The temperature dependence of ice-nucleating particle concentrations affects the radiative properties of tropical convective cloud systems

Hawker, Rachel; Miltenberger, Annette K.; Wilkinson, Jonathan; Hill, Adrian A.; Shipway, Ben J.; Cui, Zhiqiang; Cotton, Richard; Carslaw, K. S.; Field, Paul R.; Murray, Benjamin J.

doi:10.5194/acp-21-5439-2021

Cited by 42 publications

(66 citation statements)

References 86 publications

(161 reference statements)

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“…This assumes that each ice nucleation site has a characteristic temperature at which it always becomes active and time dependence is insignificant (Herbert et al, 2014), otherwise known as the singular description of heterogeneous ice nucleation (Koop and Zobrist, 2009;Murray et al, 2012;Vali, 1994;Pruppacher, 1978). Characterising icenucleating materials in terms of ns(T) also forms the basis of models used for predicting the temperatures (and thus cloud regime) at which different classes of atmospheric INPs may become active (Vergara-Temprado et al, 2017;Hawker et al, 2021;Zhao et al, 2021;Murray et al, 2012).…”

Section: Ice Nucleation Measurements By Droplet Freezing Assay and Determination Of Samples' Heat Deactivationsmentioning

confidence: 99%

“…INPs are important because newly formed ice crystals can grow at the expense of supercooled liquid droplets. This is a process that strongly modulates the radiative properties of shallow mixed-phase clouds (i.e., their albedo) (Storelvmo and Tan, 2015;Murray et al, 2021), can initiate precipitation by enhancing collision and coalescence processes (Vergara-Temprado et al, 2018;Rosenfeld et al, 2011) and can influence anvil cirrus properties in deep convective systems (Hawker et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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The sensitivity of the ice-nucleating ability of minerals to heat and the implications for the heat test for biological ice nucleators

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Whale

et al. 2021

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Abstract. Ice-nucleating particles (INPs) are atmospheric aerosol particles that can strongly influence the radiative properties and precipitation onset in mixed-phase clouds by triggering ice formation in supercooled cloud water droplets. The ability to distinguish between INPs of mineral and biological origin in samples collected from the environment is needed to better understand their distribution and sources, but this is challenging. A common method for assessing the relative contributions of mineral and biogenic INPs in samples collected from the environment (e.g., aerosol, rainwater, soil) is to determine the ice-nucleating ability (INA) before and after heating, where heat is expected to denature proteins associated with biological ice nucleants. The key assumption is that the ice nucleation sites of biological origin are denatured by heat, while those associated with mineral surfaces remain unaffected; we test this assumption here. We exposed atmospherically relevant mineral samples to wet heat (INP suspensions warmed to above 90 °C) or dry heat (dry samples heated to 250 °C) and assessed the effects on their immersion mode INA using a droplet freezing assay. K-feldspar, thought to be the dominant mineral-based atmospheric INP type where present, was not significantly affected by wet heating, while quartz, plagioclase feldspars and Arizona test Dust (ATD) lost INA when heated in this mode. We argue that these reductions in INA in the aqueous phase result from direct alteration of the mineral particle surfaces by heat treatment rather than from biological or organic contamination. We hypothesise that degradation of active sites by dissolution of mineral surfaces is the mechanism in all cases due to the correlation between mineral INA deactivation magnitudes and their dissolution rates. Dry heating produced minor but repeatable deactivations in K-feldspar particles but was generally less likely to deactivate minerals compared to wet heating. We also heat tested proteinaceous and non-proteinaceous biogenic INP proxy materials and found that non-proteinaceous samples (cellulose and pollen) were relatively heat resistant. In contrast, the proteinaceous ice-nucleating samples were highly sensitive to wet and dry heat, as expected, although their activity remained non-negligible after heating. We conclude that, while INP heat tests have the potential to produce false positives, i.e., deactivation of a mineral INA that could be misconstrued as the presence of biogenic INPs, they are still a valid method for qualitatively detecting proteinaceous biogenic INP in ambient samples, so long as the mineral-based INA is controlled by K-feldspar.

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Section: Ice Nucleation Measurements By Droplet Freezing Assay and Determination Of Samples' Heat Deactivationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The sensitivity of the ice-nucleating ability of minerals to heat and the implications for the heat test for biological ice nucleators

Daily

Tarn

Whale

et al. 2021

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“…This study introduces the methodological framework to study the sensitivity of a climate model to the representation of CMP processes. To complete it, the analysis needs to be expanded to include other CMP processes in the model: For cold CMP ice formation, regional modeling studies have demonstrated cloud susceptibility to the choice of the ice nucleation parameterisation (Levkov et al, 1995;Hawker et al, 2021b), whereas in ECHAM-HAM heterogeneous immersion freezing in mixed-phase clouds has been shown to be rather inefficient (Villanueva et al, 2021). More generally the heterogeneous ice formation pathway in mixed-phase clouds is small in ECHAM-HAM (Dietlicher et al, 2019;Bacer et al, 2021), hinting at simplification potential.…”

Section: Processmentioning

confidence: 99%

“…In a sensitivity study of CMP parameters, found that the time scale of the Wegener-Bergeron-Findeisen process explains a large variance in supercooled cloud fractions, suggesting that as a whole it may be a dominating process as well. Secondary ice formation (Korolev and Leisner, 2020) may interact with the ice crystal source processes, allowing for interactive sensitivities (Hawker et al, 2021b), and should therefore be included, even though only the Hallet-Mossop process is optionally included in ECHAM-HAM (Neubauer et al, 2019). Moreover, for a complete CMP process investigation, of course the warm rain processes need to be included as well (Wood et al, 2009;Gettelman et al, 2013)).…”

Section: Processmentioning

confidence: 99%

Assessing the potential for simplification in global climate model cloud microphysics

Proske¹,

Ferrachat²,

Neubauer³

et al. 2021

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Abstract. Cloud properties and their evolution influence Earth's radiative balance. The cloud microphysical (CMP) processes that shape these properties are therefore important to be represented in global climate models. Historically, parameterizations in these models have grown more detailed and complex. However, a simpler formulation of CMP processes may leave the model results mostly unchanged while enabling an easier interpretation of model results and helping to increase process understanding. This study employs sensitivity analysis on an emulated perturbed parameter ensemble of the global aerosol-climate model ECHAM-HAM to illuminate the impact of selected CMP cloud ice processes on model output. The response to the phasing of a process thereby serves as a proxy for the effect of a simplification. Aggregation of ice crystals is found to be the dominant CMP process in influencing key variables such as the ice water path or cloud radiative effects, while riming of cloud droplets on snow influences mostly the liquid phase. Accretion of ice and snow and self-collection of ice crystals have a negligible influence on model output and are therefore identified as suitable candidates for future simplifications. In turn, the dominating role of aggregation suggests that this process has the greatest need to be represented correctly. A seasonal and spatially resolved analysis employing a spherical harmonics expansion of the data corroborates the results. This study introduces a new framework to evaluate a processes' impact in a complex numerical model, and paves the way for simplifications of CMP processes leading to more interpretable climate models.

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“…This determines the concentration of INP at lower mixed-phase altitudes and therefore the altitude of liquid depletion due to heterogeneous freezing in the lower and middle mixed-phase cloud levels (e.g. Hawker et al, 2021;Takeishi and Storelvmo, 2018).…”

Section: Introductionmentioning

confidence: 99%

Model emulation to understand the joint effects of ice-nucleating particles and secondary ice production on deep convective anvil cirrus

et al. 2021

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Abstract. Ice crystal formation in the mixed-phase region of deep convective clouds can affect the properties of climatically important convectively generated anvil clouds. Small ice crystals in the mixed-phase cloud region can be formed by heterogeneous ice nucleation by ice-nucleating particles (INPs) and secondary ice production (SIP) by, for example, the Hallett–Mossop process. We quantify the effects of INP number concentration, the temperature dependence of the INP number concentration at mixed-phase temperatures, and the Hallett–Mossop splinter production efficiency on the anvil of an idealised deep convective cloud using a Latin hypercube sampling method, which allows optimal coverage of a multidimensional parameter space, and statistical emulation, which allows us to identify interdependencies between the three uncertain inputs. Our results show that anvil ice crystal number concentration (ICNC) is determined predominately by INP number concentration, with the temperature dependence of ice-nucleating aerosol activity having a secondary role. Conversely, anvil ice crystal size is determined predominately by the temperature dependence of ice-nucleating aerosol activity, with INP number concentration having a secondary role. This is because in our simulations ICNC is predominately controlled by the number concentration of cloud droplets reaching the homogeneous freezing level which is in turn determined by INP number concentrations at low temperatures. Ice crystal size, however, is more strongly affected by the amount of liquid available for riming and the time available for deposition growth which is determined by INP number concentrations at higher temperatures. This work indicates that the amount of ice particle production by the Hallett–Mossop process is determined jointly by the prescribed Hallett–Mossop splinter production efficiency and the temperature dependence of ice-nucleating aerosol activity. In particular, our sampling of the joint parameter space shows that high rates of SIP do not occur unless the INP parameterisation slope (the temperature dependence of the number concentration of particles which nucleate ice) is shallow, regardless of the prescribed Hallett–Mossop splinter production efficiency. A shallow INP parameterisation slope and consequently high ice particle production by the Hallett–Mossop process in our simulations leads to a sharp transition to a cloud with extensive glaciation at warm temperatures, higher cloud updraughts, enhanced vertical mass flux, and condensate divergence at the outflow level, all of which leads to a larger convectively generated anvil comprised of larger ice crystals. This work highlights the importance of quantifying the full spectrum of INP number concentrations across all mixed-phase altitudes and the ways in which INP and SIP interact to control anvil properties.

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The temperature dependence of ice-nucleating particle concentrations affects the radiative properties of tropical convective cloud systems

Cited by 42 publications

References 86 publications

The sensitivity of the ice-nucleating ability of minerals to heat and the implications for the heat test for biological ice nucleators

The sensitivity of the ice-nucleating ability of minerals to heat and the implications for the heat test for biological ice nucleators

Assessing the potential for simplification in global climate model cloud microphysics

Model emulation to understand the joint effects of ice-nucleating particles and secondary ice production on deep convective anvil cirrus

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