1k citations · 1.1k across the 4 of their papers we have counts for
4 papers
Stochastic Downscaling to Chaotic Weather Regimes using Spatially Conditioned Gaussian Random Fields with Adaptive Covariance
Rachel Prudden, Niall Robinson, Peter Challenor +1
Downscaling aims to link the behaviour of the atmosphere at fine scales to properties measurable at coarser scales, and has the potential to provide high resolution information at…
Skillful Precipitation Nowcasting using Deep Generative Models of Radar
Suman Ravuri, Karel Lenc, Matthew Willson +17
Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socio-economic needs of many sectors reliant on weather-de…
A review of radar-based nowcasting of precipitation and applicable machine learning techniques
Rachel Prudden, Samantha Adams, Dmitry Kangin +4
A 'nowcast' is a type of weather forecast which makes predictions in the very short term, typically less than two hours - a period in which traditional numerical weather prediction…
A Practical Approach to Spatiotemporal Data Compression
Niall H. Robinson, Rachel Prudden, Alberto Arribas
Datasets representing the world around us are becoming ever more unwieldy as data volumes grow. This is largely due to increased measurement and modelling resolution, but the probl…