Black, E. ORCID: https://orcid.org/0000-0003-1344-6186, Ellis, J. and Maidment, R. I.
ORCID: https://orcid.org/0000-0003-2054-3259
(2024)
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1.
Geoscientific Model Development, 17 (22).
pp. 8353-8372.
ISSN 1991-9603
doi: 10.5194/gmd-17-8353-2024
Abstract/Summary
Efficient methods for predicting weather-related hazards are crucial for the effective management of environ- mental risk. Many environmental hazards depend on the evo- lution of meteorological conditions over protracted periods, requiring assessments that account for evolving conditions. The TAMSAT-ALERT approach addresses this challenge by combining observational monitoring with a weighted multi-year ensemble. In this way, it enhances the utility of existing systems by enabling users to combine multiple streams of monitoring and meteorological forecasting data into holistic hazard assessments. TAMSAT-ALERT forecasts are now used in a number of regions in the Global South for soil moisture forecasting, drought early warning and agri- cultural decision support. The model presented here, Gen- eral TAMSAT-ALERT, represents a significant scientific and functional advance on previous implementations. Notably, General TAMSAT-ALERT is applicable to any variable for which time series data are available. In addition, function- ality has been introduced to account for climatological non- stationarity (for example due to climate change), large-scale modes of variability (for example El Niño) and persistence (for example of land-surface conditions). In this paper, we present a full description of the model, along with case studies of its application to the prediction of central England temperature, Pakistan vegetation conditions and African precipitation.
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Item Type | Article |
URI | https://reading-clone.eprints-hosting.org/id/eprint/119735 |
Item Type | Article |
Refereed | Yes |
Divisions | Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology |
Publisher | European Geosciences Union |
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