Cloud Resolving Simulations of Mixed-Phase Arctic Stratus Observed during BASE: Sensitivity to Concentration of Ice Crystals and Large-Scale Heat and Moisture Advection

Jiang, Hongli; Cotton, William R.; Pinto, James O.; Curry, Judy; Weissbluth, Michael J.

doi:10.1175/1520-0469(2000)057<2105:crsomp>2.0.co;2

Cited by 135 publications

(180 citation statements)

References 33 publications

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“…The concentration of available IFN may determine the longevity of mixed-phase clouds in the relatively pristine environment found in the Arctic in autumn. Using observations and modeling studies, Pinto [1998] and Jiang et al [2000] describe the importance of IFN concentrations in maintaining mixedphase clouds in the Arctic boundary layer. Cloud dynamics may also play a role in determining cloud phase.…”

Section: Introductionsupporting

confidence: 83%

Cloud‐aerosol interactions during autumn over Beaufort Sea

Pinto¹,

Curry²,

Intrieri³

2001

J. Geophys. Res.

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Abstract. Cloud and aerosol properties were observed by aircraft in autumn over the Beaufort Sea during the 1994 Beaufort and Arctic Storms Experiment (BASE). The microphysical properties (particle size, concentration, mass, and phase) and vertical structure of autumn clouds are examined as a function of height and minimum in-cloud temperature, rmi n. Below 2 km, liquid clouds were observed at rmi n between -5 ø and-9øC, mixed-phase clouds were observed between -5 ø and -20øC, and clear-sky ice crystal precipitation was observed at rmi n as warm as -14øC. Between 2 and 5 km all clouds were mixed-phase and typically consisted of a thin layer of liquid with ice extending well below the liquid layer. These mixed-phase clouds were found at rmi n as low as -32øC. All clouds observed above 5.5 km were composed entirely of ice at rmi n as warm as -33øC. The concentration of ice crystals is observed to increase exponentially with decreasing rmi n. The Hallet-Mossop ice multiplication process did not appear to be an important in the production of ice crystals in the mixed-phase cloud observed in this study. The atmosphere was relatively clean with condensation nuclei (CN) concentrations rarely exceeding 300 cm -3. The smallest CN concentrations (as low as 50 cm -3) were observed in the boundary layer and just above the surface where precipitation and nucleation scavenging have cleansed the air. Thin layers of very large CN concentrations were often observed within and just above low-level clouds possibly resulting from gas-to-particle conversion which requires clean and humid air typical of lower Arctic atmosphere.

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Section: Introductionsupporting

confidence: 83%

Cloud‐aerosol interactions during autumn over Beaufort Sea

Pinto¹,

Curry²,

Intrieri³

2001

J. Geophys. Res.

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“…capacitance). It is this dependence that has led to significant sensitivity of mixed-phase cloud simulations to treatment of ice crystal number concentration in previous studies (Pinto, 1998;Harrington et al, 1999;Jiang et al, 2000;Morrison et al, 2003;Morrison and Pinto, 2006;Prenni et al, 2007).…”

Section: Cloud Microphysicsmentioning

confidence: 99%

“…As an example, the relationship between ice crystal number concentration and liquid water path is examined to ask whether the model-simulated liquid water paths exhibit the inverse relationship with ice crystal number concentration found in prior studies (Harrington et al, 1999;Jiang et al, 2000;Morrison and Pinto, 2006;Prenni et al, 2007). Although ice crystal number concentrations vary over five orders of magnitude among models, the expected inverse relationship is not clearly shown from a scatter-plot of ice crystal number concentration and liquid water path (Figure 10).…”

Section: Cloud Microphysicsmentioning

confidence: 99%

“…Given that numerous modelling studies (Pinto, 1998;Harrington et al, 1999;Jiang et al, 2000;Morrison and Pinto, 2006;Prenni et al, 2007) have demonstrated that the amount of supercooled water in mixed-phase clouds is very sensitive to the representation of ice microphysics in general, and ice crystal number concentration in particular, it is of interest to determine this sensitivity with the present set of models. A sensitivity study was performed in which models were asked to simulate a hypothetical case of a liquid-phase-only cloud.…”

Section: No Ice Microphysicsmentioning

confidence: 99%

“…In these models, a more realistic treatment of ice microphysics, and in particular the number concentration of both small ice and snow, may be needed to improve results. Numerous modelling studies have demonstrated a strong sensitivity of mixed-phase clouds to ice crystal number concentration (Pinto, 1998;Harrington et al, 1999;Jiang et al, 2000;Morrison and Pinto, 2006;Prenni et al, 2007). Prenni et al (2007) substantially improved their simulation of mixed-phase clouds by reducing ice nuclei number concentrations, which influence ice crystal number concentrations, from values typical of midlatitudes to the low values observed in the Arctic.…”

Section: Introductionmentioning

confidence: 99%

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Intercomparison of model simulations of mixed‐phase clouds observed during the ARM Mixed‐Phase Arctic Cloud Experiment. I: single‐layer cloud

Klein

McCoy

Morrison

et al. 2009

Quart J Royal Meteoro Soc

275

341

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ABSTRACT:Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) programme's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud-top temperature of −15 • C. The average liquid water path of around 160 g m −2 was about two-thirds of the adiabatic value and far greater than the average mass of ice which when integrated from the surface to cloud top was around 15 g m −2 .Simulations of 17 single-column models (SCMs) and 9 cloud-resolving models (CRMs) are compared. While the simulated ice water path is generally consistent with observed values, the median SCM and CRM liquid water path is a factor-of-three smaller than observed. Results from a sensitivity study in which models removed ice microphysics suggest that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path.Despite this underestimate, the simulated liquid and ice water paths of several models are consistent with observed values. Furthermore, models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter exists. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics.

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Modeling immersion freezing with aerosol‐dependent prognostic ice nuclei in Arctic mixed‐phase clouds

Paukert

Hoose

2014

JGR Atmospheres

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While recent laboratory experiments have thoroughly quantified the ice nucleation efficiency of different aerosol species, the resulting ice nucleation parameterizations have not yet been extensively evaluated in models on different scales. Here the implementation of an immersion freezing parameterization based on laboratory measurements of the ice nucleation active surface site density of mineral dust and ice nucleation active bacteria, accounting for nucleation scavenging of ice nuclei, into a cloud‐resolving model with two‐moment cloud microphysics is presented. We simulated an Arctic mixed‐phase stratocumulus cloud observed during Flight 31 of the Indirect and Semi‐Direct Aerosol Campaign near Barrow, Alaska. Through different feedback cycles, the persistence of the cloud strongly depends on the ice number concentration. It is attempted to bring the observed cloud properties, assumptions on aerosol concentration, and composition and ice formation parameterized as a function of these aerosol properties into agreement. Depending on the aerosol concentration and on the ice crystal properties, the simulated clouds are classified as growing, dissipating, and quasi‐stable. In comparison to the default ice nucleation scheme, the new scheme requires higher aerosol concentrations to maintain a quasi‐stable cloud. The simulations suggest that in the temperature range of this specific case, mineral dust can only contribute to a minor part of the ice formation. The importance of ice nucleation active bacteria and possibly other ice formation modes than immersion freezing remains poorly constrained in the considered case, since knowledge on local variations in the emissions of ice nucleation active organic aerosols in the Arctic is scarce.

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Cloud Resolving Simulations of Mixed-Phase Arctic Stratus Observed during BASE: Sensitivity to Concentration of Ice Crystals and Large-Scale Heat and Moisture Advection

Cited by 135 publications

References 33 publications

Cloud‐aerosol interactions during autumn over Beaufort Sea

Cloud‐aerosol interactions during autumn over Beaufort Sea

Intercomparison of model simulations of mixed‐phase clouds observed during the ARM Mixed‐Phase Arctic Cloud Experiment. I: single‐layer cloud

Modeling immersion freezing with aerosol‐dependent prognostic ice nuclei in Arctic mixed‐phase clouds

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