A new look at the environmental conditions favorable to secondary ice production

Korolev, Alexei; Heckman, Ivan; Wolde, Mengistu; Ackerman, A. S.; Fridlind, A. M.; Ladino, Luis A.; Lawson, Paul A.; Milbrandt, Jason A.; Williams, E. R.

doi:10.5194/acp-2019-611

Cited by 12 publications

(22 citation statements)

References 89 publications

(153 reference statements)

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“…Further processes such as ice nucleation within the central and lower parts of the cirrus layer as well as dilution and accumulation effects by turbulent processes and wind shear can lead to a strongly varying ICNC profile from the cloud top to its base (Spichtinger and Gierens, 2009a, b). Since we concentrate on clouds and heterogeneous ice nucleation at temperatures < −20 • C, secondary ice nucleation Korolev et al, 2019) may not introduce further uncertainties.…”

Section: Cycare (2016-2018)mentioning

confidence: 99%

“…Following the terminology of Kuebbeler et al (2014), our closure study in Fig. 13 describes ice nucleation at preexisting ice conditions.…”

Section: The 17 March 2015 Case Study: Long-lasting Cirrus Evolution mentioning

confidence: 99%

“…Homogeneous freezing needs stable conditions regarding the lifting of air parcels over a long time period so that S i steadily rises and can finally reach values of 1.4-1.7. Number concentrations of nucleated ice crystals may be of the order of 1000 L −1 in the case of homogeneous freezing (Kärcher et al, 2006;Kuebbeler et al, 2014). However, at preexisting cirrus conditions, positive and negative vertical motions change frequently within the cirrus layer as a result of radiative cooling at the cloud top, turbulence, and entrainment processes and under the perma-nent influence of short-term gravity wave activity so that it is very likely that S i remains below 1.2.…”

Section: The 17 March 2015 Case Study: Long-lasting Cirrus Evolution mentioning

confidence: 99%

“…Heterogeneous ice nucleation is however not well understood due to the complexity of the ice-nucleating efficiency of atmospheric aerosol mixtures depending on their specific chemical and microphysical properties Murray et al, 2012;Kanji et al, 2017) and the complex influences of ambient temperature, humidity, air motion (updrafts, downdrafts, turbulence, and entrainment), and associated ice supersaturation conditions on the nucleation of ice crystals . In cirrus layers, the competition between heterogeneous and homogeneous ice nucleation further complicates the effort to improve our knowledge about the role of aerosols in ice formation processes in the climate system Kärcher, 2017;Kuebbeler et al, 2014;Jensen et al, 2016). As a consequence, aerosol-cloud interaction remains an important source of large uncertainty in weather and climate predictions.…”

mentioning

confidence: 99%

“…If we transfer this concept to the field of heterogeneous ice nucleation, we may use the ICNC as the dependent, measured variable. Then, the INPC may be regarded as the predicted ICNC value assuming that all INPs become ice crystals during favorable heterogeneous ice nucleation conditions and further assuming that secondary ice production processes (Hallett and Mossop, 1974;Field et al, 2017;Sullivan et al, 2017Sullivan et al, , 2018Korolev et al, 2019) and homogeneous freezing events do not occur (i.e., are suppressed because of unfavorable meteorological conditions). The INPC is calculated from measured independent variables such as the particle surface area concentration, denoted as s, or particle number concentration of large particles with a radius of > 250 nm, denoted as n 250 .…”

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confidence: 99%

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Ice-nucleating particle versus ice crystal number concentrationin altocumulus and cirrus layers embedded in Saharan dust:a closure study

et al. 2019

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Abstract. For the first time, a closure study of the relationship between the ice-nucleating particle concentration (INP; INPC) and ice crystal number concentration (ICNC) in altocumulus and cirrus layers, solely based on ground-based active remote sensing, is presented. Such aerosol–cloud closure experiments are required (a) to better understand aerosol–cloud interaction in the case of mixed-phase clouds, (b) to explore to what extent heterogeneous ice nucleation can contribute to cirrus formation, which is usually controlled by homogeneous freezing, and (c) to check the usefulness of available INPC parameterization schemes, applied to lidar profiles of aerosol optical and microphysical properties up to the tropopause level. The INPC–ICNC closure studies were conducted in Cyprus (Limassol and Nicosia) during a 6-week field campaign in March–April 2015 and during the 17-month CyCARE (Cyprus Clouds Aerosol and Rain Experiment) campaign. The focus was on altocumulus and cirrus layers which developed in pronounced Saharan dust layers at heights from 5 to 11 km. As a highlight, a long-lasting cirrus event was studied which was linked to the development of a very strong dust-infused baroclinic storm (DIBS) over Algeria. The DIBS was associated with strong convective cloud development and lifted large amounts of Saharan dust into the upper troposphere, where the dust influenced the evolution of an unusually large anvil cirrus shield and the subsequent transformation into an cirrus uncinus cloud system extending from the eastern Mediterranean to central Asia, and thus over more than 3500 km. Cloud top temperatures of the three discussed closure study cases ranged from −20 to −57 ∘C. The INPC was estimated from polarization/Raman lidar observations in combination with published INPC parameterization schemes, whereas the ICNC was retrieved from combined Doppler lidar, aerosol lidar, and cloud radar observations of the terminal velocity of falling ice crystals, radar reflectivity, and lidar backscatter in combination with the modeling of backscattering at the 532 and 8.5 mm wavelengths. A good-to-acceptable agreement between INPC (observed before and after the occurrence of the cloud layer under investigation) and ICNC values was found in the discussed three proof-of-concept closure experiments. In these case studies, INPC and ICNC values matched within an order of magnitude (i.e., within the uncertainty ranges of the INPC and ICNC estimates), and they ranged from 0.1 to 10 L−1 in the altocumulus layers and 1 to 50 L−1 in the cirrus layers observed between 8 and 11 km height. The successful closure experiments corroborate the important role of heterogeneous ice nucleation in atmospheric ice formation processes when mineral dust is present. The observed long-lasting cirrus event could be fully explained by the presence of dust, i.e., without the need for homogeneous ice nucleation processes.

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Section: Cycare (2016-2018)mentioning

confidence: 99%

“…Following the terminology of Kuebbeler et al (2014), our closure study in Fig. 13 describes ice nucleation at preexisting ice conditions.…”

Section: The 17 March 2015 Case Study: Long-lasting Cirrus Evolution mentioning

confidence: 99%

Section: The 17 March 2015 Case Study: Long-lasting Cirrus Evolution mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Ice-nucleating particle versus ice crystal number concentrationin altocumulus and cirrus layers embedded in Saharan dust:a closure study

et al. 2019

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Evaluation of the AROME model's ability to represent ice crystal icing using in situ observations from the HAIC 2015 field campaign

Wurtz

Bouniol

Vié

et al. 2021

Quart J Royal Meteoro Soc

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Since pilots generally avoid intense convective areas, ice crystals icing (ICI) is an aeronautical weather incident that mainly occurs in the anvil of tropical deep convective clouds. Samples of favorable conditions for the occurrence of ICI and data from the High Altitude Ice Crystals (HAIC) 2015 field campaign in French Guiana are investigated and compared with simulations of the French operational mesoscale forecast system Application of Research to Operations at Mesoscales (AROME). To this end, a contextualization of convective systems into convective, stratiform, and cirriform regions is employed for both observations and AROME. General features of the microphysics of deep tropical convective systems are identified. The number concentration of crystals larger than 125 μm and total water content (TWC) are strongly correlated at each temperature level, and both decrease with increasing distance from convective cores. AROME can reproduce the general behavior of the observed microphysics, especially TWC, but seems unable to simulate extreme ICI events. Reasons are sought in the assumptions performed in the microphysical scheme ICE3, and guidelines are proposed to enhance its skills in the context of ICI. In particular, the representation of the snow particle size distribution is adjusted across observations using a generalized gamma shape. This shape is found to outperform the usual Marshall–Palmer and gamma shapes. Additionally, a temperature and snow content dependence of generalized gamma parameters is found. These changes are found to significantly improve the snow concentration diagnostic of ICE3, and these modifications open the way for improvements in the ICE3 scheme.

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Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

Morrison

Lier-Walqui

Fridlind

et al. 2020

J Adv Model Earth Syst

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192

125

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In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle‐based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next‐generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process‐level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

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A new look at the environmental conditions favorable to secondary ice production

Cited by 12 publications

References 89 publications

Ice-nucleating particle versus ice crystal number concentrationin altocumulus and cirrus layers embedded in Saharan dust:a closure study

Ice-nucleating particle versus ice crystal number concentrationin altocumulus and cirrus layers embedded in Saharan dust:a closure study

Evaluation of the AROME model's ability to represent ice crystal icing using in situ observations from the HAIC 2015 field campaign

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

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