Paul Fox-Hughes

Paul Fox-Hughes

End-user
About
Paul Fox-Hughes

Project leadership

This project examined the use of detailed land surface models, satellite measurements and ground-based observations for the monitoring and prediction of landscape dryness. The research team developed a standalone prototype land surface modelling system, called Joint UK Land Environment Simulator based Australian Soil Moisture Information (JASMIN) to produce daily soil moisture analyses at 5km resolution and 4 soil layers. Verification against ground-based soil moisture observations shows that this prototype system is significantly more skilful than both the Keetch–Byram Drought Index and Soil Dryness Index. This project also aimed to improve applications such as fire danger mapping that may require soil moisture information at higher spatial resolution due to the large spatial variability of soil moisture in the landscape, and developed a simple yet skilful model to predict live fuel moisture content for the whole of Australia.
This project is part of the Black Summer research program funded by the Commonwealth Government through the 10-year extension of funding into natural hazard research in Australia.

Lead end user

This project is using high-resolution modelling, together with a range of meteorological data, to better understand and predict important meteorological natural hazards, including fire weather, tropical cyclones, severe thunderstorms and heavy rainfall. The outcomes from the project will contribute to reducing the impact and cost of these hazards on people, infrastructure, the economy and the environment.
Research team:
This project examined the use of detailed land surface models, satellite measurements and ground-based observations for the monitoring and prediction of landscape dryness. The research team developed a standalone prototype land surface modelling system, called Joint UK Land Environment Simulator based Australian Soil Moisture Information (JASMIN) to produce daily soil moisture analyses at 5km resolution and 4 soil layers. Verification against ground-based soil moisture observations shows that this prototype system is significantly more skilful than both the Keetch–Byram Drought Index and Soil Dryness Index. This project also aimed to improve applications such as fire danger mapping that may require soil moisture information at higher spatial resolution due to the large spatial variability of soil moisture in the landscape, and developed a simple yet skilful model to predict live fuel moisture content for the whole of Australia.

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