks for rice-based systems |
| title_full | Review of weather and climate forecast-based advisory frameworks for rice-based systems |
| title_fullStr | Review of weather and climate forecast-based advisory frameworks for rice-based systems |
| title_full_unstemmed | Review of weather and climate forecast-based advisory frameworks for rice-based systems |
| title_short | Review of weather and climate forecast-based advisory frameworks for rice-based systems |
| title_sort | review of weather and climate forecast based advisory frameworks for rice based systems |
| topic | innovation systems innovation adoption impact scaling up digital agriculture climate models |
| url | https://hdl.handle.net/10568/178803 |
| work_keys_str_mv | AT mabilanganabigail reviewofweatherandclimateforecastbasedadvisoryframeworksforricebasedsystems AT saitokazuki reviewofweatherandclimateforecastbasedadvisoryframeworksforricebasedsystems |