Holographic measurements of inhomogeneous cloud mixing at the centimeter scale

Beals, Matthew; Fugal, Jacob P.; Shaw, Raymond A.; Lu, Jiang; Spuler, Scott M.; Stith, Jeffrey L.

doi:10.1126/science.aab0751

Cited by 135 publications

(169 citation statements)

References 75 publications

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“…11 was taken at an altitude of 2300 m with smaller ice crystal (< 50 cm −3 ) and cloud droplet (< 50 cm −3 ) number concentrations. This is in the region of the cloud base and the cloud volume is strongly diluted and filamented possibly due to turbulent mixing with clear air as it was also observed in Beals et al (2015). This observation is reflected in a small value of R of 0.51.…”

Section: Mixed-phase Casementioning

confidence: 79%

“…This is of particular importance for the HoloGondel platform, because the air speed through the instrument depends on the varying wind speed and the travel velocity of the cable car. Finally it provides the spatial distribution of the particles in the sample volume on a millimeter scale (Beals et al, 2015). The principal disadvantage of holographic imaging systems is the high computational power required for data reconstruction and data analysis.…”

mentioning

confidence: 99%

“…Digital in-line holography has been previously used in a series of airborne (Conway et al, 1982;Beals et al, 2015) and ground-based field instruments (Thompson, 1964;Kozikowska et al, 1984;Borrmann and Jaenicke, 1993;Raupach et al, 2006;Henneberger et al, 2013). In comparison to other in situ cloud probes, holographic imagers have specific advantages and disadvantages (see Baumgardner et al, 2011).…”

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confidence: 99%

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HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

et al. 2017

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Abstract. In situ observations of cloud properties in complex alpine terrain where research aircraft cannot sample are commonly conducted at mountain-top research stations and limited to single-point measurements. The HoloGondel platform overcomes this limitation by using a cable car to obtain vertical profiles of the microphysical and meteorological cloud parameters. The main component of the HoloGondel platform is the HOLographic Imager for Microscopic Objects (HOLIMO 3G), which uses digital in-line holography to image cloud particles. Based on two-dimensional images the microphysical cloud parameters for the size range from small cloud particles to large precipitation particles are obtained for the liquid and ice phase. The low traveling velocity of a cable car on the order of 10 m s −1 allows measurements with high spatial resolution; however, at the same time it leads to an unstable air speed towards the HoloGondel platform. Holographic cloud imagers, which have a sample volume that is independent of the air speed, are therefore well suited for measurements on a cable car. Example measurements of the vertical profiles observed in a liquid cloud and a mixed-phase cloud at the Eggishorn in the Swiss Alps in the winters 2015 and 2016 are presented. The HoloGondel platform reliably observes cloud droplets larger than 6.5 µm, partitions between cloud droplets and ice crystals for a size larger than 25 µm and obtains a statistically significantly size distribution for every 5 m in vertical ascent.

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Section: Mixed-phase Casementioning

confidence: 79%

mentioning

confidence: 99%

mentioning

confidence: 99%

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HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

et al. 2017

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“…This behavior is the outcome of the almost completely inhomogeneous mixing behavior of the clouds with the ambient air (Burnet and Brenguier, 2007;Freud et al, 2011). Recently, Beals et al (2015) wrote that their "measurements reveal that turbulent clouds are inhomogeneous, with sharp transitions between cloud and clear air properties persisting to dissipative scales (< 1 cm). The local droplet size distribution fluctuates strongly in number density but with a nearly unchanging mean droplet diameter".…”

Section: Estimating N Amentioning

confidence: 99%

Comparing parameterized versus measured microphysical properties of tropical convective cloud bases during the ACRIDICON–CHUVA campaign

et al. 2017

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Abstract. The objective of this study is to validate parameterizations that were recently developed for satellite retrievals of cloud condensation nuclei supersaturation spectra, N CCN (S), at cloud base alongside more traditional parameterizations connecting N CCN (S) with cloud base updrafts and drop concentrations. This was based on the HALO aircraft measurements during the ACRIDICON-CHUVA campaign over the Amazon region, which took place in September 2014. The properties of convective clouds were measured with a cloud combination probe (CCP), a cloud and aerosol spectrometer (CAS-DPOL), and a CCN counter onboard the HALO aircraft. An intercomparison of the cloud drop size distributions (DSDs) and the cloud water content (CWC) derived from the different instruments generally shows good agreement within the instrumental uncertainties. To this end, the directly measured cloud drop concentrations (N d ) near cloud base were compared with inferred values based on the measured cloud base updraft velocity (W b ) and N CCN (S) spectra. The measurements of N d at cloud base were also compared with drop concentrations (N a ) derived on the basis of an adiabatic assumption and obtained from the vertical evolution of cloud drop effective radius (r e ) above cloud base. The measurements of N CCN (S) and W b reproduced the observed N d within the measurements uncertainties when the old (1959) Twomey's parameterization was used. The agreement between the measured and calculated N d was only within a factor of 2 with attempts to use cloud base S, as obtained from the measured W b , N d , and N CCN (S). This underscores the yet unresolved challenge of aircraft measurements of S in clouds. Importantly, the vertical evolution of r e with height reproduced the observation-based nearly adiabatic cloud base drop concentrations, N a . The combination of these results provides aircraft observational support for the various components of the satellite-retrieved methodology that was recently developed to retrieve N CCN (S) under the base of convective clouds. This parameterization can now be applied with the proper qualifications to cloud simulations and satellite retrievals.

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“…It should be mentioned that the CDSD observed in previous studies might have the problem of instrumental broadening due to low instrument resolution or long-distance averaging of the sampling volume (Brenguier et al, 2011;Devenish et al, 2012). A broad CDSD is also observed by recent holographic measurements, which limit the effect of instrument broadening and have much higher temporal and spatial resolution than other instruments, such as particle-counting probes (Beals et al, 2015;Glienke et al, 2017;Desai et al, 2018).…”

Section: Discussionmentioning

confidence: 90%

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

et al. 2018

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Abstract. Cloud droplet size distributions (CDSDs), which are related to cloud albedo and rain formation, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a moving-size-grid cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, submicrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with early work. The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by numerous smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are as follows: (1) droplets form on aerosols of different sizes, and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in situ measurements and 3-D dynamic models.

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Holographic measurements of inhomogeneous cloud mixing at the centimeter scale

Cited by 135 publications

References 75 publications

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

HoloGondel: in situ cloud observations on a cable car in the Swiss Alps using a holographic imager

Comparing parameterized versus measured microphysical properties of tropical convective cloud bases during the ACRIDICON–CHUVA campaign

Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

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