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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 und Righi, Mattia und Hendricks, Johannes und Beer, Christof Gerhard und Burkhardt, Ulrike und 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, Seiten 12727-12747. Copernicus Publications. doi: 10.5194/acp-24-12727-2024. ISSN 1680-7316.

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

Kurzfassung

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.

elib-URL des Eintrags:https://elib.dlr.de/208739/
Dokumentart:Zeitschriftenbeitrag
Titel:Revealing dominant patterns of aerosol regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Li, JingminDLR, IPAhttps://orcid.org/0000-0002-4434-0029NICHT SPEZIFIZIERT
Righi, MattiaDLR, IPAhttps://orcid.org/0000-0003-3827-5950NICHT SPEZIFIZIERT
Hendricks, JohannesDLR, IPANICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Beer, Christof GerhardDLR, IPAhttps://orcid.org/0000-0003-3815-0007NICHT SPEZIFIZIERT
Burkhardt, UlrikeDLR, IPAhttps://orcid.org/0000-0002-0742-7176NICHT SPEZIFIZIERT
Schmidt, AnjaDLR, IPAhttps://orcid.org/0000-0001-8759-2843NICHT SPEZIFIZIERT
Datum:15 November 2024
Erschienen in:Atmospheric Chemistry and Physics (ACP)
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:24
DOI:10.5194/acp-24-12727-2024
Seitenbereich:Seiten 12727-12747
Verlag:Copernicus Publications
ISSN:1680-7316
Status:veröffentlicht
Stichwörter:aerosol regimes, global aerosol modelling, preindustrial aerosol, SSP scenarios, K-means algorithm, Random Forest algorithm, machine learning
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Verkehrssystem
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V VS - Verkehrssystem
DLR - Teilgebiet (Projekt, Vorhaben):V - MoDa - Models and Data for Future Mobility_Supporting Services
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Physik der Atmosphäre > Erdsystem-Modellierung
Hinterlegt von: Li, Jingmin
Hinterlegt am:18 Nov 2024 09:53
Letzte Änderung:18 Nov 2024 09:53

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