7 citations · 45 across the 13 of their papers we have counts for
8 papers · 1 filter
Addressing Deep Learning Model Uncertainty in Long-Range Climate Forecasting with Late Fusion
Ken C. L. Wong, Hongzhi Wang, Etienne E. Vos +3
Global warming leads to the increase in frequency and intensity of climate extremes that cause tremendous loss of lives and property. Accurate long-range climate prediction allows…
Controlling Weather Field Synthesis Using Variational Autoencoders
Dario Augusto Borges Oliveira, Jorge Guevara Diaz, Bianca Zadrozny +1
One of the consequences of climate change is anobserved increase in the frequency of extreme cli-mate events. That poses a challenge for weatherforecast and generation algorithms,…
A comparative study of stochastic and deep generative models for multisite precipitation synthesis
Jorge Guevara, Dario Borges, Campbell Watson +1
Future climate change scenarios are usually hypothesized using simulations from weather generators. However, there only a few works comparing and evaluating promising deep learning…
Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network
Daniel Salles Civitarese, Daniela Szwarcman, Bianca Zadrozny +1
An impact of climate change is the increase in frequency and intensity of extreme precipitation events. However, confidently predicting the likelihood of extreme precipitation at s…
Decadal Forecasts with ResDMD: a Residual DMD Neural Network
Eduardo Rodrigues, Bianca Zadrozny, Campbell Watson +1
Operational forecasting centers are investing in decadal (1-10 year) forecast systems to support long-term decision making for a more climate-resilient society. One method that has…
Reduced order modeling of dynamical systems using artificial neural networks applied to water circulation
Alberto Costa Nogueira, João Lucas de Sousa Almeida, Guillaume Auger +1
General circulation models are essential tools in weather and hydrodynamic simulation. They solve discretized, complex physical equations in order to compute evolutionary states of…