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Revealing dominant patterns of aerosol regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations

Li, Jingmin and Righi, Mattia and Hendricks, Johannes and Beer, Christof Gerhard and Burkhardt, Ulrike and Schmidt, Anja (2024) Revealing dominant patterns of aerosol regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations. Atmospheric Chemistry and Physics (ACP), 24, pp. 12727-12747. Copernicus Publications. doi: 10.5194/acp-24-12727-2024. ISSN 1680-7316.

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Official URL: https://acp.copernicus.org/articles/24/12727/2024/

Abstract

Aerosols play an important role in the Earth system, but their impact on cloud properties and the resulting radiative forcing of climate remains highly uncertain. The large temporal and spatial variability of a number of aerosol properties and the choice of different “preindustrial” reference years prevent a concise understanding of their impacts on clouds and radiation. In this study, we characterize the spatial patterns and long-term evolution of lower tropospheric aerosols (in terms of regimes) by clustering multiple instead of single aerosol properties from preindustrial times to the year 2050 under three different Shared Socioeconomic Pathway (SSP) scenarios. The clustering is based on a combination of statistic-based machine learning algorithms and output from emissions-driven global aerosol model simulations, which do not consider the effects of climate change. Our analysis suggests that in comparison with the present-day case, lower tropospheric aerosol regimes during preindustrial times are mostly represented by regimes of comparatively clean conditions, where marked differences between the years 1750 and 1850 emerge due to the growing influence of agriculture and other anthropogenic activities in 1850. Key aspects of the spatial distribution and extent of the aerosol regimes identified in year 2050 differ compared to preindustrial and present-day conditions, with significant variations resulting from the emission scenario investigated. In 2050, the low-emission SSP1-1.9 scenario is the only scenario where the spatial distribution and extent of the aerosol regimes very closely resemble preindustrial conditions, where the similarity is greater compared to 1850 than 1750. The aerosol regimes for 2050 under SSP3-7.0 closely resemble present-day conditions, but there are some notable regional differences: developed countries tend to shift towards cleaner conditions in future, while the opposite is the case for developing countries. The aerosol regimes for 2050 under SSP2-4.5 represent an intermediate stage between preindustrial times and present-day conditions. Further analysis indicates a north–south difference in the clean background regime during preindustrial times and close resemblance of preindustrial aerosol conditions in the marine regime to present-day conditions in the Southern Hemispheric ocean. Not considering the effects of climate change is expected to cause uncertainties in the size and extent of the identified aerosol regimes but not the general regime patterns. This is due to a dominating influence of emissions rather than climate change in most cases. The approach and findings of this study can be used for designing targeted measurements of different preindustrial-like conditions and for tailored air pollution mitigation measures in specific regions.

Item URL in elib:https://elib.dlr.de/208739/
Document Type:Article
Title:Revealing dominant patterns of aerosol regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Li, JingminDLR, IPAhttps://orcid.org/0000-0002-4434-0029UNSPECIFIED
Righi, MattiaDLR, IPAhttps://orcid.org/0000-0003-3827-5950UNSPECIFIED
Hendricks, JohannesDLR, IPAUNSPECIFIEDUNSPECIFIED
Beer, Christof GerhardDLR, IPAhttps://orcid.org/0000-0003-3815-0007UNSPECIFIED
Burkhardt, UlrikeDLR, IPAhttps://orcid.org/0000-0002-0742-7176UNSPECIFIED
Schmidt, AnjaDLR, IPAhttps://orcid.org/0000-0001-8759-2843UNSPECIFIED
Date:15 November 2024
Journal or Publication Title:Atmospheric Chemistry and Physics (ACP)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:24
DOI:10.5194/acp-24-12727-2024
Page Range:pp. 12727-12747
Publisher:Copernicus Publications
ISSN:1680-7316
Status:Published
Keywords:aerosol regimes, global aerosol modelling, preindustrial aerosol, SSP scenarios, K-means algorithm, Random Forest algorithm, machine learning
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - MoDa - Models and Data for Future Mobility_Supporting Services
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Atmospheric Physics > Earth System Modelling
Deposited By: Li, Jingmin
Deposited On:18 Nov 2024 09:53
Last Modified:18 Nov 2024 09:53

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