Arctic cloud macrophysical characteristics from CloudSat and CALIPSO

Liu, Yinghui; Key, Jeffrey R.; Ackerman, S. A.; Mace, Gerald G.; Zhang, Qiuqing

doi:10.1016/j.rse.2012.05.006

Cited by 98 publications

(90 citation statements)

References 69 publications

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“…The blended cloud property vertical distribution can be used as an input to a Monte Carlo radiative transfer model for a more accurate surface radiation flux calculation at these sites. A blended cloud property vertical distribution can also be used to evaluate cloud parameterizations in both weather and climate models (Klaus et al, 2016), to study Arctic atmosphere-sea ice-ocean interactions (Kay et al, 2008;Kay and Gettleman, 2009;Taylor et al, 2015;Liu et al, 2012a), and in other Arctic cloud studies (Devasthale et al, 2011;Liu et al, 2012b;Liu and Key, 2016).…”

Section: Discussionmentioning

confidence: 99%

Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

Liu¹,

Shupe

Wang

et al. 2017

Atmos. Chem. Phys.

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Abstract. Detailed and accurate vertical distributions of cloud properties (such as cloud fraction, cloud phase, and cloud water content) and their changes are essential to accurately calculate the surface radiative flux and to depict the mean climate state. Surface and space-based active sensors including radar and lidar are ideal to provide this information because of their superior capability to detect clouds and retrieve cloud microphysical properties. In this study, we compare the annual cycles of cloud property vertical distributions from space-based active sensors and surface-based active sensors at two Arctic atmospheric observatories, Barrow and Eureka. Based on the comparisons, we identify the sensors' respective strengths and limitations, and develop a blended cloud property vertical distribution by combining both sets of observations. Results show that surface-based observations offer a more complete cloud property vertical distribution from the surface up to 11 km above mean sea level (a.m.s.l.) with limitations in the middle and high altitudes; the annual mean total cloud fraction from space-based observations shows 25-40 % fewer clouds below 0.5 km than from surface-based observations, and space-based observations also show much fewer ice clouds and mixed-phase clouds, and slightly more liquid clouds, from the surface to 1 km. In general, space-based observations show comparable cloud fractions between 1 and 2 km a.m.s.l., and larger cloud fractions above 2 km a.m.s.l. than from surface-based observations. A blended product combines the strengths of both products to provide a more reliable annual cycle of cloud property vertical distributions from the surface to 11 km a.m.s.l. This information can be valuable for deriving an accurate surface radiative budget in the Arctic and for cloud parameterization evaluation in weather and climate models. Cloud annual cycles show similar evolutions in total cloud fraction and ice cloud fraction, and lower liquidcontaining cloud fraction at Eureka than at Barrow; the differences can be attributed to the generally colder and drier conditions at Eureka relative to Barrow.

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Section: Discussionmentioning

confidence: 99%

Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

Liu¹,

Shupe

Wang

et al. 2017

Atmos. Chem. Phys.

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“…Models also have difficulties in representing the correct amount and vertical distribution of cloud hydrometeor phase partitioning over polar regions, under a wide range of annual temperatures. These biases lead to direct consequences for the surface radiation budget, near-surface temperature, and the lower ABL thermal stability and turbulent structure Karlsson and Svensson, 2011;Kay et al, 2011;Cesana et al, 2012;Liu et al, 2012).…”

Section: Cloud Physicsmentioning

confidence: 99%

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

et al. 2014

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Abstract. The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2009, significant advances have been made in understanding these processes. Here, these recent advances are reviewed, synthesized, and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal, and fjordic processes as well as in boundary layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of superimposed ice and snow ice, and the small-scale dynamics of sea ice. For the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, double-diffusive convection, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but the challenge is to understand their interactions with and impacts and feedbacks on other processes. Uncertainty in the parameterization of small-scale processes continues to be among the greatest challenges facing climate modelling, particularly in high latitudes. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments.

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“…The recent developments of ground-based stations (Barrow, EUREKA, Ny-Ålesund, among others) and spaceborne remote sensing observations (as lidar and radar observations from the CALIPSO and CloudSat platforms, respectively) G. Mioche et al: Microphysical properties of Arctic mixed-phase clouds allow reliable studies today of Arctic cloud phase variability from a few kilometers to the pan-Arctic region (Dong et al, 2010;Kay and Gettelman, 2009;Liu et al, 2012;Shupe et al, 2011). Moreover, remote sensing observations from space performed by active instruments onboard CALIPSO (Winker et al, 2003) and CloudSat (Stephens et al, 2002) satellites as a part of the A-Train constellation provide a unique way of characterizing Arctic cloud vertical properties.…”

Section: Introductionmentioning

confidence: 99%

Vertical distribution of microphysical properties of Arctic springtime low-level mixed-phase clouds over the Greenland and Norwegian seas

et al. 2017

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Abstract. This study aims to characterize the microphysical and optical properties of ice crystals and supercooled liquid droplets within low-level Arctic mixed-phase clouds (MPCs). We compiled and analyzed cloud in situ measurements from four airborne spring campaigns (representing 18 flights and 71 vertical profiles in MPCs) over the Greenland and Norwegian seas mainly in the vicinity of the Svalbard archipelago. Cloud phase discrimination and representative vertical profiles of the number, size, mass and shape of ice crystals and liquid droplets are established. The results show that the liquid phase dominates the upper part of the MPCs. High concentrations (120 cm −3 on average) of small droplets (mean values of 15 µm), with an averaged liquid water content (LWC) of 0.2 g m −3 are measured at cloud top. The ice phase dominates the microphysical properties in the lower part of the cloud and beneath it in the precipitation region (mean values of 100 µm, 3 L −1 and 0.025 g m −3 for diameter, particle concentration and ice water content (IWC), respectively). The analysis of the ice crystal morphology shows that the majority of ice particles are irregularly shaped or rimed particles; the prevailing regular habits found are stellars and plates. We hypothesize that riming and diffusional growth processes, including the WegenerBergeron-Findeisen (WBF) mechanism, are the main growth mechanisms involved in the observed MPCs. The impact of larger-scale meteorological conditions on the vertical profiles of MPC properties was also investigated. Large values of LWC and high concentration of smaller droplets are possibly linked to polluted situations and air mass origins from the south, which can lead to very low values of ice crystal size and IWC. On the contrary, clean situations with low temperatures exhibit larger values of ice crystal size and IWC. Several parameterizations relevant for remote sensing or modeling studies are also determined, such as IWC (and LWC) -extinction relationship, ice and liquid integrated water paths, ice concentration and liquid water fraction according to temperature.

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Arctic cloud macrophysical characteristics from CloudSat and CALIPSO

Cited by 98 publications

References 69 publications

Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review

Vertical distribution of microphysical properties of Arctic springtime low-level mixed-phase clouds over the Greenland and Norwegian seas

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