Speaker
Description
This paper explores the benefits of integrating Earth Observation (EO) techniques with Artificial Intelligence (AI) to enhance the capabilities of Numerical Weather Prediction (NWP) models, particularly in the context of severe weather and environmental hazards over South Africa. NWP models often employ EO that lacks real-time resolution, which may lead to increased uncertainty in short-term forecasts and reduced reliability during high-impact weather events. EO systems provide high-resolution, near-real-time observations. AI techniques perform post-processing tasks like bias correction, anomaly detection, and pattern recognition. AI also excels at capturing non-linear relationships and fine-scale phenomena that are often poorly resolved in NWP models. This EO-AI integrated approach should improve model forecast accuracy, and detection of localized hazards. We demonstrate the benefits and shortcomings of our approach in detecting hazards such as heat waves, wildfires and wetland degradation.
| Registered for the conference? | Yes |
|---|---|
| Presenting Author | Patience Mulovhedzi |
| Institute | CSIR |
