Hemispheric contrasts in ice formation in stratiform mixed-phase clouds: disentangling the role of aerosol and dynamics with ground-based remote sensing

Abstract. Multi-year ground-based remote-sensing datasets were acquired with the Leipzig Aerosol and Cloud Remote Observations System (LACROS) at three sites. A highly polluted central European site (Leipzig, Germany), a polluted and strongly dust-influenced eastern Mediterranean site (Limassol, Cyprus), and a clean marine site in the southern midlatitudes (Punta Arenas, Chile) are used to contrast ice formation in shallow stratiform liquid clouds. These unique, long-term datasets in key regions of aerosol–cloud interaction provide a deeper insight into cloud microphysics. The influence of temperature, aerosol load, boundary layer coupling, and gravity wave motion on ice formation is investigated. With respect to previous studies of regional contrasts in the properties of mixed-phase clouds, our study contributes the following new aspects: (1) sampling aerosol optical parameters as a function of temperature, the average backscatter coefficient at supercooled conditions is within a factor of 3 at all three sites. (2) Ice formation was found to be more frequent for cloud layers with cloud top temperatures above -15∘C than indicated by prior lidar-only studies at all sites. A virtual lidar detection threshold of ice water content (IWC) needs to be considered in order to bring radar–lidar-based studies in agreement with lidar-only studies. (3) At similar temperatures, cloud layers which are coupled to the aerosol-laden boundary layer show more intense ice formation than decoupled clouds. (4) Liquid layers formed by gravity waves were found to bias the phase occurrence statistics below -15∘C. By applying a novel gravity wave detection approach using vertical velocity observations within the liquid-dominated cloud top, wave clouds can be classified and excluded from the statistics. After considering boundary layer and gravity wave influences, Punta Arenas shows lower fractions of ice-containing clouds by 0.1 to 0.4 absolute difference at temperatures between −24 and -8∘C. These differences are potentially caused by the contrast in the ice-nucleating particle (INP) reservoir between the different sites.

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Hemispheric contrasts in ice formation in stratiform mixed-phase clouds: Disentangling the role of aerosol and dynamics with ground-based remote sensing

10.5194/acp-2021-360 ◽

2021 ◽

Author(s):

Martin Radenz ◽

Johannes Bühl ◽

Patric Seifert ◽

Holger Baars ◽

Ronny Engelmann ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Gravity Wave ◽

Detection Threshold ◽

Cloud Microphysics ◽

Mixed Phase ◽

Ice Formation ◽

Absolute Difference ◽

Optical Parameters ◽

Mixed Phase Clouds

Abstract. Multi-year ground-based remote-sensing datasets acquired with the Leipzig Aerosol and Cloud Remote Observations System (LACROS) at three sites: a highly polluted central European site (Leipzig, Germany), a polluted and strongly dust-influenced eastern Mediterranean site (Limassol, Cyprus), and a clean marine site in the southern mid-latitudes (Punta Arenas, Chile) are used to contrast ice formation in shallow stratiform liquid clouds. These unique, long-term datasets at key sites of aerosol-cloud interaction provide a deeper insight into cloud microphysics. The influence of temperature, aerosol load, boundary-layer coupling and gravity wave motion on ice formation is investigated. With respect to previous studies of regional contrasts in the properties of mixed-phase clouds our study contributes the following new aspects: (1) Sampling aerosol optical parameters as a function of temperature, the average backscatter coefficient at supercooled temperatures is within a factor of 3 at all three sites. (2) Ice formation was found to be more frequent for cloud layers with cloud top temperatures above −15 °C than indicated by prior lidar-only studies at all sites. A virtual lidar-detection threshold of IWC needs to be considered in order to bring radar-lidar-based studies in agreement with lidar-only studies. (3) At similar temperatures, cloud layers which are coupled to the aerosol-laden boundary layer show more intense ice formation than de-coupled clouds. (4) Liquid layers formed by gravity waves were found to bias the phase occurrence statistics below −15 °C. By applying a novel gravity wave detection approach using vertical velocity observations within the liquid-dominated cloud top, wave clouds can be classified and excluded from the statistics. After considering boundary layer and gravity-wave influences, Punta Arenas shows lower fractions of ice containing clouds by 0.1 to 0.4 absolute difference at temperatures between −24 and −8 °C. These differences are potentially caused by the contrast in the INP reservoir between the different sites.

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Application of COSMO-SPECS for remote sensing observations of mixed-phase clouds during CyCare and DACAPO-PESO

10.5194/egusphere-egu21-14558 ◽

2021 ◽

Author(s):

Roland Schrödner ◽

Johannes Bühl ◽

Fabian Senf ◽

Oswald Knoth ◽

Jens Stoll ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Conditions ◽

Case Studies ◽

Weather Prediction ◽

Cloud Microphysics ◽

Horizontal Resolution ◽

Model System ◽

Mixed Phase ◽

Real Case ◽

Mixed Phase Clouds

During the campaigns CyCyare (Limassol, Cyprus) and DACAPO-PESO (Punta Arenas, Chile), remote sensing methods were applied to study mixed-phase clouds. The two sites show contrasting aerosol loads with very clean, marine atmosphere over southern Chile and higher aerosol mass and number concentrations over Cyprus, which frequently are dust-laden. The observations suggest differing cloud properties. To further study the properties and evolution of the observed clouds as well as their relation to the ambient aerosol, the detailed coupled cloud microphysical model COSMO-SPECS is applied for selected real case studies.The SPECtral bin cloud microphysicS model SPECS was developed to simulate cloud processes using fixed-bin size distributions of aerosol particles and of liquid and frozen hydrometeors. It was implemented in the numerical weather prediction model COSMO. COSMO-SPECS has been used for idealized case studies with horizontally periodic boundary conditions. Recently, the model system has been enhanced by considering lateral boundary conditions for the hydrometeor spectra allowing for high-resolution real case studies on nested domains. The simulations are carried out by first applying the meteorological driver COSMO using its standard two-moment microphysics scheme on multiple nests with increasing horizontal resolution. Finally, the COSMO-SPECS model system is applied on the innermost domain with a horizontal resolution of a few hundred meters using boundary data derived from the finest driving COSMO domain. For this purpose, the bulk hydrometeor fields of the driving model need to be translated into the corresponding hydrometeor mass and number distributions of SPECS&#8217; hydrometeor spectra.In this work, we present first results for selected case-studies of mixed-phase clouds observed during CyCyare and DACAPO-PESO. The results of the model simulations are compared against the LIDAR and cloud radar observations at the two sites.

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Microphysical sensitivity of coupled springtime Arctic stratocumulus to modelled primary ice over the ice pack, marginal ice, and ocean

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-4209-2017 ◽

2017 ◽

Vol 17 (6) ◽

pp. 4209-4227 ◽

Cited By ~ 10

Author(s):

Gillian Young ◽

Paul J. Connolly ◽

Hazel M. Jones ◽

Thomas W. Choularton

Keyword(s):

Sea Ice ◽

Liquid Water ◽

Cloud Microphysics ◽

Mixed Phase ◽

The Arctic ◽

Ice Formation ◽

Large Eddy ◽

Break Up ◽

Mixed Phase Clouds ◽

Ice Pack

Abstract. This study uses large eddy simulations to test the sensitivity of single-layer mixed-phase stratocumulus to primary ice number concentrations in the European Arctic. Observations from the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign are considered for comparison with cloud microphysics modelled using the Large Eddy Model (LEM, UK Met. Office). We find that cloud structure is very sensitive to ice number concentrations, Nice, and small increases can cause persisting mixed-phase clouds to glaciate and break up.Three key dependencies on Nice are identified from sensitivity simulations and comparisons with observations made over the sea ice pack, marginal ice zone (MIZ), and ocean. Over sea ice, we find deposition–condensation ice formation rates are overestimated, leading to cloud glaciation. When ice formation is limited to water-saturated conditions, we find microphysics comparable to aircraft observations over all surfaces considered. We show that warm supercooled (−13 °C) mixed-phase clouds over the MIZ are simulated to reasonable accuracy when using both the DeMott et al.(2010) and Cooper(1986) primary ice nucleation parameterisations. Over the ocean, we find a strong sensitivity of Arctic stratus to Nice. The Cooper(1986) parameterisation performs poorly at the lower ambient temperatures, leading to a comparatively higher Nice (2.43 L−1 at the cloud-top temperature, approximately −20 °C) and cloud glaciation. A small decrease in the predicted Nice (2.07 L−1 at −20 °C), using the DeMott et al.(2010) parameterisation, causes mixed-phase conditions to persist for 24 h over the ocean. However, this representation leads to the formation of convective structures which reduce the cloud liquid water through snow precipitation, promoting cloud break-up through a depleted liquid phase. Decreasing the Nice further (0.54 L−1, using a relationship derived from ACCACIA observations) allows mixed-phase conditions to be maintained for at least 24 h with more stability in the liquid and ice water paths. Sensitivity to Nice is also evident at low number concentrations, where 0.1  × Nice predicted by the DeMott et al.(2010) parameterisation results in the formation of rainbands within the model; rainbands which also act to deplete the liquid water in the cloud and promote break-up.

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Microphysical sensitivity of coupled springtime Arctic stratocumulus to modelled primary ice over the ice pack, marginal ice, and ocean

10.5194/acp-2016-898 ◽

2016 ◽

Author(s):

Gillian Young ◽

Paul J. Connolly ◽

Hazel M. Jones ◽

Thomas W. Choularton

Keyword(s):

Sea Ice ◽

Liquid Water ◽

Cloud Microphysics ◽

Mixed Phase ◽

The Arctic ◽

Ice Formation ◽

Large Eddy ◽

Break Up ◽

Mixed Phase Clouds ◽

Ice Pack

Abstract. This study uses large eddy simulations to test the sensitivity of single-layer mixed-phase stratocumulus to primary ice number concentrations in the European Arctic. Observations from the Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) campaign are considered for comparison with cloud microphysics modelled using the Large Eddy Model (LEM, UK Met. Office). We find that cloud structure is very sensitive to ice number concentrations, N_ice , and small increases can cause persisting mixed-phase clouds to glaciate and break up. Three key sensitivities are identified with comparison to in situ cloud observations over the sea ice pack, marginal ice zone (MIZ), and ocean. Over sea ice, we find deposition-condensation ice formation rates are overestimated, leading to cloud glaciation. When ice formation is limited to water-saturated conditions, we find microphysics comparable to the aircraft observations over all surfaces considered. We show that warm supercooled (−13 °C) mixed-phase clouds over the MIZ are simulated to reasonable accuracy when using both the DeMott et al. (2010) and Cooper (1986) parameterisations. Over the ocean, we find a strong sensitivity of Arctic stratus to ice number concentrations. Cooper (1986) performs poorly at the lower ambient temperatures, leading to comparatively higher ice number concentrations (2.43 L−1 at the cloud top temperature, approximately −20 °C) and cloud glaciation. A small decrease in the predicted Nice (2.07 L−1 at −20 °C), using the DeMott et al. (2010) parameterisation, causes mixed-phase conditions to persist for 24 h over the ocean. However, this representation leads to the formation of convective structures which reduce the cloud liquid water through snow precipitation, promoting cloud break up. Decreasing the ice crystal number concentration further (0.54 L−1, using a relationship derived from ACCACIA observations) allows mixed-phase conditions to be maintained for at least 24 h with more stability in the liquid and ice water paths. Sensitivity to Nice is also evident at low number concentrations, where 0.1×Nice predicted by the DeMott et al. (2010) parameterisation results in the formation of rainbands within the model; rainbands which also act to deplete the liquid water in the cloud and promote break up.

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Ice formation in Arctic mixed-phase clouds: Insights from a 3-D cloud-resolving model with size-resolved aerosol and cloud microphysics

Journal of Geophysical Research Atmospheres ◽

10.1029/2008jd010782 ◽

2009 ◽

Vol 114 (D4) ◽

Cited By ~ 67

Author(s):

Jiwen Fan ◽

Mikhail Ovtchinnikov ◽

Jennifer M. Comstock ◽

Sally A. McFarlane ◽

Alexander Khain

Keyword(s):

Cloud Microphysics ◽

Mixed Phase ◽

Ice Formation ◽

Cloud Resolving Model ◽

Mixed Phase Clouds

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Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship‐based and satellite remote sensing observations

Journal of Geophysical Research Atmospheres ◽

10.1002/2016jd025771 ◽

2017 ◽

Vol 122 (4) ◽

pp. 2403-2418 ◽

Cited By ~ 7

Author(s):

David Painemal ◽

J.‐Y. Christine Chiu ◽

Patrick Minnis ◽

Christopher Yost ◽

Xiaoli Zhou ◽

...

Keyword(s):

Remote Sensing ◽

Boundary Layer ◽

Satellite Remote Sensing ◽

Cloud Microphysics ◽

Northeast Pacific

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Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2

Geoscientific Model Development ◽

10.5194/gmd-13-4107-2020 ◽

2020 ◽

Vol 13 (9) ◽

pp. 4107-4157 ◽

Cited By ~ 1

Author(s):

Shin-ichiro Shima ◽

Yousuke Sato ◽

Akihiro Hashimoto ◽

Ryohei Misumi

Keyword(s):

Method Development ◽

Cloud Condensation Nuclei ◽

Deep Convection ◽

Cloud Microphysics ◽

Mixed Phase ◽

Computational Time ◽

Ice Particles ◽

Mass Dimension ◽

Mixed Phase Clouds ◽

Droplet Method

Abstract. The super-droplet method (SDM) is a particle-based numerical scheme that enables accurate cloud microphysics simulation with lower computational demand than multi-dimensional bin schemes. Using SDM, a detailed numerical model of mixed-phase clouds is developed in which ice morphologies are explicitly predicted without assuming ice categories or mass–dimension relationships. Ice particles are approximated using porous spheroids. The elementary cloud microphysics processes considered are advection and sedimentation; immersion/condensation and homogeneous freezing; melting; condensation and evaporation including cloud condensation nuclei activation and deactivation; deposition and sublimation; and coalescence, riming, and aggregation. To evaluate the model's performance, a 2-D large-eddy simulation of a cumulonimbus was conducted, and the life cycle of a cumulonimbus typically observed in nature was successfully reproduced. The mass–dimension and velocity–dimension relationships the model predicted show a reasonable agreement with existing formulas. Numerical convergence is achieved at a super-particle number concentration as low as 128 per cell, which consumes 30 times more computational time than a two-moment bulk model. Although the model still has room for improvement, these results strongly support the efficacy of the particle-based modeling methodology to simulate mixed-phase clouds.

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Intercomparison of Bulk Cloud Microphysics Schemes in Mesoscale Simulations of Springtime Arctic Mixed-Phase Stratiform Clouds

Monthly Weather Review ◽

10.1175/mwr3154.1 ◽

2006 ◽

Vol 134 (7) ◽

pp. 1880-1900 ◽

Cited By ~ 62

Author(s):

H. Morrison ◽

J. O. Pinto

Keyword(s):

Boundary Layer ◽

Liquid Water ◽

Heat Budget ◽

Cloud Microphysics ◽

Ice Nucleation ◽

Mixed Phase ◽

Precipitation Rate ◽

The Arctic ◽

Ice Clouds ◽

Complex Scheme

Abstract A persistent, weakly forced, horizontally extensive mixed-phase boundary layer cloud observed on 4–5 May 1998 during the Surface Heat Budget of the Arctic Ocean (SHEBA)/First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment–Arctic Clouds Experiment (FIRE–ACE) is modeled using three different bulk microphysics parameterizations of varying complexity implemented into the polar version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). The two simpler schemes predict mostly ice clouds and very little liquid water, while the complex scheme is able to reproduce the observed persistence and horizontal extent of the mixed-phase stratus deck. This mixed-phase cloud results in radiative warming of the surface, the development of a cloud-topped, surface-based mixed layer, and an enhanced precipitation rate. In contrast, the optically thin ice clouds predicted by the simpler schemes lead to radiative cooling of the surface, a strong diurnal cycle in the boundary layer structure, and very weak precipitation. The larger surface precipitation rate using the complex scheme is partly balanced by an increase in the turbulent flux of water vapor from the surface to the atmosphere. This enhanced vapor flux is attributed to changes in the surface and boundary layer characteristics induced by the cloud itself, although cloud–surface interactions appear to be exaggerated in the model compared with reality. The prediction of extensive mixed-phase stratus by the complex scheme is also associated with increased surface pressure and subsidence relative to the other simulations. Sensitivity tests show that the detailed treatment of ice nucleation and prediction of snow particle number concentration in the complex scheme suppresses ice particle concentration relative to the simpler schemes, reducing the vapor deposition rate (for given values of bulk ice mass and ice supersaturation) and leading to much greater amounts of liquid water and mixed-phase cloudiness. These results suggest that the treatments of ice nucleation and the snow intercept parameter in the simpler schemes, which are based upon midlatitude observations, are inadequate for simulating the weakly forced mixed-phase clouds endemic to the Arctic.

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