Observations by Lidar of Linear Depolarization Ratios for Hydrometeors

Schotland, R. M.; Sassen, Kenneth; Stone, R.

doi:10.1175/1520-0450(1971)010<1011:oblold>2.0.co;2

Cited by 190 publications

(122 citation statements)

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“…See also Baumgardner et al (2012) and Wendisch and Brenguier (2013) for recent developments on the aircraft instruments. In addition, in the lidar community, the polarization information has been used for cloud measurements since the 1970s (Schotland et al, 1971; see also Sassen, 1991). It is also noted here that possible scientific applications of the Aperture size ～ 0.5cm Figure 1.…”

supporting

confidence: 74%

Development of a cloud particle sensor for radiosonde sounding

et al. 2016

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Abstract. A meteorological balloon-borne cloud sensor called the cloud particle sensor (CPS) has been developed. The CPS is equipped with a diode laser at ∼ 790 nm and two photodetectors, with a polarization plate in front of one of the detectors, to count the number of particles per second and to obtain the cloud-phase information (i.e. liquid, ice, or mixed). The lower detection limit for particle size was evaluated in laboratory experiments as ∼ 2 µm diameter for water droplets. For the current model the output voltage often saturates for water droplets with diameter equal to or greater than ∼ 80 µm. The upper limit of the directly measured particle number concentration is ∼ 2 cm −3 (2×10 3 L −1 ), which is determined by the volume of the detection area of the instrument. In a cloud layer with a number concentration higher than this value, particle signal overlap and multiple scattering of light occur within the detection area, resulting in a counting loss, though a partial correction may be possible using the particle signal width data. The CPS is currently interfaced with either a Meisei RS-06G radiosonde or a Meisei RS-11G radiosonde that measures vertical profiles of temperature, relative humidity, height, pressure, and horizontal winds. Twenty-five test flights have been made between 2012 and 2015 at midlatitude and tropical sites. In this paper, results from four flights are discussed in detail. A simultaneous flight of two CPSs with different instrumental configurations confirmed the robustness of the technique. At a midlatitude site, a profile containing, from low to high altitude, water clouds, mixed-phase clouds, and ice clouds was successfully obtained. In the tropics, vertically thick cloud layers in the middle to upper troposphere and vertically thin cirrus layers in the upper troposphere were successfully detected in two separate flights. The data quality is much better at night, dusk, and dawn than during the daytime because strong sunlight affects the measurements of scattered light.

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confidence: 74%

Development of a cloud particle sensor for radiosonde sounding

et al. 2016

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“…This commercial Lidar emits laser pulses with a wavelength of 355 nm, a repetition rate of 20 Hz, and an average pulse energy of 16 mJ. It detects attenuated backscatter, both in parallel and perpendicular polarization, enabling a determination of the sphericity and thus the physical state of the scattering particles (Schotland et al, 1971;Kovalev and Eichinger, 2004;Zieger et al, 2012).…”

Section: Lidar Measurementmentioning

confidence: 99%

Sensitivities of Lagrangian modelling of mid-latitude cirrus clouds to trajectory data quality

et al. 2015

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Abstract. Simulations of cirrus are subject to uncertainties in model physics and meteorological input data. Here we model cirrus clouds along air mass trajectories, whose extinction has been measured with an elastic backscatter lidar at Jungfraujoch research station in the Swiss Alps, with a microphysical stacked box model. The sensitivities of these simulations to input data uncertainties (trajectory resolution, unresolved vertical velocities, ice nuclei number density and upstream specific humidity) are investigated.Variations in the temporal resolution of the wind field data (COSMO-Model at 2.2 km resolution) between 20 s and 1 h have only a marginal impact on the trajectory path, while the representation of the vertical velocity variability and therefore the cooling rate distribution are significantly affected. A temporal resolution better than 5 min must be chosen in order to resolve cooling rates required to explain the measured extinction. A further increase in the temporal resolution improves the simulation results slightly. The close match between the modelled and observed extinction profile for high-resolution trajectories suggests that the cooling rate spectra calculated by the COSMO-2 model suffice on the selected day. The modelled cooling rate spectra are, however, characterized by significantly lower vertical velocity amplitudes than those found previously in some aircraft campaigns (SUCCESS, MACPEX). A climatological analysis of the vertical velocity amplitude in the Alpine region based on COSMO-2 analyses and balloon sounding data suggests large day-to-day variability in small-scale temperature fluctuations. This demonstrates the necessity to apply numerical weather prediction models with high spatial and temporal resolutions in cirrus modelling, whereas using climatological means for the amplitude of the unresolved air motions does generally not suffice.The box model simulations further suggest that uncertainties in the upstream specific humidity ( ± 10 % of the model prediction) and in the ice nuclei number density (0-100 L −1 ) are more important for the modelled cirrus cloud than the unresolved temperature fluctuations if temporally highly resolved trajectories are used. For the presented case the simulations are incompatible with ice nuclei number densities larger than 20 L −1 and insensitive to variations below this value.

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“…While cirrus clouds or ash particles mostly create a large signal in the depolarization because of their non-spherical shape, spherical particles create a depolarization close to zero. The volume depolarization is calculated by dividing the perpendicular and parallel signal normalized by constant C introduced by Schotland et al (1971). The constant C accounts for differences in the detection efficiency of parallel and perpendicularly polarized light in both detectors.…”

Section: Lidar Measurementsmentioning

confidence: 99%

Lidar observation and model simulation of a volcanic-ash-induced cirrus cloud during the Eyjafjallajökull eruption

Rolf

Krämer

Schiller³

et al. 2012

Atmos. Chem. Phys.

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Abstract. Heterogeneous ice formation induced by volcanic ash from the Eyjafjallajökull volcano eruption in April 2010is investigated based on the combination of a cirrus cloud observed with a backscatter lidar over Jülich (western Germany) and model simulations along backward trajectories. The microphysical properties of the cirrus cloud could only be represented by the microphysical model under the assumption of an enhanced number of efficient ice nuclei originating from the volcanic eruption. The ice nuclei (IN) concentration determined by lidar measurements directly before and after cirrus cloud occurrence implies a value of around 0.1 cm −3 (in comparison normal IN conditions: 0.01 cm −3 ). This leads to a cirrus cloud with rather small ice crystals having a mean radius of 12 µm and a modification of the ice particle number (0.08 cm −3 instead of 3 × 10 −4 cm −3 under normal IN conditions). The effectiveness of ice nuclei was estimated by the use of the microphysical model and the backward trajectories based on ECMWF data, establishing a freezing threshold of around 105 % relative humidity with respect to ice in a temperature range from −45 to −55 • C . Only with these highly efficient ice nuclei was it possible for the cirrus cloud to be formed in a slightly supersaturated environment.

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Observations by Lidar of Linear Depolarization Ratios for Hydrometeors

Cited by 190 publications

References 0 publications

Development of a cloud particle sensor for radiosonde sounding

Development of a cloud particle sensor for radiosonde sounding

Sensitivities of Lagrangian modelling of mid-latitude cirrus clouds to trajectory data quality

Lidar observation and model simulation of a volcanic-ash-induced cirrus cloud during the Eyjafjallajökull eruption

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