Articles | Volume 11, issue 6
https://doi.org/10.5194/gmd-11-2353-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-2353-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
19 Jun 2018
Model description paper |
| 19 Jun 2018
| 19 Jun 2018
TAMSAT-ALERT v1: a new framework for agricultural decision support
Dagmawi Asfaw
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
Emily Black
Department of Meteorology, University of Reading, Reading, UK
Matthew Brown
Department of Atmospheric, Oceanic and Planetary Physics, University
of Oxford, Oxford, UK
Kathryn Jane Nicklin
School of Earth and Environment, University of Leeds, Leeds, UK
Frederick Otu-Larbi
Ghana Meteorological Agency, Accra, Ghana
Ewan Pinnington
Department of Meteorology, University of Reading, Reading, UK
Andrew Challinor
School of Earth and Environment, University of Leeds, Leeds, UK
Ross Maidment
Department of Meteorology, University of Reading, Reading, UK
Tristan Quaife
Department of Meteorology, University of Reading, Reading, UK
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Cited
23 citations as recorded by crossref.
- An Improved Climatological Forecast Method for Projecting End-of-Season Water Requirement Satisfaction Index W. Turner et al. 10.1175/JHM-D-21-0184.1
- Detecting agricultural drought risks: A case study of the rice crop (Oryza sativa) and the TAMSAT‐ALERT system in Guyana D. David 10.1002/met.2149
- Evaluation and Mapping of Rainfall Erosivity from Tamsat Satellite Data in the Sanaga River Basin (Srb) in Nachtigal, Cameroon (Central Africa) H. Zobo Mbele et al. 10.2139/ssrn.4188421
- TOQO: A new Tillage Operations Quality Optimization model based on parallel and dynamic Decision Support System H. Fawzi et al. 10.1016/j.jclepro.2021.128263
- Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data E. Pinnington et al. 10.5194/hess-25-1617-2021
- Re-prioritizing climate services for agriculture: Insights from Bangladesh S. Mason et al. 10.1016/j.cliser.2022.100306
- A comprehensive analysis of the advances in Indian Digital Agricultural architecture A. Balkrishna et al. 10.1016/j.atech.2023.100318
- Rainfall Variability and Trends over the African Continent Using TAMSAT Data (1983–2020): Towards Climate Change Resilience and Adaptation N. Alahacoon et al. 10.3390/rs14010096
- Translating seasonal climate forecasts into water balance forecasts for decision making D. MacLeod et al. 10.1371/journal.pclm.0000138
- Water security in sub‐Saharan Africa: Understanding the status of sustainable development goal 6 E. Nkiaka et al. 10.1002/wat2.1552
- A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 E. Black et al. 10.5194/gmd-17-8353-2024
- Application of TAMSAT-ALERT soil moisture forecasts for planting date decision support in Africa E. Black et al. 10.3389/fclim.2022.993511
- An Information-Theoretic Approach to Reconciling Historical Climate Observations and Impacts on Agriculture M. Mauerman et al. 10.1175/WCAS-D-22-0019.1
- Investigating the performance of high-resolution subseasonal precipitation forecasts in support of food insecurity early warning W. Turner et al. 10.1088/2752-5295/adcadf
- Evaluation and validation of TAMSAT‐ALERT soil moisture and WRSI for use in drought anticipatory action V. Boult et al. 10.1002/met.1959
- Cocoa plant productivity in West Africa under climate change: a modelling and experimental study E. Black et al. 10.1088/1748-9326/abc3f3
- From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management V. Saiz-Rubio & F. Rovira-Más 10.3390/agronomy10020207
- A new drought model for disaster risk management in the Punjab, Sindh and Baluchistan provinces of Pakistan E. Black et al. 10.3389/fclim.2024.1332233
- Development of a 10-km resolution global soil profile dataset for crop modeling applications E. Han et al. 10.1016/j.envsoft.2019.05.012
- Impact-based seasonal rainfall forecasting to trigger early action for droughts T. Busker et al. 10.1016/j.scitotenv.2023.165506
- A Novel Taxonomy for Risks in Agribusiness Supply Chains: A Systematic Literature Review S. Imbiri et al. 10.3390/su13169217
- Lessons from integrated seasonal forecast-crop modelling in Africa: A systematic review S. Mkuhlani et al. 10.1515/biol-2022-0507
- TAMSAT-ALERT v1: a new framework for agricultural decision support D. Asfaw et al. 10.5194/gmd-11-2353-2018
21 citations as recorded by crossref.
- An Improved Climatological Forecast Method for Projecting End-of-Season Water Requirement Satisfaction Index W. Turner et al. 10.1175/JHM-D-21-0184.1
- Detecting agricultural drought risks: A case study of the rice crop (Oryza sativa) and the TAMSAT‐ALERT system in Guyana D. David 10.1002/met.2149
- Evaluation and Mapping of Rainfall Erosivity from Tamsat Satellite Data in the Sanaga River Basin (Srb) in Nachtigal, Cameroon (Central Africa) H. Zobo Mbele et al. 10.2139/ssrn.4188421
- TOQO: A new Tillage Operations Quality Optimization model based on parallel and dynamic Decision Support System H. Fawzi et al. 10.1016/j.jclepro.2021.128263
- Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data E. Pinnington et al. 10.5194/hess-25-1617-2021
- Re-prioritizing climate services for agriculture: Insights from Bangladesh S. Mason et al. 10.1016/j.cliser.2022.100306
- A comprehensive analysis of the advances in Indian Digital Agricultural architecture A. Balkrishna et al. 10.1016/j.atech.2023.100318
- Rainfall Variability and Trends over the African Continent Using TAMSAT Data (1983–2020): Towards Climate Change Resilience and Adaptation N. Alahacoon et al. 10.3390/rs14010096
- Translating seasonal climate forecasts into water balance forecasts for decision making D. MacLeod et al. 10.1371/journal.pclm.0000138
- Water security in sub‐Saharan Africa: Understanding the status of sustainable development goal 6 E. Nkiaka et al. 10.1002/wat2.1552
- A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 E. Black et al. 10.5194/gmd-17-8353-2024
- Application of TAMSAT-ALERT soil moisture forecasts for planting date decision support in Africa E. Black et al. 10.3389/fclim.2022.993511
- An Information-Theoretic Approach to Reconciling Historical Climate Observations and Impacts on Agriculture M. Mauerman et al. 10.1175/WCAS-D-22-0019.1
- Investigating the performance of high-resolution subseasonal precipitation forecasts in support of food insecurity early warning W. Turner et al. 10.1088/2752-5295/adcadf
- Evaluation and validation of TAMSAT‐ALERT soil moisture and WRSI for use in drought anticipatory action V. Boult et al. 10.1002/met.1959
- Cocoa plant productivity in West Africa under climate change: a modelling and experimental study E. Black et al. 10.1088/1748-9326/abc3f3
- From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management V. Saiz-Rubio & F. Rovira-Más 10.3390/agronomy10020207
- A new drought model for disaster risk management in the Punjab, Sindh and Baluchistan provinces of Pakistan E. Black et al. 10.3389/fclim.2024.1332233
- Development of a 10-km resolution global soil profile dataset for crop modeling applications E. Han et al. 10.1016/j.envsoft.2019.05.012
- Impact-based seasonal rainfall forecasting to trigger early action for droughts T. Busker et al. 10.1016/j.scitotenv.2023.165506
- A Novel Taxonomy for Risks in Agribusiness Supply Chains: A Systematic Literature Review S. Imbiri et al. 10.3390/su13169217
Latest update: 29 Oct 2025
Short summary
TAMSAT-ALERT is a framework for combining observational and forecast information into continually updated assessments of the likelihood of user-defined adverse events like low cumulative rainfall or lower than average crop yield. It is easy to use and flexible to accommodate any impact model that uses meteorological data. The results show that it can be used to monitor the meteorological impact on yield within a growing season and to test the value of routinely issued seasonal forecasts.
TAMSAT-ALERT is a framework for combining observational and forecast information into...
