Preprints
https://doi.org/10.5194/gmd-2024-75
https://doi.org/10.5194/gmd-2024-75
Submitted as: model description paper
 | 
06 May 2024
Submitted as: model description paper |  | 06 May 2024
Status: this preprint is currently under review for the journal GMD.

A computationally light-weight model for ensemble forecasting of environmental hazard: General TAMSAT-ALERT v1.2.1

Emily Black, John Ellis, and Ross Maidment

Abstract. Efficient methods for predicting weather-related hazards are crucial for stakeholders managing environmental risks. 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 climatological ensemble. As such, it enhances the utility of existing systems by enabling users to combine multiple streams of monitoring and 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 Nino), and persistence (for example of land-surface condition). In this paper, we present a full description of the model, along with case studies of its application to prediction of Central England Temperature, Pakistan vegetation condition and African precipitation.

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Emily Black, John Ellis, and Ross Maidment

Status: open (until 01 Jul 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Emily Black, John Ellis, and Ross Maidment

Model code and software

General TAMSAT-ALERT v1.2.1 John Ellis and Emily Black https://doi.org/10.5281/zenodo.10955490

Interactive computing environment

Demo of General TAMSAT-ALERT v1.2.1 John Ellis and Emily Black https://gws-access.jasmin.ac.uk/public/tamsat/tamsat_alert/gmd_paper/demo.zip

Emily Black, John Ellis, and Ross Maidment

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Short summary
We present General TAMSAT-ALERT: a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and forecasting data into probabilistic hazard assessments. As such, it complements existing systems and enhances their utility for actionable hazard assessment.