A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
<p>Efficient methods for predicting weather-related hazards are crucial for the effective management of environmental risk. Many environmental hazards depend on the evolution of meteorological conditions over protracted periods, requiring assessments that account for evolving conditions. The T...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-11-01
|
| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/17/8353/2024/gmd-17-8353-2024.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850268348040871936 |
|---|---|
| author | E. Black E. Black J. Ellis R. I. Maidment R. I. Maidment R. I. Maidment |
| author_facet | E. Black E. Black J. Ellis R. I. Maidment R. I. Maidment R. I. Maidment |
| author_sort | E. Black |
| collection | DOAJ |
| description | <p>Efficient methods for predicting weather-related hazards are crucial for the effective management of environmental risk. Many environmental hazards depend on the evolution 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 agricultural decision support. The model presented here, General 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, functionality 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.</p> |
| format | Article |
| id | doaj-art-c43e467bf28d4532b3eff82188fe7430 |
| institution | OA Journals |
| issn | 1991-959X 1991-9603 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj-art-c43e467bf28d4532b3eff82188fe74302025-08-20T01:53:30ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032024-11-01178353837210.5194/gmd-17-8353-2024A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1E. Black0E. Black1J. Ellis2R. I. Maidment3R. I. Maidment4R. I. Maidment5Department of Meteorology, University of Reading, Reading, RG6 6BB, UKNational Centre for Atmospheric Science, Leeds, LS2 9PH, UKDepartment of Computer Science, University of Warwick, Coventry, CV4 7AL, UKDepartment of Meteorology, University of Reading, Reading, RG6 6BB, UKNational Centre for Atmospheric Science, Leeds, LS2 9PH, UKNational Centre for Earth Observation, Leicester, LE4 5SP, UK<p>Efficient methods for predicting weather-related hazards are crucial for the effective management of environmental risk. Many environmental hazards depend on the evolution 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 agricultural decision support. The model presented here, General 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, functionality 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.</p>https://gmd.copernicus.org/articles/17/8353/2024/gmd-17-8353-2024.pdf |
| spellingShingle | E. Black E. Black J. Ellis R. I. Maidment R. I. Maidment R. I. Maidment A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 Geoscientific Model Development |
| title | A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 |
| title_full | A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 |
| title_fullStr | A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 |
| title_full_unstemmed | A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 |
| title_short | A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1 |
| title_sort | computationally lightweight model for ensemble forecasting of environmental hazards general tamsat alert v1 2 1 |
| url | https://gmd.copernicus.org/articles/17/8353/2024/gmd-17-8353-2024.pdf |
| work_keys_str_mv | AT eblack acomputationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT eblack acomputationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT jellis acomputationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT rimaidment acomputationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT rimaidment acomputationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT rimaidment acomputationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT eblack computationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT eblack computationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT jellis computationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT rimaidment computationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT rimaidment computationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 AT rimaidment computationallylightweightmodelforensembleforecastingofenvironmentalhazardsgeneraltamsatalertv121 |