A computationally efficient description of heterogeneous freezing: A simplified version of the Soccer ball model

Niedermeier, D.; Ervens, B.; Clauß, T.; Voigtländer, Jens; Wex, Heike; Hartmann, S.; Stratmann, Frank

doi:10.1002/2013gl058684

Cited by 40 publications

(71 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At warmer temperatures, between −10 • and −15 • C, there are no CFDC observation data to constrain the parameterizations because CFDC can not provide observation data at warm temperatures (> −15 • C). However, Niemand et al (2012) reported the Aerosol Interactions and Dynamics in the Atmosphere (AIDA) cloud chamber measurement of natural dust at temperatures of −13 and −16 • C with active fractions of 10 −4 and 10 −5 , which agree with our fitted active fractions from the α-PDF model. Saharan natural dust is reported in recent CFDC observations to have onset temperatures ranging from about −10 to −15 • C, which is consistent with laboratory observations of various types of surrogate dust (Phillips et al, 2012).…”

Section: Fitting Parameters For Natural Dust and Sootsupporting

confidence: 82%

“…For example, for σ = 0.01, droplets freeze within a narrow temperature interval of about 10 • C, while for σ = 0.08, freezing occurs over a temperature range of about 18 • C. The change in the active fraction with temperature ( Fig. 10b) becomes smoother with an increase in the standard deviation, which indicates the "recovery" of singular behavior (Niedermeier et al, 2011(Niedermeier et al, , 2014Welti et al, 2012) and a weakening of the time dependence of stochastic behavior (see Fig. 2 for the change in time dependence with an increase in the standard deviation).…”

Section: Occurrence Frequency Of Ice Nucleation Modesmentioning

confidence: 97%

“…The first, "singular (or deterministic) hypothesis", proposed by Langham and Mason (1958), assumes that the radius of the ice germ forming on the aerosol surface at a given supercooling is controlled by surface features and that thermal fluctuations have a negligible influence on the ice germ radius. Thus, the freezing of a droplet is only determined by whether the temperature is below the characteristic temperature of the immersed IN in the droplet (Phillips et al, 2008(Phillips et al, , 2012DeMott et al, 2010;Niemand et al, 2012). The second hypothesis, the "stochastic hypothesis" proposed by Bigg (1953), holds that heterogeneous ice nucleation is a function of time.…”

Section: Y Wang Et Al: Different Contact Angle Distributionsmentioning

confidence: 99%

See 2 more Smart Citations

Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5

et al. 2014

View full text Add to dashboard Cite

Abstract. In order to investigate the impact of different treatments for the contact angle (α) in heterogeneous ice nucleating properties of natural dust and black carbon (BC) particles, we implement the classical-nucleation-theory-based parameterization of heterogeneous ice nucleation (Hoose et al., 2010) in the Community Atmospheric Model version 5 (CAM5) and then improve it by replacing the original singlecontact-angle model with the probability-density-functionof-α (α-PDF) model to better represent the ice nucleation behavior of natural dust found in observations. We refit the classical nucleation theory (CNT) to constrain the uncertain parameters (i.e., onset α and activation energy in the single-α model; mean contact angle and standard deviation in the α-PDF model) using recent observation data sets for Saharan natural dust and BC (soot). We investigate the impact of the time dependence of droplet freezing on mixed-phase clouds and climate in CAM5 as well as the roles of natural dust and soot in different nucleation mechanisms. Our results show that, when compared with observations, the potential ice nuclei (IN) calculated by the α-PDF model show better agreement than those calculated by the single-α model at warm temperatures (T ; T > −20 • C). More ice crystals can form at low altitudes (with warm temperatures) simulated by the α-PDF model than compared to the single-α model in CAM5. All of these can be attributed to different ice nucleation efficiencies among aerosol particles, with some particles having smaller contact angles (higher efficiencies) in the α-PDF model. In the sensitivity tests with the α-PDF model, we find that the change in mean contact angle has a larger impact on the active fraction at a given temperature than a change in standard deviation, even though the change in standard deviation can lead to a change in freezing behavior. Both the single-α and the α-PDF model indicate that the immersion freezing of natural dust plays a more important role in the heterogeneous nucleation than that of soot in mixed-phase clouds. The new parameterizations implemented in CAM5 induce more significant aerosol indirect effects than the default parameterization.

show abstract

Section: Fitting Parameters For Natural Dust and Sootsupporting

confidence: 82%

Section: Occurrence Frequency Of Ice Nucleation Modesmentioning

confidence: 97%

Section: Y Wang Et Al: Different Contact Angle Distributionsmentioning

confidence: 99%

See 1 more Smart Citation

Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Specifically, a contact angle distribution was fitted to the LACIS measurements and was used, together with the soccer ball model (SBM; Niedermeier et al, 2011Niedermeier et al, , 2014, to simulate frozen fractions for different residence times varying over 4 orders of magnitude (i.e., 1, 10, 100 and 1000 s residence time). These frozen fractions were then used to calculate n s , shown as lines in Fig.…”

Section: Stochastic Nature Of Freezing and Time Dependencementioning

confidence: 99%

A comprehensive laboratory study on the immersion freezing behavior of illite NX particles: a comparison of 17 ice nucleation measurement techniques

et al. 2015

View full text Add to dashboard Cite

Abstract. Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice-nucleating particles. However, an intercomparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques.Within the framework of INUIT (Ice Nuclei Research Unit), we distributed an illite-rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain Published by Copernicus Publications on behalf of the European Geosciences Union. N. Hiranuma et al.: A comparison of 17 IN measurement techniquesIN data as a function of particle concentration, temperature (T ), cooling rate and nucleation time. A total of 17 measurement methods were involved in the data intercomparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while 10 other instruments employed water vapor condensation onto drydispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing data set was evaluated using the ice nucleation active surface-site density, n s , to develop a representative n s (T ) spectrum that spans a wide temperature range (−37 • C < T < −11 • C) and covers 9 orders of magnitude in n s .In general, the 17 immersion freezing measurement techniques deviate, within a range of about 8 • C in terms of temperature, by 3 orders of magnitude with respect to n s . In addition, we show evidence that the immersion freezing efficiency expressed in n s of illite NX particles is relatively independent of droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature dependence and weak time and size dependence of the immersion freezing efficiency of illite-rich clay mineral particles enabled the n s parameterization solely as a function of temperature. We also characterized the n s (T ) spectra and identified a section with a steep slope between −20 and −27 • C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below −27 • C. While the agreement between different instruments was reasonable below ∼ −27 • C, there seemed to be a different trend in the temperature-dependent ice nucleation activity from the suspension and dry-dispersed particle measurements for this mineral dust, in particular at higher temperatures. For instance,...

show abstract

“…Time dependence arises from CNT because it is expressed as the rate of nucleation per unit time. Examples of this approach are Khvorostyanov and Curry (2000), Diehl and Wurzler (2004), Hoose (2010), Knopf (2011), Yang et al (2013), Wang et al (2014), andNiedermeier et al (2014).…”

Section: G Vali and J R Snider: Tdfr Parcel Modelmentioning

confidence: 99%

Time-dependent freezing rate parcel model

Vali

Snider

2015

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. The time-dependent freezing rate (TDFR) model here described represents the formation of ice particles by immersion freezing within an air parcel. The air parcel trajectory follows an adiabatic ascent and includes a period in time when the parcel remains stationary at the top of its ascent. The description of the ice nucleating particles (INPs) in the air parcel is taken from laboratory experiments with cloud and precipitation samples and is assumed to represent the INP content of the cloud droplets in the parcel. Time dependence is included to account for variations in updraft velocity and for the continued formation of ice particles under isothermal conditions. The magnitudes of these factors are assessed on the basis of laboratory measurements. Results show that both factors give rise to three-fold variations in ice concentration for a realistic range of the input parameters. Refinements of the parameters specifying time dependence and INP concentrations are needed to make the results more specific to different atmospheric aerosol types. The simple model framework described in this paper can be adapted to more elaborate cloud models. The results here presented can help guide decisions on whether to include a time-dependent ice nucleation scheme or a simpler singular description in models.

show abstract

A computationally efficient description of heterogeneous freezing: A simplified version of the Soccer ball model

Cited by 40 publications

References 35 publications

Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5

Different contact angle distributions for heterogeneous ice nucleation in the Community Atmospheric Model version 5

A comprehensive laboratory study on the immersion freezing behavior of illite NX particles: a comparison of 17 ice nucleation measurement techniques

Time-dependent freezing rate parcel model

Contact Info

Product

Resources

About