1 code implementation • 14 Jul 2023 • Shahine Bouabid, Dino Sejdinovic, Duncan Watson-Parris
The result is an emulator that (i) enjoys the flexibility of statistical machine learning models and can learn from observations, and (ii) has a robust physical grounding with interpretable parameters that can be used to make inference about the climate system.
1 code implementation • 6 Dec 2022 • William Yik, Sam J. Silva, Andrew Geiss, Duncan Watson-Parris
We also find no significant difference in prediction speed between networks with standard feedforward dense layers and those with randomly wired layers.
no code implementations • 22 Nov 2022 • Kenza Tazi, Emiliano Díaz Salas-Porras, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, Nis Meinert
The pipeline's first two components, a pyroCb database and a pyroCb forecast model, are presented.
no code implementations • 16 Nov 2022 • Emiliano Díaz Salas-Porras, Kenza Tazi, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, Nis Meinert
A first causal discovery analysis from observational data of pyroCb (storm clouds generated from extreme wildfires) is presented.
no code implementations • 24 Jul 2022 • Paula Harder, Duncan Watson-Parris, Philip Stier, Dominik Strassel, Nicolas R. Gauger, Janis Keuper
The original M7 model is used to generate data of input-output pairs to train a neural network on it.
1 code implementation • 6 May 2022 • Shahine Bouabid, Duncan Watson-Parris, Sofija Stefanović, Athanasios Nenes, Dino Sejdinovic
In this work, we develop a framework for the vertical disaggregation of AOD into extinction profiles, i. e. the measure of light extinction throughout an atmospheric column, using readily available vertically resolved meteorological predictors such as temperature, pressure or relative humidity.
no code implementations • 28 Oct 2021 • Andrew Jesson, Peter Manshausen, Alyson Douglas, Duncan Watson-Parris, Yarin Gal, Philip Stier
Aerosol-cloud interactions include a myriad of effects that all begin when aerosol enters a cloud and acts as cloud condensation nuclei (CCN).
no code implementations • 22 Sep 2021 • Paula Harder, Duncan Watson-Parris, Dominik Strassel, Nicolas Gauger, Philip Stier, Janis Keuper
This is done in the ECHAM-HAM global climate aerosol model using the M7 microphysics model, but increased computational costs make it very expensive to run at higher resolutions or for a longer time.
no code implementations • 17 Dec 2020 • Christian Schroeder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski
Extreme precipitation events, such as violent rainfall and hail storms, routinely ravage economies and livelihoods around the developing world.
1 code implementation • 13 Nov 2020 • Paula Harder, William Jones, Redouane Lguensat, Shahine Bouabid, James Fulton, Dánell Quesada-Chacón, Aris Marcolongo, Sofija Stefanović, Yuhan Rao, Peter Manshausen, Duncan Watson-Parris
The recent explosion in applications of machine learning to satellite imagery often rely on visible images and therefore suffer from a lack of data during the night.
no code implementations • 29 Nov 2019 • Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony Caterini, Dino Sejdinovic, Philip Stier
One of the most pressing questions in climate science is that of the effect of anthropogenic aerosol on the Earth's energy balance.
1 code implementation • 5 Nov 2019 • Valentina Zantedeschi, Fabrizio Falasca, Alyson Douglas, Richard Strange, Matt J. Kusner, Duncan Watson-Parris
One of the greatest sources of uncertainty in future climate projections comes from limitations in modelling clouds and in understanding how different cloud types interact with the climate system.