Search Results for author: Duncan Watson-Parris

Found 7 papers, 3 papers with code

AODisaggregation: toward global aerosol vertical profiles

1 code implementation6 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.

Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific

no code implementations28 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).

Emulating Aerosol Microphysics with Machine Learning

no code implementations22 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.

NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations

1 code implementation13 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.


Detecting anthropogenic cloud perturbations with deep learning

no code implementations29 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.

Cumulo: A Dataset for Learning Cloud Classes

1 code implementation5 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.

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