Aerosol-cloud-climate interactions in the climate model CAM-Oslo

The 1883 Krakatau eruption is one of the most well-known historical volcanic eruptions due to its significant global climate impact as well as first recorded observations of various aerosol associated optical and physical phenomena. Although much work has been done on the former by comparison of global climate model predictions/ simulations with instrumental and proxy climate records, the latter has surprisingly not been studied in similar detail. In particular, there is a wealth of observations of vivid red sunsets, blue suns, and other similar features, that can be used to analyze the spatio-temporal dispersal of volcanic aerosols in summer to winter 1883. Thus, aerosol cloud dispersal after the Krakatau eruption can be estimated, bolstered by aerosol cloud behavior as monitored by satellite-based instrument observations after the 1991 Pinatubo eruption. This is one of a handful of large historic eruptions where this analysis can be done (using non-climate proxy methods). In this study, we model particle trajectories of the Krakatau eruption cloud using the Hysplit trajectory model and compare our results with our compiled observational dataset (principally using Verbeek 1884, the Royal Society report, and Kiessling 1884).In particular, we explore the effect of different atmospheric states - the quasi-biennial oscillation (QBO) which impacts zonal movement of the stratospheric volcanic plume - to estimate the phase of the QBO in 1883 required for a fast-moving westward cloud. Since this alone is unable to match the observed latitudinal spread of the aerosols, we then explore the impact of an&#160; umbrella cloud (2000 km diameter) that almost certainly formed during such a large eruption. A large umbrella cloud, spreading over ~18 degrees within the duration of the climax of the eruption (6-8 hours), can lead to much quicker latitudinal spread than a point source (vent). We will discuss the results of the combined model (umbrella cloud and correct QBO phase) with historical accounts and observations, as well as previous work on the 1991 Pinatubo eruption. We also consider the likely impacts of water on aerosol concentrations and the relevance of this process for eruptions with possible significant seawater interactions, like Krakatau. We posit that the role of umbrella clouds is an under-appreciated, but significant, process for beginning to model the climatic impacts of large volcanic eruptions.

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Toward a New Era of Research in Aerosol/Cloud/Climate Interactions at LLNL

10.2172/792712 ◽

2000 ◽

Author(s):

C Chuang ◽

J Dignon ◽

K Grant ◽

P Connell ◽

D Bergman ◽

...

Keyword(s):

New Era ◽

Aerosol Cloud ◽

Climate Interactions

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Improving the simulation of global aerosol with size-segregated anthropogenic number emissions

10.5194/acp-2017-841 ◽

2017 ◽

Author(s):

Filippo Xausa ◽

Pauli Paasonen ◽

Risto Makkonen ◽

Mikhail Arshinov ◽

Aijun Ding ◽

...

Keyword(s):

Particle Number ◽

Climate Models ◽

Climate Model ◽

Dominant Role ◽

Particle Diameter ◽

Radiation Budget ◽

Size Distributions ◽

Anthropogenic Aerosol ◽

Accumulation Mode ◽

Climate Interactions

Abstract. Climate models are important tools that are used for generating climate change projections, in which aerosol-climate interactions are one of the main sources of uncertainties. In order to quantify aerosol-radiation and aerosol-cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in precompiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently-formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS)-model, where the emission number size distributions vary, for example, with respect to the fuel and technology. A special attention in our analysis was put on accumulation mode particles (particle diameter dp > 100 nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100 nanometers particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol-climate interactions are expected to be affected. Analysis of global particle number concentrations and size distributions reveal that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particle agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp > 100 nm) particle number concentrations. This suggests that revisions are needed in the new particle formation and growth schemes currently applied in global modeling frameworks.

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Quantifying how model assumptions affect aerosol-cloud interactions in large-eddy simulations of warm stratocumulus clouds

10.5194/egusphere-egu21-11169 ◽

2021 ◽

Author(s):

Matthias Schwarz ◽

Julien Savre ◽

Annica Ekman

Keyword(s):

Number Concentration ◽

Large Eddy Simulations ◽

Radiation Balance ◽

Marine Stratocumulus ◽

Aerosol Cloud ◽

Reference Simulation ◽

Model Aerosol ◽

Large Eddy ◽

Stratocumulus Clouds ◽

Climate Interactions

Subtropical low-level marine stratocumulus clouds effectively reflect downwelling shortwave radiation while having a small effect on outgoing longwave radiation. Hence, they impose a strong negative net radiative effect on the Earth&#8217;s radiation balance. The optical and microphysical properties of these clouds are susceptible to anthropogenic changes in aerosol abundance. Although these aerosol-cloud-climate interactions (ACI) are generally explicitly treated in state-of-the-art Earth System Models (ESMs), they are accountable for large uncertainties in current climate projections.Here, we present preliminary work where we exploit Large-Eddy-Simulations (LES) of warm stratocumulus clouds to identify and constrain processes and model assumptions that affect the response of cloud droplet number concentration (Nd) to changes in aerosol number concentration (Na). Our results are based on simulations with the MISU-MIT Cloud-Aerosol (MIMICA, Savre et al., 2014) LES, which has two-moment bulk microphysics (Seifert and Beheng, 2001) and a two-moment aerosol scheme (Ekman et al., 2006). The reference simulation is based on observations made during the Dynamics and Chemistry of Marine Stratocumulus Field Study (DYCOMS-II, Stevens et al., 2003) which were used extensively during previous LES studies (e.g., Ackerman et al., 2009).Starting from the reference simulation, we conduct sensitivity experiments to examine how the susceptibility (&#946;=dln(Nd)/dln(Na)) changes depending on different model setups. We run the model with fixed and interactive aerosol concentrations, with and without saturation adjustment, with different aerosol populations, and with different model parameter choices. Our early results suggest that &#946; is sensitive to these choices and can vary roughly between 0.6 to 0.9 depending on the setup. The overall purpose of our study is to guide future model developments and evaluations concerning aerosol-cloud-climate interactions. &#160;&#160;ReferencesAckerman, A. S., vanZanten, M. C., Stevens, B., Savic-Jovcic, V., Bretherton, C. S., Chlond, A., et al. (2009). Large-Eddy Simulations of a Drizzling, Stratocumulus-Topped Marine Boundary Layer. Monthly Weather Review, 137(3), 1083&#8211;1110. https://doi.org/10.1175/2008MWR2582.1Ekman, A. M. L., Wang, C., Str&#246;m, J., & Krejci, R. (2006). Explicit Simulation of Aerosol Physics in a Cloud-Resolving Model: Aerosol Transport and Processing in the Free Troposphere. Journal of the Atmospheric Sciences, 63(2), 682&#8211;696. https://doi.org/10.1175/JAS3645.1Savre, J., Ekman, A. M. L., & Svensson, G. (2014). Technical note: Introduction to MIMICA, a large-eddy simulation solver for cloudy planetary boundary layers. Journal of Advances in Modeling Earth Systems, 6(3), 630&#8211;649. https://doi.org/10.1002/2013MS000292Stevens, B., Lenschow, D. H., Vali, G., Gerber, H., Bandy, A., Blomquist, B., et al. (2003). Dynamics and Chemistry of Marine Stratocumulus&#8212;DYCOMS-II. Bulletin of the American Meteorological Society, 84(5), 579&#8211;594. https://doi.org/10.1175/BAMS-84-5-579

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Advancing global aerosol simulations with size-segregated anthropogenic particle number emissions

Atmospheric Chemistry and Physics ◽

10.5194/acp-18-10039-2018 ◽

2018 ◽

Vol 18 (13) ◽

pp. 10039-10054 ◽

Cited By ~ 5

Author(s):

Filippo Xausa ◽

Pauli Paasonen ◽

Risto Makkonen ◽

Mikhail Arshinov ◽

Aijun Ding ◽

...

Keyword(s):

Particle Number ◽

Climate Model ◽

Dominant Role ◽

Particle Diameter ◽

Radiation Budget ◽

Size Distributions ◽

Anthropogenic Aerosol ◽

Accumulation Mode ◽

Climate Interactions ◽

Gains Model

Abstract. Climate models are important tools that are used for generating climate change projections, in which aerosol–climate interactions are one of the main sources of uncertainties. In order to quantify aerosol–radiation and aerosol–cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in pre-compiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few, very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. In the GAINS model the emission number size distributions vary, for example, with respect to the fuel and technology. Special attention was paid to accumulation mode particles (particle diameter dp > 100 nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100 nm particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol–climate interactions, are expected to be affected. Analysis of global particle number concentrations and size distributions reveals that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particles agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp < 100 nm) particle number concentrations. This suggests that revisions are needed in the new particle formation and growth schemes currently applied in global modeling frameworks.

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Overview of the biosphere-aerosol-cloud-climate interactions (BACCI) studies

Tellus B ◽

10.1111/j.1600-0889.2008.00354.x ◽

2008 ◽

Vol 60 (3) ◽

pp. 300-317 ◽

Cited By ~ 7

Author(s):

Markku Kulmala ◽

Veli-Matti Kerminen ◽

Ari Laaksonen ◽

Ilona Riipinen ◽

Mikko Sipilä ◽

...

Keyword(s):

Aerosol Cloud ◽

Climate Interactions

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BVOC-aerosol-climate interactions in the global aerosol-climate model ECHAM5.5-HAM2

Atmospheric Chemistry and Physics ◽

10.5194/acp-12-10077-2012 ◽

2012 ◽

Vol 12 (21) ◽

pp. 10077-10096 ◽

Cited By ~ 47

Author(s):

R. Makkonen ◽

A. Asmi ◽

V.-M. Kerminen ◽

M. Boy ◽

A. Arneth ◽

...

Keyword(s):

Climate Model ◽

Atmospheric Temperature ◽

Cloud Forcing ◽

Albedo Change ◽

Volatile Organic ◽

Nucleation Mechanisms ◽

Climate Interactions ◽

Emission Models ◽

Potential Impact ◽

Year 2000

Abstract. The biosphere emits volatile organic compounds (BVOCs) which, after oxidation in the atmosphere, can partition on the existing aerosol population or even form new particles. The large quantities emitted provide means for a large potential impact on both aerosol direct and indirect effects. Biogenic responses to atmospheric temperature change can establish feedbacks even in rather short timescales. However, due to the complexity of organic aerosol partitioning, even the sign of these feedbacks is of large uncertainty. We use the global aerosol-climate model ECHAM5.5-HAM2 to explore the effect of BVOC emissions on new particle formation, clouds and climate. Two BVOC emission models, MEGAN2 and LPJ-GUESS, are used. MEGAN2 shows a 25% increase while LPJ-GUESS shows a slight decrease in global BVOC emission between years 2000 and 2100. The change of shortwave cloud forcing from year 1750 to 2000 ranges from −1.4 to −1.8 W m−2 with 5 different nucleation mechanisms. We show that the change in shortwave cloud forcing from the year 2000 to 2100 ranges from 1.0 to 1.5 W m−2. Although increasing future BVOC emissions provide 3–5% additional CCN, the effect on the cloud albedo change is modest. Due to simulated decreases in future cloud cover, the increased CCN concentrations from BVOCs can not provide significant additional cooling in the future.

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The contribution of the strength and structure of extratropical cyclones to observed cloud–aerosol relationships

Atmospheric Chemistry and Physics ◽

10.5194/acp-13-10689-2013 ◽

2013 ◽

Vol 13 (21) ◽

pp. 10689-10701 ◽

Cited By ~ 7

Author(s):

B. S. Grandey ◽

P. Stier ◽

R. G. Grainger ◽

T. M. Wagner

Keyword(s):

Large Scale ◽

Relative Vorticity ◽

Extratropical Cyclones ◽

Small Component ◽

Aerosol Cloud ◽

Climate Interactions ◽

Local Meteorology ◽

Moderate Resolution Imaging Spectroradiometer ◽

Regression Slopes ◽

Aerosol Cloud Interactions

Abstract. Meteorological conditions may drive relationships between aerosol and cloud-related properties. It is important to account for the meteorological contribution to observed cloud–aerosol relationships in order to improve understanding of aerosol–cloud–climate interactions. A new method of investigating the contribution of meteorological covariation to observed cloud–aerosol relationships is introduced. Other studies have investigated the contribution of local meteorology to cloud–aerosol relationships. In this paper, a complimentary large-scale view is presented. Extratropical cyclones have been previously shown to affect satellite-retrieved aerosol optical depth (τ), due to enhanced emission of sea salt and sea surface brightness artefacts in regions of higher wind speed. Extratropical cyclones have also been shown to affect cloud-related properties such as cloud fraction (fc) and cloud top temperature (Ttop). Therefore, it seems plausible to hypothesise that extratropical cyclones may drive relationships between cloud-related properties and τ. In this paper, this hypothesis is investigated for extratropical cyclones, henceforth referred to as storms, over the Atlantic Ocean. MODerate resolution Imaging Spectroradiometer (MODIS) retrieved τ, fc and Ttop data are analysed using a storm-centric coordinate system centred on extratropical cyclones which have been tracked using European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis 850 hPa relative vorticity data. The tracked relative vorticity (ω) is used as a measure of storm strength, while position in the storm-centric domain is used to account for storm structure. Relationships between the cloud-related properties and τ are measured by calculating regression slopes and correlations. The fc–τ relationships are positive, while the Ttop–τ relationships are negative. By shuffling the pairing of the cloud and τ data at each location in the storm-centric domain and within narrow ω bins, the contribution of storm strength and storm structure to the observed relationships can be investigated. It is found that storm strength and storm structure can explain only a small component of the relationships observed in the MODIS data. The primary causes for observed cloud–aerosol relationships are likely to be other factors such as retrieval errors, local meteorology or aerosol–cloud interactions.

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