Bayesian posterior predictive return levels for environmental extremes L Fawcett, AC Green Stochastic environmental research and risk assessment 32, 2233-2252, 2018 | 22 | 2018 |
Precipitation extremes in 2023 HJ Fowler, S Blenkinsop, A Green, PA Davies Nature Reviews Earth & Environment, 1-3, 2024 | 8 | 2024 |
A framework for space–time modelling of rainfall events for hydrological applications of weather radar AC Green, C Kilsby, A Bárdossy Journal of Hydrology 630, 130630, 2024 | 6 | 2024 |
A decision support toolkit to inform road safety investment decisions J Matthews, K Newman, A Green, L Fawcett, N Thorpe, K Kremer Proceedings of the Institution of Civil Engineers–Municipal Engineer 172 (1 …, 2019 | 6 | 2019 |
Bayesian inference for solar flare extremes B Griffiths, L Fawcett, AC Green Space Weather 20 (3), e2021SW002886, 2022 | 1 | 2022 |
Unravelling the Complex Interplay between Daily and Sub-Daily Rainfall Extremes in Different Climates SB Guerreiro, S Blenkinsop, E Lewis, D Pritchard, AC Green, HJ Fowler Available at SSRN 4749709, 0 | 1* | |
Unveiling global sub-daily precipitation extremes: Insights and development of the INTENSE Project H Fowler, A Green, E Lewis, D Pritchard, S Blenkinsop, LP Velasquez, ... EGU24, 2024 | | 2024 |
Assessing rainfall radar errors with an inverse stochastic modelling framework AC Green, C Kilsby, A Bárdossy Available at SSRN 4478761, 2024 | | 2024 |
Quantifying the uncertainty corresponding to the radar rainfall estimation process: an inverse model for radar attenuation error A Green, C Kilsby, A Bardossy EGU General Assembly Conference Abstracts, EGU-14569, 2023 | | 2023 |
Improving radar rainfall estimation for flood risk using Monte Carlo ensemble simulation AC Green Newcastle University, 2022 | | 2022 |
A Framework for Incorporating Rainfall Data into a Flooding Digital Twin AC Green, E Lewis, X Tong, R Wardle Available at SSRN 4737831, 0 | | |