8 citations · 39 across the 15 of their papers we have counts for
5 papers · 1 filter
Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) Clouds
Kenza Tazi, Emiliano Díaz Salas-Porras, Ashwin Braude +5
Pyrocumulonimbus (pyroCb) clouds are storm clouds generated by extreme wildfires. PyroCbs are associated with unpredictable, and therefore dangerous, wildfire spread. They can also…
Identifying the Causes of Pyrocumulonimbus (PyroCb)
Emiliano Díaz Salas-Porras, Kenza Tazi, Ashwin Braude +5
A first causal discovery analysis from observational data of pyroCb (storm clouds generated from extreme wildfires) is presented. Invariant Causal Prediction was used to develop to…
Abstract error analysis for Cahn--Hilliard type equations with dynamic boundary conditions
Paula Harder
This work addresses the problem of solving the Cahn-Hilliard equation numerically. For that we introduce an abstract formulation for Cahn-Hilliard type equations with dynamic bound…
Hard-Constrained Deep Learning for Climate Downscaling
Paula Harder, Alex Hernandez-Garcia, Venkatesh Ramesh +5
The availability of reliable, high-resolution climate and weather data is important to inform long-term decisions on climate adaptation and mitigation and to guide rapid responses…
Physics-Informed Learning of Aerosol Microphysics
Paula Harder, Duncan Watson-Parris, Philip Stier +3
Aerosol particles play an important role in the climate system by absorbing and scattering radiation and influencing cloud properties. They are also one of the biggest sources of u…