Invention:
This software includes a method designed to evaluate forecast skill at sub-seasonal to seasonal (S2S) time scale, combining traditional evaluation methods and image processing approaches.
A demonstration of this technology for the Arabian Peninsula is described in: Risanto, C.B., Chang, HI., Luong, T.M. et al. Retrospective sub-seasonal forecasts of extreme precipitation events in the Arabian Peninsula using convective-permitting modeling. Clim Dyn (2022). https://doi.org/10.1007/s00382-022-06336-8.
Background:
Extreme weather events such as heavy precipitation, flash flooding, and heat waves, are becoming more intense globally. More reliable forecast systems are needed for early warning of extreme weather events, such as heavy precipitation, flash flooding, and heat waves. Climate changes are challenging societal resilience and economies. Improved extended weather models and forecasting are needed to mitigate risk and to inform infrastructure needs.
Applications:
- Accumulated precipitation
- Weather forecasting
- Sub-seasonal forecast evaluations
- Climate forecasting
- Resilience analysis
Advantages:
- Increased reliability for extreme weather forecasting
- Extended forecast times
- Large-scale regional applicability
