Drizzle formation in stratocumulus clouds: effects of turbulent mixing

Magaritz-Ronen, Leehi; Pinsky, Mark; Хаин, А.

doi:10.5194/acpd-15-24131-2015

Cited by 5 publications

(12 citation statements)

References 38 publications

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“…A recent model study by Magaritz‐Ronen et al . [] provides strong support to our hypothesis. In their study, a Lagrangian‐Eularian model containing ~2000 air parcels advecting in a turbulent‐like velocity field was used to simulate a shallow marine stratocumulus cloud and investigate the effect of turbulent mixing on drizzle formation.…”

Section: Resultsmentioning

confidence: 99%

“…More recently, Magaritz‐Ronen et al . [] used a Lagrangian‐Eulerian model to simulate the effects of turbulent mixing on drizzle formation in stratocumulus clouds and found that drizzle develops only when turbulent mixing of parcels is included in the model. In this study, we investigate the impact of the turbulent mixing on the cloud‐to‐drizzle process using available measurements at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) site in the Azores.…”

Section: Introductionmentioning

confidence: 99%

“…Unlike previous observation/parameterization [ Nicholls , ; Baker , ; Austin et al ., ] or model [ Feingold et al ., ; Magaritz‐Ronen et al ., ] studies, we attempt to assess the roles of vertical wind shear and boundary layer instability (buoyancy) in the drizzle initiation processes and investigate how the precipitation patterns respond to these two forcings using ground‐based observations. The manuscript is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Effects of environment forcing on marine boundary layer cloud‐drizzle processes

Dong

et al. 2017

JGR Atmospheres

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Determining the factors affecting drizzle formation in marine boundary layer (MBL) clouds remains a challenge for both observation and modeling communities. To investigate the roles of vertical wind shear and buoyancy (static instability) in drizzle formation, ground‐based observations from the Atmospheric Radiation Measurement Program at the Azores are analyzed for two types of conditions. The type I clouds should last for at least 5 h and more than 90% time must be nondrizzling and then followed by at least 2 h of drizzling periods, while the type II clouds are characterized by mesoscale convection cellular structures with drizzle occur every 2 to 4 h. By analyzing the boundary layer wind profiles (direction and speed), it was found that either directional or speed shear is required to promote drizzle production in the type I clouds. Observations and a recent model study both suggest that vertical wind shear helps the production of turbulent kinetic energy (TKE), stimulates turbulence within cloud layer, and enhances drizzle formation near the cloud top. The type II clouds do not require strong wind shear to produce drizzle. The small values of lower tropospheric stability (LTS) and negative Richardson number (Ri) in the type II cases suggest that boundary layer instability plays an important role in TKE production and cloud‐drizzle processes. By analyzing the relationships between LTS and wind shear for all cases and all time periods, a stronger connection was found between LTS and wind directional shear than that between LTS and wind speed shear.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effects of environment forcing on marine boundary layer cloud‐drizzle processes

Dong

et al. 2017

JGR Atmospheres

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“…[] and Magaritz et al . [] argue that a certain fraction of parcels, which exceed a threshold in liquid water content, is needed to trigger drizzle and that mixing plays an important role in this process [ Magaritz‐Ronen et al ., ]. Using an idealized single cloud setup, Cooper et al .…”

Section: Introductionmentioning

confidence: 99%

Recirculation and growth of raindrops in simulated shallow cumulus

Naumann

Seifert

2016

J Adv Model Earth Syst

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This study investigates growth processes of raindrops and the role of recirculation of raindrops for the formation of precipitation in shallow cumulus. Two related cases of fields of lightly precipitating shallow cumulus are simulated using Large‐Eddy Simulation combined with a Lagrangian drop model for raindrop growth and a cloud tracking algorithm. Statistics from the Lagrangian drop model yield that most raindrops leave the cloud laterally and then evaporate in the subsaturated cloud environmental air. Only 1%–3% of the raindrops contribute to surface precipitation. Among this subsample of raindrops that contribute to surface precipitation, two growth regimes are identified: those raindrops that are dominated by accretional growth from cloud water, and those raindrops that are dominated by selfcollection among raindrops. The mean cloud properties alone are not decisive for the growth of an individual raindrop but the in‐cloud variability is crucial. Recirculation of raindrops is found to be common in shallow cumulus, especially for those raindrops that contribute to surface precipitation. The fraction of surface precipitation that is attributed to recirculating raindrops differs from cloud to cloud but can be larger than 50%. This implies that simple conceptual models of raindrop growth that neglect the effect of recirculation disregard a substantial portion of raindrop growth in shallow cumulus.

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“…Wurzler et al () and Xue et al () showed that aerosols released by complete droplet evaporation may affect the development of secondary clouds. The exact description of the regeneration process requires the calculation of aerosol mass within drops (Flossmann & Pruppacher, ; Pinsky et al, ; Magaritz et al, ; Magaritz‐Ronen et al, , ; Ovchinnikov & Easter, ). Since this approach is computationally expensive, it is used typically only in large‐eddy simulation and trajectory ensemble models for the investigation of warm cloud aqueous chemistry.…”

Section: Description Of the Modified Fast Sbm (Fsbm‐2)mentioning

confidence: 99%

Simulating a Mesoscale Convective System Using WRF With a New Spectral Bin Microphysics: 1: Hail vs Graupel

et al. 2019

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A modified Fast Spectral Bin Microphysics scheme (FSBM‐2) embedded into the Weather Research and Forecasting (WRF) model is used to simulate a mesoscale deep convective system observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). FSBM‐2 uses modified source codes as compared to the current FSBM (FSBM‐1). In contrast to FSBM‐1, FSBM‐2 can simulate hail of several centimeters in diameter and includes additional processes such as spontaneous breakup of raindrops and aerosol regeneration by drop evaporation. It is shown that allowing large hail particles of diameters exceeding about 1 cm substantially increases the agreement between the simulated and observed squall‐line structures in both the convective and stratiform regions. In contrast, if graupel particles are used to represent high‐density hydrometeors in convective areas, the ratio of convective‐to‐stratiform areas diverges from the ratio seen in observations and maximum radar reflectivities are substantially underestimated. Analysis of snow size distributions in the stratiform area shows an important link between the ice crystals formed by homogeneous freezing in the convective area to ice particle number concentration in the stratiform region. Simulated raindrop size distributions in the stratiform area below the melting level from FSBM‐2 show a good agreement with observations. The regeneration of cloud condensational nuclei (CCN) by droplet evaporation and detrainment of these CCN to the stratiform region increases the concentration of CCN there up to 8‐ to 9‐km altitude; the additional CCN penetrate clouds and produce new droplets, leading to some convection intensification.

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Drizzle formation in stratocumulus clouds: effects of turbulent mixing

Cited by 5 publications

References 38 publications

Effects of environment forcing on marine boundary layer cloud‐drizzle processes

Effects of environment forcing on marine boundary layer cloud‐drizzle processes

Recirculation and growth of raindrops in simulated shallow cumulus

Simulating a Mesoscale Convective System Using WRF With a New Spectral Bin Microphysics: 1: Hail vs Graupel

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