Submitted as: development and technical paper 21 Dec 2020
Submitted as: development and technical paper | 21 Dec 2020
Physically Regularized Machine Learning Emulators of Aerosol Activation
- 1Pacific Northwest National Laboratory, Richland, WA
- 2ClimaCell, Boston, MA
- 1Pacific Northwest National Laboratory, Richland, WA
- 2ClimaCell, Boston, MA
Abstract. The activation of aerosol into cloud droplets is an important step in the formation of clouds, and strongly influences the radiative budget of the Earth. Explicitly simulating aerosol activation in Earth system models is challenging due to the computational complexity required to resolve the necessary chemical and physical processes and their interactions. As such, various parameterizations have been developed to approximate these details at reduced computational cost and accuracy. Here, we explore how machine learning emulators can be used to bridge this gap in computational cost and parameterization accuracy. We evaluate a set of emulators of a detailed cloud parcel model using physically regularized machine learning regression techniques. We find that the emulators can reproduce the parcel model at higher accuracy than many existing parameterizations. Furthermore, physical regularization tends to improve emulator accuracy, most significantly when emulating very low activation fractions. This work demonstrates the value of physical constraints in machine learning model development and enables the implementation of improved hybrid physical-machine learning models of aerosol activation into next generation Earth system models.
Sam J. Silva et al.


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SC1: 'Comment on gmd-2020-393', Sami Romakkaniemi, 07 Jan 2021
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AC3: 'Reply on SC1', Sam Silva, 26 Mar 2021
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AC3: 'Reply on SC1', Sam Silva, 26 Mar 2021
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RC1: 'Review', Anonymous Referee #1, 07 Jan 2021
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AC1: 'Reply on RC1', Sam Silva, 26 Mar 2021
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AC1: 'Reply on RC1', Sam Silva, 26 Mar 2021
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RC2: 'Referee Comment', Anonymous Referee #2, 15 Jan 2021
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AC2: 'Reply on RC2', Sam Silva, 26 Mar 2021
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AC2: 'Reply on RC2', Sam Silva, 26 Mar 2021
Sam J. Silva et al.
Data sets
Data for Silva et al. Activation Emulators Sam J. Silva https://doi.org/10.5281/zenodo.4319145
Sam J. Silva et al.
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