Constraining the Impact of Dust‐Driven Droplet Freezing on Climate Using Cloud‐Top‐Phase Observations

Villanueva, Diego; Neubauer, David; Gasparini, Blaž; Ickes, Luisa; Tegen, Ina

doi:10.1029/2021gl092687

Cited by 13 publications

(9 citation statements)

References 74 publications

(110 reference statements)

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“…It is evident by recent studies that highlight the importance of the mixed-phase cloud ice nucleation associated with dust particles in the Northern Hemisphere (Y. Shi and Liu, 2019;Villanueva et al, 2021). Overall, the dust enhancement introduced by MAM9 warms up the atmosphere by 0.36 W/m 2 (Figure 12c), and the warming coincides with the cirrus cloud ice enhancement (Figure 13).…”

Section: Global Dust Burden and Lifetimementioning

confidence: 68%

“…Because the MAM9 implementation has reduced the fine mode dust burden compared to MAM4 (Tables 8 and 9) due to a greater STD value in the fine dust mode (2.0 in MAM9 vs. 1.8 in MAM4), the mixed‐phase cloud ice nucleation has been suppressed by MAM9, especially in the Northern Hemisphere. It is evident by recent studies that highlight the importance of the mixed‐phase cloud ice nucleation associated with dust particles in the Northern Hemisphere (Y. Shi and Liu, 2019; Villanueva et al., 2021). Overall, the dust enhancement introduced by MAM9 warms up the atmosphere by 0.36 W/m 2 (Figure 12c), and the warming coincides with the cirrus cloud ice enhancement (Figure 13).…”

Section: Resultsmentioning

confidence: 98%

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Improved Dust Representation and Impacts on Dust Transport and Radiative Effect in CAM5

Liu

et al. 2022

J Adv Model Earth Syst

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Dust transport and spatial distribution are poorly represented in current global climate models (GCMs) including the Community Atmosphere Model version 5 (CAM5). Particularly, models lack explicit representation of super‐coarse dust, which may have important implications for dust radiative forcing and impacts on biogeochemistry. A nine‐mode version of the modal aerosol model (MAM9) has been developed to address these issues. In this new aerosol scheme, four dust modes have been designed to treat dust particles of sizes up to 20 μm. The MAM9‐simulated results are compared with those from the default four‐mode version of MAM (MAM4) and also with the in situ surface measurements of dust concentration and deposition flux, satellite‐retrieved dust extinction profile, and in situ vertical measurements of dust concentrations from the NASA Atmosphere Tomography Mission (ATom). Overall, MAM9 improves the dust representation in remote regions while maintaining reasonably good results near the dust source regions. In addition, MAM9 reduces the fine dust burden and increases the coarse dust burden globally. The increased coarse dust burden has slightly increased the dust direct radiative effect by 0.01 W m−2 while it enhanced dust indirect radiative effect by 0.36 W m−2, globally.

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Section: Global Dust Burden and Lifetimementioning

confidence: 68%

Section: Resultsmentioning

confidence: 98%

Improved Dust Representation and Impacts on Dust Transport and Radiative Effect in CAM5

Liu

et al. 2022

J Adv Model Earth Syst

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“…However, both are usually believed to be important processes for ICNC (Kanji et al., 2017; Kärcher et al., 2022; Korolev & Leisner, 2020; Qu et al., 2022; Villanueva et al., 2021) and thus the model behavior seems faulty. The insensitivity of ECHAM‐HAM to heterogeneous freezing (formulations) has been documented before (Dietlicher, 2018; Dietlicher et al., 2019; Hoose, Lohmann, Erdin, & Tegen, 2008; Ickes et al., 2022; Villanueva et al., 2021) but never as clearly as in the present study. Our hypothesis for this model behavior is a strong seeder feeder mechanism (Ansmann et al., 2009; Proske et al., 2021; Roe, 2005; P. Seifert et al., 2009) in the model, meaning that ice crystal sedimentation is supplying ice crystals from cirrus clouds to lower levels so readily in the model that it renders heterogeneous freezing unimportant even as a threshold process.…”

Section: Resultsmentioning

confidence: 99%

Addressing Complexity in Global Aerosol Climate Model Cloud Microphysics

Proske

Ferrachat

Klampt

et al. 2023

J Adv Model Earth Syst

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In climate modeling, our task is to represent an immensely complex system which we wish to understand and learn about. Model development inherently faces tradeoffs between epistemic values like tractability, interpretability, validation potential, and specificity (Beucler et al., 2021;Larsen et al., 2016;Undorf et al., 2022), which manifest themselves in the ever present question of where to draw the line for details. Understanding nature requires a simplification of the mechanisms at play, but wanting to be precise calls for more details that increase complexity (Tapiador et al., 2019). For the term "model complexity" we here follow the "loose definition" mentioned in García-Callejas and Araújo (2016) that a model becomes more complex the more difficult to comprehend its computations are and the more processes/computations there are (Baartman et al. (2020) andRandall et al. (2003)).Climate modeling has followed the mirror view (Parker, 2022), meaning that it wants to mirror the Earth system in the model representation. Different modeling approaches would be following for example, the predictive or

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“…Model data are presented in Figure 2a are likely due to the under-prediction of mixed-phase ice using the default rate-based scheme for dust immersion freezing. The Villanueva et al (2021) study suggests using a different approach for mixed-phase cloud glaciation for better comparability to observations and to address this issue of an over-abundance of liquid-origin cirrus ice. Krämer et al (2020) suggest that these liquid-origin cirrus in the mid-latitudes originate from warm conveyor belts or mesoscale convective systems.…”

Section: Model Validationmentioning

confidence: 99%

“…These phenomena may be linked to the default parameterization for heterogeneous nucleation on mineral dust particles in mixed-phase clouds in ECHAM byLohmann and Diehl. (2006), which is based on dust immersion freezing rates Villanueva et al (2021). conducted several sensitivity tests with ECHAM-HAM using this default freezing-rate-based scheme and an newer AF approach based on dust particle surface area and active site density.…”

mentioning

confidence: 99%

Cirrus cloud thinning using a more physically-based ice microphysics scheme in the ECHAM-HAM GCM

Tully

Neubauer

Omanovic

et al. 2021

Preprint

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Abstract. Cirrus cloud thinning (CCT) is a relatively new radiation management proposal to counteract anthropogenic climate warming by targeting Earth’s terrestrial radiation balance. The efficacy of this method was presented in several general circulation model (GCM) studies that showed widely varied radiative responses, originating in part from the differences in the representation of cirrus ice microphysics between the different GCMs. The recent implementation of a new, more physically based ice microphysics scheme (Predicted Particle Properties, P3) that abandons ice hydrometeor size class separation into the ECHAM-HAM GCM, coupled to a new approach for calculating cloud fractions that increases the relative humidity (RH) thresholds for cirrus cloud formation, motivated a reassessment of CCT efficacy. In this study, we first compared CCT sensitivity between the new cloud fraction approach and the original ECHAM-HAM cloud fraction approach. With the P3 scheme and the higher RH thresholds for cirrus cloud formation, we find a significant cooling response of −0.36 Wm−2 only for our simulation with a seeding particle concentration of 1 L−1, due mostly to rapid cloud adjustments. The most notable response is the reduction of the maximum global-mean net top-of-atmosphere (TOA) radiative anomalies from overseeding by more than 50 %, from 9.0 Wm−2 with the original cloud fraction approach, down to 4.3 Wm−2 using the new cloud fraction RH thresholds by avoiding artificial ice-cloud expansion upon ice nucleation. We attribute the large positive TOA anomalies to seeding particles overtaking both homogeneous nucleation and heterogeneous nucleation on mineral dust particles within cirrus clouds to produce more numerous and smaller ice crystals. This effect is amplified by longer ice residence times in clouds due to the more realistic, slower removal of ice via sedimentation in the P3 scheme. In an effort to avoid this overtaking effect of seeding particles, we increased the default critical ice saturation ratio (Si,seed) for ice nucleation on seeding particles from the default value of 1.05 to 1.35 in a second sensitivity test. With the higher Si,seed we eliminate overseeding and are able to produce cooling responses over a broader range of seeding particle concentrations, with the largest cooling of −0.32 Wm−2 for a seeding particle concentration of 10 L−1, which suggests that Si,seed is a key factor to consider for future CCT studies. However, the global-mean TOA anomalies contain high uncertainty. In response, we examined the TOA responses regionally and found that specific regions only show a small potential for targeted CCT, which is partially enhanced by using the larger Si,seed. Finally, in a seasonal analysis of TOA responses to CCT, we find that our results do not support the previous finding that high-latitude wintertime seeding is a feasible strategy to enhance CCT efficacy, as seeding in our model enhances the already positive cirrus longwave cloud radiative effect. Instead, our results show that summertime cooling occurs due to adjustments of lower-lying mixed-phase and liquid clouds. Therefore, we conclude that CCT is unlikely to act as a feasible climate intervention strategy on a global scale, and should be investigated further with higher-resolution studies in potential target regions and with studies dedicated to assessing potentially realistic seeding particle materials.

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Constraining the Impact of Dust‐Driven Droplet Freezing on Climate Using Cloud‐Top‐Phase Observations

Cited by 13 publications

References 74 publications

Improved Dust Representation and Impacts on Dust Transport and Radiative Effect in CAM5

Improved Dust Representation and Impacts on Dust Transport and Radiative Effect in CAM5

Addressing Complexity in Global Aerosol Climate Model Cloud Microphysics

Cirrus cloud thinning using a more physically-based ice microphysics scheme in the ECHAM-HAM GCM

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