Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

Generative models provide a well‐established statistical framework for evaluating
uncertainty and deriving conclusions from large data sets especially in the presence of …

Rapidly expanding cities in the Middle Eastern and North African (MENA) region are at risk
of flooding due to heavy rainfall, insufficient drainage capacity, a lack of preparedness and …

The most common approaches to detection and attribution (D&A) of extreme weather events
using fraction of attributable risk or risk ratio answer a particular form of research question …

One difficulty for real‐time tracking of epidemics is related to reporting delay. The reporting
delay may be due to laboratory confirmation, logistical problems, infrastructure difficulties …

Due to the non-cognition of real-time data, rare loss-based risk warning methods can
effectively respond to unexpected emergencies. Machine learning has powerful data …

Forecasting the weather is an increasingly data-intensive exercise. Numerical weather
prediction (NWP) models are becoming more complex, with higher resolutions, and there …

Comparisons between anomaly and full-field methods have been carried out in weather
analysis and forecasting over the last decade. Evidence from these studies has …

Despite the significant progress in probabilistic forecasting science in the last two decades,
particularly in the quantification of predictive uncertainty (PU), most operational flood early …

Abstract Flash Flood Guidance (FFG) is a rainfall threshold which initiates flooding in
streams. It merely provides a binary output (yes or no) which has large uncertainties in …