Antarctic clouds, supercooled liquid water and mixed phase, investigated with DARDAR: geographical and seasonal variations

Abstract. Antarctic tropospheric clouds are investigated using the DARDAR (raDAR/liDAR)-MASK products between 60 and 82∘ S. The cloud fraction (occurrence frequency) is divided into the supercooled liquid-water-containing cloud (SLC) fraction and its complementary part called the all-ice cloud fraction. A further distinction is made between SLC involving ice (mixed-phase clouds, MPC) or not (USLC, for unglaciated SLC). The low-level (<3 km above surface level) SLC fraction is larger over seas (20 %–60 %), where it varies according to sea ice fraction, than over continental regions (0 %–35 %). The total SLC fraction is much larger over West Antarctica (10 %–40 %) than it is over the Antarctic Plateau (0 %–10 %). In East Antarctica the total SLC fraction – in summer for instance – decreases sharply polewards with increasing surface height (decreasing temperatures) from 40 % at the coast to <5% at 82∘ S on the plateau. The geographical distribution of the continental total all-ice fraction is shaped by the interaction of the main low-pressure systems surrounding the continent and the orography, with little association with the sea ice fraction. Opportunistic comparisons with published ground-based supercooled liquid-water observations at the South Pole in 2009 are made with our SLC fractions at 82∘ S in terms of seasonal variability, showing good agreement. We demonstrate that the largest impact of sea ice on the low-level SLC fraction (and mostly through the MPC) occurs in autumn and winter (22 % and 18 % absolute decrease in the fraction between open water and sea ice-covered regions, respectively), while it is almost null in summer and intermediate in spring (11 %). Monthly variability of the MPC fraction over seas shows a maximum at the end of summer and a minimum in winter. Conversely, the USLC fraction has a maximum at the beginning of summer. However, monthly evolutions of MPC and USLC fractions do not differ on the continent. This suggests a seasonality in the glaciation process in marine liquid-bearing clouds. From the literature, we identify the pattern of the monthly evolution of the MPC fraction as being similar to that of the aerosols in coastal regions, which is related to marine biological activity. Marine bioaerosols are known to be efficient ice-nucleating particles (INPs). The emission of these INPs into the atmosphere from open waters would add to the temperature and sea ice fraction seasonalities as factors explaining the MPC fraction monthly evolution.

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Antarctic clouds, supercooled liquid water and mixed-phase investigated with DARDAR: geographical and seasonal variations

10.5194/acp-2018-1222 ◽

2018 ◽

Author(s):

Constantino Listowski ◽

Julien Delanoë ◽

Amélie Kirchgaessner ◽

Tom Lachlan-Cope ◽

John King

Keyword(s):

Sea Ice ◽

Liquid Water ◽

Supercooled Liquid ◽

Mixed Phase ◽

Ice Clouds ◽

Ice Cloud ◽

The One ◽

Autumn And Winter ◽

Mixed Phase Clouds ◽

Ice Fraction

Abstract. Antarctic tropospheric clouds are investigated using the radar-lidar DARDAR (raDAR/liDAR)-MASK products. The cloud fraction is divided into the supercooled liquid water (SLW)-containing clouds and the all-ice clouds. The low-level SLW fraction varies according to temperature and sea ice fraction. It is the largest over water. In East Antarctica, the SLW fraction decreases sharply polewards. It is twice to three times higher in West Antarctica. The all-ice cloud geographical distribution is shaped by the interaction of the main low-pressure systems surrounding the continent and the orography, with little links with sea ice fraction. We demonstrate the largest impact of sea ice on SLW (mostly mixed-phase clouds, MPC) in autumn and winter, while it is almost null in summer and intermediate in spring. Monthly variability of MPC shows a maximum fraction at the end of summer and minimum in winter. Conversely, the unglaciated (pure) SLW (USLW) fraction has a maximum at the beginning of summer. Monthly evolutions of MPC and USLW fractions do not differ on the continent. This demonstrates a seasonality in the glaciation process in marine liquid-bearing clouds. From the literature, we identify the pattern of the monthly evolution of the MPC fraction as being similar to the one of the aerosols, which is related to marine biological activity. Marine bioaerosols are known to be efficient Ice Nucleating Particles (INPs). The emission of these INPs into the atmosphere from open waters would come on top of the temperature and sea ice fraction seasonalities as factors explaining the mixed-phase clouds monthly evolution.

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Constraining Neoproterozoic subtropical low-level clouds to assess the plausibility of near-Snowball Earth states

10.5194/egusphere-egu21-4742 ◽

2021 ◽

Author(s):

Christoph Braun ◽

Aiko Voigt ◽

Johannes Hörner ◽

Joaquim G. Pinto

Keyword(s):

Sea Ice ◽

Climate Models ◽

Global Climate ◽

Global Climate Models ◽

Mixed Phase ◽

Snowball Earth ◽

Stable Range ◽

Climate Regime ◽

Low Level ◽

Mixed Phase Clouds

<p>Stable waterbelt climate states with close to global ice cover challenge the classical Snowball Earth hypothesis because they provide a robust explanation for the survival of advanced marine species during the Neoproterozoic glaciations (1000 &#8211; 541 Million years ago). Whether Earth&#8217;s climate stabilizes in a waterbelt state or rushes towards a Snowball state is determined by the magnitude of the ice-albedo feedback in the subtropics, where dark, bare sea ice instead of snow-covered sea ice prevails. For a given bare sea-ice albedo, the subtropical ice-albedo feedback and thus the stable range of the waterbelt climate regime is sensitive to the albedo over ice-free ocean, which is largely determined by shortwave cloud-radiative effects (CRE). In the present-day climate, CRE are known to dominate the spread of climate sensitivity across global climate models. We here study the impact of uncertainty associated with CRE on the existence of geologically relevant waterbelt climate regimes using two global climate models and an idealized energy balance model. We find that the stable range of the waterbelt climate regime is very sensitive to the abundance of subtropical low-level mixed-phase clouds. If subtropical cloud cover is low, climate sensitivity becomes so high as to inhibit stable waterbelt states.</p><p>The treatment of mixed-phase clouds is highly uncertain in global climate models. Therefore we aim to constrain the uncertainty associated with their CRE by means of a hierarchy of global and regional simulations that span horizontal grid resolutions from 160 km to 300m, and in particular include large eddy simulations of subtropical mixed-phase clouds located over a low-latitude ice edge. In the cold waterbelt climate subtropical CRE arise from convective events caused by strong meridional temperature gradients and stratocumulus decks located in areas of large-scale descending motion. We identify the latter to dominate subtropical CRE and therefore focus our large eddy simulations on subtropical stratocumulus clouds. By conducting simulations with two extreme scenarios for the abundance of atmospheric mineral dust, which serves as ice-nucleating particles and therefore can control mixed-phase cloud physics, we aim to estimate the possible spread of CRE associated with subtropical mixed-phase clouds. From this estimate we may assess whether Neoproterozoic low-level cloud abundance may have been high enough to sustain a stable waterbelt climate regime.</p>

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The importance of mixed-phase and ice clouds for climate sensitivity in the global aerosol–climate model ECHAM6-HAM2

Atmospheric Chemistry and Physics ◽

10.5194/acp-18-8807-2018 ◽

2018 ◽

Vol 18 (12) ◽

pp. 8807-8828 ◽

Cited By ~ 20

Author(s):

Ulrike Lohmann ◽

David Neubauer

Keyword(s):

Climate Sensitivity ◽

Liquid Water ◽

Climate Model ◽

Supercooled Liquid ◽

Cloud Feedback ◽

Mixed Phase ◽

Shortwave Radiation ◽

Ice Clouds ◽

Cloud Optical Depth ◽

Mixed Phase Clouds

Abstract. How clouds change in a warmer climate remains one of the largest uncertainties for the equilibrium climate sensitivity (ECS). While a large spread in the cloud feedback arises from low-level clouds, it was recently shown that mixed-phase clouds are also important for ECS. If mixed-phase clouds in the current climate contain too few supercooled cloud droplets, too much ice will change to liquid water in a warmer climate. As shown by Tan et al. (2016), this overestimates the negative cloud-phase feedback and underestimates ECS in the CAM global climate model (GCM). Here we use the newest version of the ECHAM6-HAM2 GCM to investigate the importance of mixed-phase and ice clouds for ECS. Although we also considerably underestimate the fraction of supercooled liquid water globally in the reference version of the ECHAM6-HAM2 GCM, we do not obtain increases in ECS in simulations with more supercooled liquid water in the present-day climate, different from the findings by Tan et al. (2016). We hypothesize that it is not the global supercooled liquid water fraction that matters, but only how well low- and mid-level mixed-phase clouds with cloud-top temperatures in the mixed-phase temperature range between 0 and −35 ∘C that are not shielded by higher-lying ice clouds are simulated. These occur most frequently in midlatitudes, in particular over the Southern Ocean where they determine the amount of absorbed shortwave radiation. In ECHAM6-HAM2 the amount of absorbed shortwave radiation over the Southern Ocean is only significantly overestimated if all clouds below 0 ∘C consist exclusively of ice. Only in this simulation is ECS significantly smaller than in all other simulations and the cloud optical depth feedback is the dominant cloud feedback. In all other simulations, the cloud optical depth feedback is weak and changes in cloud feedbacks associated with cloud amount and cloud-top pressure dominate the overall cloud feedback. However, apart from the simulation with only ice below 0 ∘C, differences in the overall cloud feedback are not translated into differences in ECS in our model. This insensitivity to the cloud feedback in our model is explained with compensating effects in the clear sky.

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The importance of mixed-phase clouds for climate sensitivity in the global aerosol-climate model ECHAM6-HAM2

10.5194/acp-2018-97 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ulrike Lohmann ◽

David Neubauer

Keyword(s):

Southern Ocean ◽

Climate Sensitivity ◽

Liquid Water ◽

Climate Model ◽

Global Climate Model ◽

Supercooled Liquid ◽

Mixed Phase ◽

Radiation Budget ◽

Shortwave Radiation ◽

Mixed Phase Clouds

Abstract. Clouds are important in the climate system because of their large influence on the radiation budget. On the one hand, they scatter solar radiation and with that cool the climate. On the other hand, they absorb and re-emit terrestrial radiation, which causes a warming. How clouds change in a warmer climate is one of the largest uncertainties for the equilibrium climate sensitivity (ECS). While a large spread in the cloud feedback arises from low-level clouds, it was recently shown that also mixed-phase clouds are important for ECS. If mixed-phase clouds in the current climate contain too few supercooled cloud droplets, too much ice will change to liquid water in a warmer climate. As shown by Tan et al. (2016), this overestimates the negative cloud phase feedback and underestimates ECS in the CAM global climate model (GCM). Here we are using the newest version of the ECHAM6-HAM2 GCM to investigate the importance of mixed-phase clouds for ECS. Although we also considerably underestimate the fraction of supercooled liquid water globally in the reference version of ECHAM6-HAM2 GCM, we do not obtain increases in ECS in simulations with more supercooled liquid water in the present-day climate, contrary to the findings by Tan et al. (2016). We hypothesize that it is not the global supercooled liquid water fraction that matters, but only how well low- and mid-level mixed-phase clouds with cloud top temperatures in the mixed-phase temperature range between 0 and −35 ºC are simulated. These occur most frequent in mid-latitudes, in particular over the Southern Ocean where they determine the amount of absorbed shortwave radiation. In ECHAM6-HAM2 the amount of absorbed shortwave radiation over the Southern Ocean is only overestimated if all clouds below 0 ºC consist exclusively of ice and only in this simulation is ECS is significantly smaller than in all other simulations. Hence, the negative cloud phase feedback seems to be important only if the optically thin low- and mid-level mid-latitude clouds have the wrong phase (ice instead of liquid water) in the absence of overlying clouds. In all other simulations, changes in cloud feedbacks associated with cloud amount and cloud top pressure, dominate.

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In-situ Observation of Riming in Mixed-Phase Clouds using the PHIPS probe

10.5194/acp-2021-833 ◽

2021 ◽

Author(s):

Fritz Waitz ◽

Martin Schnaiter ◽

Thomas Leisner ◽

Emma Järvinen

Keyword(s):

Liquid Water ◽

Prediction Models ◽

Supercooled Liquid ◽

Liquid Water Content ◽

Mixed Phase ◽

Ice Crystals ◽

The Arctic ◽

In Situ Observation ◽

Cloud Particle ◽

Mixed Phase Clouds

Abstract. Mixed-phase clouds consist of both supercooled liquid water droplets and solid ice crystals. Despite having a significant impact on Earth‘s climate, mixed-phase clouds are poorly understood and not well represented in climate prediction models. One piece of the puzzle is understanding and parameterizing riming of mixed-phase cloud ice crystals, which is one of the main growth mechanisms of ice crystals via the accretion of small, supercooled droplets. Especially the extent of riming on ice crystals smaller than 500 μm is often overlooked in studies – mainly because observations are scarce. Here, we investigated riming in mixed-phase clouds during three airborne campaigns in the Arctic, the Southern Ocean and US east coast. Riming was observed from stereo-microscopic cloud particle images recorded with the Particle Habit Imaging and Polar Scattering (PHIPS) probe. We show that riming is most prevalent at temperatures around −7 °C, where, on average, 43 % of the investigated particles in a size range from 100 ≤ D ≤ 700 μm showed evidence of riming. We discuss the occurrence and properties of rimed ice particles and show correlation of the occurrence and the amount of riming with ambient meteorological parameters. We show that riming fraction increases with ice particle size (< 20 % for D ≤ 200 μm, 35–40 % for D ≥ 400 μm) and liquid water content (25 % for LWC ≤ 0.05 g m−3, up to 60 % for LWC = 0.5 g m−3). We investigate the ageing of rimed particles and the difference between "normal" and "epitaxial" riming based on a case study.

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Determining Cloud Thermodynamic Phase from the Polarized Micro Pulse Lidar

10.5194/amt-2020-298 ◽

2020 ◽

Author(s):

Jasper R. Lewis ◽

James R. Campbell ◽

Simone Lolli ◽

Sebastian A. Stewart ◽

Ivy Tan ◽

...

Keyword(s):

Liquid Water ◽

Supercooled Liquid ◽

Mixed Phase ◽

Orthogonal Polarization ◽

Water Ice ◽

Earth Observing System ◽

Micro Pulse Lidar ◽

Mixed Phase Clouds ◽

Ice Water ◽

Thermodynamic Phase

Abstract. A method to distinguish cloud thermodynamic phase from polarized Micro Pulse Lidar (MPL) measurements is described. The method employs a simple enumerative approach to classify cloud layers as either liquid water, ice water, or mixed-phase clouds based on the linear volume depolarization ratio and cloud top temperatures derived from Goddard Earth Observing System, version 5 (GEOS-5) assimilated data. Two years of cloud retrievals from the Micro Pulse Lidar Network (MPLNET) site in Greenbelt, MD are used to evaluate the performance of the algorithm. The fraction of supercooled liquid water in the mixed-phase temperature regime (−37 °C–0 °C) calculated using MPLNET data is compared to similar calculations made using the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on board the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, with reasonable consistency.

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Determining cloud thermodynamic phase from the polarized Micro Pulse Lidar

Atmospheric Measurement Techniques ◽

10.5194/amt-13-6901-2020 ◽

2020 ◽

Vol 13 (12) ◽

pp. 6901-6913

Author(s):

Jasper R. Lewis ◽

James R. Campbell ◽

Sebastian A. Stewart ◽

Ivy Tan ◽

Ellsworth J. Welton ◽

...

Keyword(s):

Liquid Water ◽

Supercooled Liquid ◽

Mixed Phase ◽

Orthogonal Polarization ◽

Water Ice ◽

Earth Observing System ◽

Micro Pulse Lidar ◽

Mixed Phase Clouds ◽

Ice Water ◽

Thermodynamic Phase

Abstract. A method to distinguish cloud thermodynamic phase from polarized Micro Pulse Lidar (MPL) measurements is described. The method employs a simple enumerative approach to classify cloud layers as either liquid water, ice water, or mixed-phase clouds based on the linear volume depolarization ratio and cloud top temperatures derived from Goddard Earth Observing System, version 5 (GEOS-5), assimilated data. Two years of cloud retrievals from the Micro Pulse Lidar Network (MPLNET) site in Greenbelt, MD, are used to evaluate the performance of the algorithm. The fraction of supercooled liquid water in the mixed-phase temperature regime (−37–0 ∘C) calculated using MPLNET data is compared to similar calculations made using the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, with reasonable consistency.

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Retrieving Mean Temperature of Atmospheric Liquid Water Layers Using Microwave Radiometer Measurements

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-17-0179.1 ◽

2018 ◽

Vol 35 (5) ◽

pp. 1091-1102 ◽

Cited By ~ 6

Author(s):

Sergey Y. Matrosov ◽

David D. Turner

Keyword(s):

Water Vapor ◽

Liquid Water ◽

Microwave Radiometer ◽

Supercooled Liquid ◽

Mixed Phase ◽

Liquid Temperature ◽

Ka Band ◽

Mean Temperature ◽

Water Layers ◽

Mixed Phase Clouds

AbstractA remote sensing method to retrieve the mean temperature of cloud liquid using ground-based microwave radiometer measurements is evaluated and tested by comparisons with direct cloud temperature information inferred from ceilometer cloud-base measurements and temperature profiles from radiosonde soundings. The method is based on the dependence of the ratio of cloud optical thicknesses at W-band (~90 GHz) and Ka-band (~30 GHz) frequencies on cloud liquid temperature. This ratio is obtained from total optical thicknesses inferred from radiometer measurements of brightness temperatures after accounting for the contributions from oxygen and water vapor. This accounting is done based on the radiometer-based retrievals of integrated water vapor amount and temperature and pressure measurements at the surface. The W–Ka-band ratio method is applied to the measurements from a three-channel (90, 31.4, and 23.8 GHz) microwave radiometer at the U.S. Department of Energy Atmospheric Radiation Measurement Mobile Facility at Oliktok Point, Alaska. The analyzed events span conditions from warm stratus clouds with temperatures above freezing to mixed-phase clouds with supercooled liquid water layers. Intercomparisons of radiometer-based cloud liquid temperature retrievals with estimates from collocated ceilometer and radiosonde measurements indicated on average a standard deviation of about 3.5°C between the two retrieval types in a wide range of cloud temperatures, from warm liquid clouds to mixed-phase clouds with supercooled liquid and liquid water paths greater than 50 g m−2. The three-channel microwave radiometer–based method has a broad applicability, since it requires neither the use of active sensors to locate the boundaries of liquid cloud layers nor information on the vertical profile of temperature.

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Improvements in Supercooled Liquid Water Simulations of Low-Level Mixed-Phase Clouds over the Southern Ocean Using a Single-Column Model

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-19-0266.1 ◽

2020 ◽

Vol 77 (11) ◽

pp. 3803-3819 ◽

Cited By ~ 1

Author(s):

Tatsuya Seiki ◽

Woosub Roh

Keyword(s):

Supercooled Liquid ◽

Atmospheric Model ◽

Cloud Microphysics ◽

Cloud Water ◽

Mixed Phase ◽

Microphysics Scheme ◽

Low Level ◽

Single Column ◽

Single Column Model ◽

Mixed Phase Clouds

AbstractA high-resolution global atmospheric model, the nonhydrostatic icosahedral atmospheric model (NICAM), exhibited underestimation biases in low-level mixed-phase clouds in the midlatitudes and polar regions. The ice-cloud microphysics used in a single-moment bulk cloud microphysics scheme (NSW6) was evaluated and improved using a single-column model by reference to a double-moment bulk cloud microphysics scheme (NDW6). Budget analysis indicated that excessive action of the Bergeron–Findeisen and riming processes crucially reduced supercooled liquid water. In addition, the rapid production of rain directly reduced cloud water and indirectly reduced cloud water through the production of snow and graupel by riming. These biases in growth rates were found to originate from the number concentration diagnosis used in NSW6. The diagnosis based on the midlatitude cloud systems assumption was completely different from the one for low-level mixed-phase clouds. To alleviate underestimation biases, rain production, heterogeneous ice nucleation, vapor deposition by snow and graupel, and riming processes were revised. The sequential revisions of cloud microphysics alleviated the underestimation biases step by step without parameter tuning. The lifetime of cloud layers simulated by NSW6 was reasonably prolonged.

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A Physically Based Subgrid Parameterization for the Production and Maintenance of Mixed-Phase Clouds in a General Circulation Model

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-15-0021.1 ◽

2015 ◽

Vol 73 (1) ◽

pp. 279-291 ◽

Cited By ~ 32

Author(s):

K. Furtado ◽

P. R. Field ◽

I. A. Boutle ◽

C. J. Morcrette ◽

J. M. Wilkinson

Keyword(s):

General Circulation Model ◽

Liquid Water ◽

General Circulation ◽

Circulation Model ◽

Supercooled Liquid ◽

Liquid Water Content ◽

Mixed Phase ◽

Physically Based ◽

Scale Turbulence ◽

Mixed Phase Clouds

Abstract A physically based method for parameterizing the role of subgrid-scale turbulence in the production and maintenance of supercooled liquid water and mixed-phase clouds is presented. The approach used is to simplify the dynamics of supersaturation fluctuations to a stochastic differential equation that can be solved analytically, giving increments to the prognostic liquid cloud fraction and liquid water content fields in a general circulation model (GCM). Elsewhere, it has been demonstrated that the approach captures the properties of decameter-resolution large-eddy simulations of a turbulent mixed-phase environment. In this paper, it is shown that it can be implemented in a GCM, and the effects that this has on Southern Ocean biases and on Arctic stratus are investigated.

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