210 citations · 211 across the 3 of their papers we have counts for
3 papers
Probabilistic Emulation of the Community Radiative Transfer Model Using Machine Learning
Lucas Howard, Aneesh C. Subramanian, Gregory Thompson +2
The continuous improvement in weather forecast skill over the past several decades is largely due to the increasing quantity of available satellite observations and their assimilat…
How is model-related uncertainty quantified and reported in different disciplines?
Emily G. Simmonds, Kwaku Peprah Adjei, Christoffer Wold Andersen +40
How do we know how much we know? Quantifying uncertainty associated with our modelling work is the only way we can answer how much we know about any phenomenon. With quantitative s…
Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model
David John Gagne, Hannah M. Christensen, Aneesh C. Subramanian +1
Stochastic parameterizations account for uncertainty in the representation of unresolved sub-grid processes by sampling from the distribution of possible sub-grid forcings. Some ex…