skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud‐Forming Particles
Title: Machine Learning Uncovers Aerosol Size Information From Chemistry and Meteorology to Quantify Potential Cloud‐Forming Particles
Abstract Cloud condensation nuclei (CCN) are mediators of aerosol‐cloud interactions, which contribute to the largest uncertainty in climate change prediction. Here, we present a machine learning (ML)/artificial intelligence (AI) model that quantifies CCN from model‐simulated aerosol composition, atmospheric trace gas, and meteorological variables. Comprehensive multi‐campaign airborne measurements, covering varied physicochemical regimes in the troposphere, confirm the validity of and help probe the inner workings of this ML model: revealing for the first time that different ranges of atmospheric aerosol composition and mass correspond to distinct aerosol number size distributions. ML extracts this information, important for accurate quantification of CCN, additionally from both chemistry and meteorology. This can provide a physicochemically explainable, computationally efficient, robust ML pathway in global climate models that only resolve aerosol composition; potentially mitigating the uncertainty of effective radiative forcing due to aerosol‐cloud interactions (ERFaci) and improving confidence in assessment of anthropogenic contributions and climate change projections.  more » « less
Award ID(s):
1650786
PAR ID:
10375027
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  more » ;  ;  ;  ;  ;  ;  ;   « less
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Geophysical Research Letters
Volume:
48
Issue:
21
ISSN:
0094-8276
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; (, Geophysical Research Letters)
    Abstract The effect of aerosols on the properties of clouds is a large source of uncertainty in predictions of weather and climate. These aerosol‐cloud interactions depend critically on the ability of aerosol particles to form cloud droplets. A challenge in modeling aerosol‐cloud interactions is the representation of interactions between turbulence and cloud microphysics. Turbulent mixing leads to small‐scale fluctuations in water vapor and temperature that are unresolved in large‐scale atmospheric models. To quantify the impact of turbulent fluctuations on cloud condensation nuclei (CCN) activation, we used a high‐resolution Large Eddy Simulation of a convective cloud chamber to drive particle‐based cloud microphysics simulations. We show small‐scale fluctuations strongly impact CCN activity. Once activated, the relatively long timescales of evaporation compared to fluctuations causes droplets to persist in subsaturated regions, which further increases droplet concentrations. 
    more » « less
  2. ; ; ; ; ; ; (, Atmospheric Chemistry and Physics)
    Abstract. Nitrate (NO3-) aerosol is projected to increase dramatically in the coming decades and may become the dominant inorganic particle species. This is due to the continued strong decrease in SO2 emissions, which is not accompanied by a corresponding decrease in NOx and especially NH3 emissions. Thus, the radiative effect (RE) of NO3- aerosol may become more important than that of SO42- aerosol in the future. The physicochemical interactions of mineral dust particles with gas and aerosol tracers play an important role in influencing the overall RE of dust and non-dust aerosols but can be a major source of uncertainty due to their lack of representation in many global climate models. Therefore, this study investigates how and to what extent dust affects the current global NO3- aerosol radiative effect through both radiation (REari) and cloud interactions (REaci) at the top of the atmosphere (TOA). For this purpose, multiyear simulations nudged towards the observed atmospheric circulation were performed with the global atmospheric chemistry and climate model EMAC, while the thermodynamics of the interactions between inorganic aerosols and mineral dust were simulated with the thermodynamic equilibrium model ISORROPIA-lite. The emission flux of the mineral cations Na+, Ca2+, K+, and Mg2+ is calculated as a fraction of the total aeolian dust emission based on the unique chemical composition of the major deserts worldwide. Our results reveal positive and negative shortwave and longwave radiative effects in different regions of the world via aerosol–radiation interactions and cloud adjustments. Overall, the NO3- aerosol direct effect contributes a global cooling of −0.11 W m−2, driven by fine-mode particle cooling at short wavelengths. Regarding the indirect effect, it is noteworthy that NO3- aerosol exerts a global mean warming of +0.17 W m−2. While the presence of NO3- aerosol enhances the ability of mineral dust particles to act as cloud condensation nuclei (CCN), it simultaneously inhibits the formation of cloud droplets from the smaller anthropogenic particles. This is due to the coagulation of fine anthropogenic CCN particles with the larger nitrate-coated mineral dust particles, which leads to a reduction in total aerosol number concentration. This mechanism results in an overall reduced cloud albedo effect and is thus attributed as warming. 
    more » « less
  3. ; ; (, Journal of Climate)
    Abstract The aerosol indirect effect (AIE) dominates uncertainty in total anthropogenic aerosol forcing in phase 6 of the Coupled Model Intercomparison Project (CMIP6) models. AIE strength depends on meteorological conditions that have been shown to change between preindustrial (PI) and present-day (PD) climates, such as cloud cover and atmospheric moisture. Hence, AIE strength may depend on background climate state, impacting the dependence of model-based AIE estimates on experiment design or the evolution of AIE strength with intensifying climate change, which has not previously been explicitly evaluated. Using atmosphere-only simulations with prescribed observed sea surface temperatures (SSTs) and sea ice in the National Center for Atmospheric Research (NCAR) Community Earth System Model 2, version 2.1.3 (CESM2), Community Atmosphere Model, version 6.0 (CAM6), model, we impose a PD (2000) aerosol perturbation onto a PI (1850), PD, and PD with a uniform 4 K increase in the SST (PD + 4 K) background climate to assess the dependence of the total aerosol effective radiative forcing (ERF) and AIE on background climate. We find statistically insignificant increases in aerosol ERF when estimated in the different background climates, almost entirely from increases in direct ERF but with some regionally significant compensating signals in PD + 4 K. The absence of an AIE dependence on background climate in our PD simulation may be tied to documented differences in cloud responses to the observed SSTs used in our simulations versus SSTs produced by the fully coupled models from which most cloud feedback studies are derived, known as the “pattern effect.” Our findings indicate that AIE and aerosol forcing overall may not have a strong dependence on the background climate state in the near future but could regionally under extreme climate change. Significance StatementDiverse model representations of aerosol–cloud interactions strongly contribute to uncertainty in historical anthropogenic aerosol forcing and are associated with uncertainty in climate sensitivity. This study aims to highlight the dependence of aerosol indirect effects on the background climate state in Community Earth System Model 2, version 2.1.3 (CESM2), Community Atmosphere Model, version 6.0 (CAM6), by identifying microphysical and meteorological changes between aerosol-driven atmospheric responses in present-day and preindustrial climate states to understand anthropogenic aerosol-driven forcing more thoroughly. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, Proceedings of the National Academy of Sciences)
    Anthropogenic ammonia (NH3) emissions have significantly increased in recent decades due to enhanced agricultural activities, contributing to global air pollution. While the effects of NH3on surface air quality are well documented, its influence on particle dynamics in the upper troposphere-lower stratosphere (UTLS) and related aerosol impacts remain unquantified. NH3reaches the UTLS through convective transport and can enhance new particle formation (NPF). This modeling study evaluates the global impact of anthropogenic NH3on UTLS particle formation and quantifies its effects on aerosol loading and cloud condensation nuclei (CCN) abundance. We use the EMAC Earth system model, incorporating multicomponent NPF parameterizations from the CERN CLOUD experiment. Our simulations reveal that convective transport increases NH3-driven NPF in the UTLS by one to three orders of magnitude compared to a baseline scenario without anthropogenic NH3, causing a doubling of aerosol numbers over high-emission regions. These aerosol changes induce a 2.5-fold increase in upper tropospheric CCN concentrations. Anthropogenic NH3emissions increase the relative contribution of water-soluble inorganic ions to the UTLS aerosol optical depth (AOD) by 20% and increase total column AOD by up to 80%. In simulations without anthropogenic NH3, UTLS aerosol composition is dominated by sulfate and organic species, with a marked reduction in ammonium nitrate and aerosol water content. This results in a decline of aerosol mass concentration by up to 50%. These findings underscore the profound global influence of anthropogenic NH3emissions on UTLS particle formation, AOD, and CCN production, with important implications for cloud formation and climate. 
    more » « less
  5. ; ; ; (, Geophysical Research Letters)
    Abstract The abundance and sources of ice‐nucleating particles, particles required for heterogeneous ice nucleation, are long‐standing sources of uncertainty in quantifying aerosol‐cloud interactions. In this study, we demonstrate near closure between immersion freezing ice‐nucleating particle number concentration (nINPs) observations andnINPscalculated from simulated sea spray aerosol and dust. The Community Atmospheric Model with constrained meteorology was used to simulate aerosol concentrations at the Mace Head Research Station (North Atlantic) and over the Southern Ocean to the south of Tasmania (Clouds, Aerosols, Precipitation, Radiation, and atmospherIc Composition Over the southeRN ocean campaign). Model‐predictednINPswere within a factor of 10 ofnINPsobserved with an off‐line ice spectrometer at Mace Head Research Station and Clouds, Aerosols, Precipitation, Radiation, and atmospherIc Composition Over the southeRN ocean campaign, for 93% and 69% of observations, respectively. Simulated vertical profiles ofnINPsreveal that transported dust may be critical tonINPsin remote regions and that sea spray aerosol may be the dominate contributor to primary ice nucleation in Southern Ocean low‐level mixed‐phase clouds. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email