PHIPS-HALO: the airborne particle habit imaging and polar
scattering probe – Part 3: Single Particle Phase Discrimination and
Particle Size Distribution based on Angular Scattering Function

Waitz, Fritz; Schnaiter, M.; Leisner, Thomas; Järvinen, Emma

doi:10.5194/amt-2020-297

Cited by 2 publications

(5 citation statements)

References 25 publications

(45 reference statements)

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“…The SOCRATES payload also included the Particle Habit Imaging and Polar Scattering (PHIPS) probe, which records high-quality images of particles with a maximum imaging rate set at 3 Hz for SOCRATES and measures particle scattering phase functions at a maximum rate of 3.5 kHz (Abdelmonem et al, 2016;Schnaiter et al, 2018). The PHIPS dataset (Schnaiter, 2018b) includes manual classifications of particle phase based on particle images and automated classifications of particle sphericity based on particle scattering phase functions (Waitz et al, 2021). Because the maximum scattering phase function data acquisition rate is greater than the maximum imaging rate, there are more automated classifications than manual classifications.…”

Section: Preparation Of Training Validation and Test Datamentioning

confidence: 99%

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The University of Washington Ice–Liquid Discriminator (UWILD) improves single-particle phase classifications of hydrometeors within Southern Ocean clouds using machine learning

et al. 2021

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Abstract. Mixed-phase Southern Ocean clouds are challenging to simulate, and their representation in climate models is an important control on climate sensitivity. In particular, the amount of supercooled water and frozen mass that they contain in the present climate is a predictor of their planetary feedback in a warming climate. The recent Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) vastly increased the amount of in situ data available from mixed-phase Southern Ocean clouds useful for model evaluation. Bulk measurements distinguishing liquid and ice water content are not available from SOCRATES, so single-particle phase classifications from the Two-Dimensional Stereo (2D-S) probe are invaluable for quantifying mixed-phase cloud properties. Motivated by the presence of large biases in existing phase discrimination algorithms, we develop a novel technique for single-particle phase classification of binary 2D-S images using a random forest algorithm, which we refer to as the University of Washington Ice–Liquid Discriminator (UWILD). UWILD uses 14 parameters computed from binary image data, as well as particle inter-arrival time, to predict phase. We use liquid-only and ice-dominated time periods within the SOCRATES dataset as training and testing data. This novel approach to model training avoids major pitfalls associated with using manually labeled data, including reduced model generalizability and high labor costs. We find that UWILD is well calibrated and has an overall accuracy of 95 % compared to 72 % and 79 % for two existing phase classification algorithms that we compare it with. UWILD improves classifications of small ice crystals and large liquid drops in particular and has more flexibility than the other algorithms to identify both liquid-dominated and ice-dominated regions within the SOCRATES dataset. UWILD misclassifies a small percentage of large liquid drops as ice. Such misclassified particles are typically associated with model confidence below 75 % and can easily be filtered out of the dataset. UWILD phase classifications show that particles with area-equivalent diameter (Deq) < 0.17 mm are mostly liquid at all temperatures sampled, down to −40 ∘C. Larger particles (Deq>0.17 mm) are predominantly frozen at all temperatures below 0 ∘C. Between 0 and 5 ∘C, there are roughly equal numbers of frozen and liquid mid-sized particles (0.17<Deq<0.33 mm), and larger particles (Deq>0.33 mm) are mostly frozen. We also use UWILD's phase classifications to estimate sub-1 Hz phase heterogeneity, and we show examples of meter-scale cloud phase heterogeneity in the SOCRATES dataset.

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Section: Preparation Of Training Validation and Test Datamentioning

confidence: 99%

“…Particle sphericity is a good indicator of particle phase for small and medium-sized particles. However, large liquid drops are typically aspherical or elongated because they are distorted due to pressure differences in the instrument's inlet, as discussed in Supplement 4 of Waitz et al (2021).…”

Section: Preparation Of Training Validation and Test Datamentioning

confidence: 99%

The University of Washington Ice–Liquid Discriminator (UWILD) improves single-particle phase classifications of hydrometeors within Southern Ocean clouds using machine learning

et al. 2021

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“…Phase discrimination by the PHIPS probe is based on analyzing the shape of the single particle angular scattering function as described in detail by Waitz et al. (2021) where it was shown to be 98% accurate. The scattering function is only weakly dependent upon particle size, so phase discrimination could be conducted down to the minimum detectable ice particle size, which was set to 20 μm for SOCRATES.…”

Section: Observations and Analysismentioning

confidence: 99%

“…Ice particles can sometimes collide with probes and shatter, artificially inflating number concentrations and decreasing mean sizes (e.g., Korolev et al., 2011), and this can also occur with the PHIPS probe. In the standard release of the PHIPS data set, the data are automatically flagged as possibly influenced by shattering when more than 10% of all particles measured by the 2DS at that time exceed 800 μm diameter (Waitz et al., 2021). However, in this study, the presence of such large particles on the optical array probes is often indicative of graupel/frozen raindrops, which are a necessary ingredient for the rime‐splintering process, so additional manual scrutiny of the PHIPS data for all 32 of the cloud passes was performed to attain careful, best estimates of the number concentrations of ice particles less than 60 μm diameter.…”

Section: Observations and Analysismentioning

confidence: 99%

“…The microphysical data used in this study include: size distributions of cloud droplets from 2 to 50 μm diameter from the Cloud Droplet Probe (CDP; Lance et al, 2010), the presence of supercooled cloud droplets as indicated by the Rosemount Icing Detector (RICE; Baumgardner & Rodi, 1989), the presence of graupel/ rimed frozen raindrops as indicated by 2D images of particles 200-1,600 μm in diameter (with 25 μm resolution) from the 2DC Probe (for which occasional condensation on the probe mirrors during SOCRATES made number concentrations unreliable Finlon et al, 2020), and liquid and ice particle size distributions and images for particles 60-700 μm and 20-700 μm in diameter (with 6.2-6.8 μm resolution, depending on the camera taking the images), respectively, from the PHIPS probe (Abdelmonem et al, 2016;Schnaiter et al, 2018;Waitz et al, 2021). Phase discrimination by the PHIPS probe is based on analyzing the shape of the single particle angular scattering function as described in detail by Waitz et al (2021) where it was shown to be 98% accurate. The scattering function is only weakly dependent upon particle size, so phase discrimination could be conducted down to the minimum detectable ice particle size, which was set to 20 μm for SOCRATES.…”

Section: Measurements and Data Processingmentioning

confidence: 99%

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Observations and Modeling of Rime Splintering in Southern Ocean Cumuli

et al. 2021

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Recent studies have suggested a correct representation of cloud phase in the Southern Ocean region is important in climate models for an accurate representation of the energy balance. Satellite retrievals indicate many of the clouds are predominantly liquid, despite their low temperatures. However, clouds containing high numbers of ice crystals have sometimes been observed in this region and implicated the secondary ice production process called rime splintering. This study re‐examines rime splintering in Southern Ocean cumuli using both a new data set and high‐resolution numerical modeling. Measurements acquired during the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES) provide an evaluation of the amount of ice in shallow cumuli sampled over two days in this region. The measurements sometimes exhibit seven orders of magnitude or more ice particles compared to amounts expected from measurements of ice‐nucleating particles (INP) on the same days. Cumuli containing multiple updrafts had the greatest tendency to contain high ice concentrations and meet the expected conditions for rime splintering. Idealized numerical modeling, constrained by the observations, suggests that the multiple updrafts produce more frozen raindrops/graupel, and allow them to travel through the rime‐splintering zone over an extended period of time, increasing the number of ice particles by many orders of magnitude. The extremely low number of INP in the Southern Ocean thus appears to require special conditions like multiple updrafts to help glaciate the cumuli in this region, potentially explaining the predominance of supercooled cumuli observed there.

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PHIPS-HALO: the airborne particle habit imaging and polar scattering probe – Part 3: Single Particle Phase Discrimination and Particle Size Distribution based on Angular Scattering Function

Cited by 2 publications

References 25 publications

The University of Washington Ice–Liquid Discriminator (UWILD) improves single-particle phase classifications of hydrometeors within Southern Ocean clouds using machine learning

The University of Washington Ice–Liquid Discriminator (UWILD) improves single-particle phase classifications of hydrometeors within Southern Ocean clouds using machine learning

Observations and Modeling of Rime Splintering in Southern Ocean Cumuli

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