Preprints
https://doi.org/10.5194/acp-2022-688
https://doi.org/10.5194/acp-2022-688
04 Oct 2022
 | 04 Oct 2022
Status: this preprint was under review for the journal ACP but the revision was not accepted.

Possible evidence of increased global cloudiness due to aerosol-cloud interactions

Alyson Rose Douglas and Tristan L'Ecuyer

Abstract. Aerosol-cloud interactions remain a large source of uncertainty in global climate models due to uncertainty in how pre-industrial clouds, aerosols, and the environment behaved. We employ three machine learning models, a random forest, a stochastic gradient boosting, and an extreme gradient boosting regressor to derive a pre-industrial proxy for warm cloudiness predicted using only their environmental controls. We train our models on boundary layer stability, relative humidity of the free atmosphere, upper level vertical motion, and sea surface temperature to predict a simulated, pristine cloud fraction as a one-for-one proxy for a pre-industrial warm cloud fraction. Using a multivariate linear regression as a proxy for sensitivity studies, we show that the non-linear signatures derived using the simple machine learning models are pivotal in deriving an accurate estimate. We find that aerosols may have increased global cloudiness by 1.27 % since pre-industrial times, leading to −0.42 (0.39–0.46 at 95 % confidence intervals) of cooling. Our methodology reduces the covariability between aerosol, the environment, and cloud adjustments by aiming only to estimate an initial, unperturbed state of the cloud based on the environment alone.

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Alyson Rose Douglas and Tristan L'Ecuyer

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-688', Anonymous Referee #1, 02 Nov 2022
  • RC2: 'Comment on acp-2022-688', Anonymous Referee #2, 03 Nov 2022
  • RC3: 'Comment on acp-2022-688', Anonymous Referee #3, 11 Nov 2022
  • EC1: 'Comment on acp-2022-688', Timothy Garrett, 19 Dec 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-688', Anonymous Referee #1, 02 Nov 2022
  • RC2: 'Comment on acp-2022-688', Anonymous Referee #2, 03 Nov 2022
  • RC3: 'Comment on acp-2022-688', Anonymous Referee #3, 11 Nov 2022
  • EC1: 'Comment on acp-2022-688', Timothy Garrett, 19 Dec 2022
Alyson Rose Douglas and Tristan L'Ecuyer
Alyson Rose Douglas and Tristan L'Ecuyer

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Short summary
Aerosol, or small particles released by human activities, enter the atmosphere and eventually interact with clouds in what we term aerosol-cloud interactions. As more aerosol enter a cloud, they act as cloud droplet nuclei, increasing the number of cloud droplets in a cloud and delaying rain formation, leading to a larger cloud. We use machine learning and found that these interactions lead to 1.27 % more cloudiness on Earth and offset ~1/4 of the warming due to CO2.
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