Airborne Phase Doppler Interferometry for Cloud Microphysical Measurements

Chuang, P. Y.; Saw, Ewe-Wei; Griswold, Jennifer D. Small; Shaw, Raymond A.; Sipperley, Chad; Payne, Gregory A.; Bachalo, W. D.

doi:10.1080/02786820802232956

Cited by 83 publications

(99 citation statements)

References 27 publications

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“…One way of addressing the isoaxial sampling is to put the instrument onto a turntable and letting it continually turn into the main wind direction as done by Vong (1995), Kowalski et al (1997), Kowalski (1999), Wrzesinsky (2000), Burkard et al (2002), Thalmann (2002, Burkard (2003), Eugster et al (2006), andHolwerda et al (2006). Nevertheless, these procedures do not assure isokinetic sampling conditions.…”

Section: Sampling Lossesmentioning

confidence: 99%

“…The FM-100 has been used in several ground based studies so far especially as part of an eddy covariance system to quantify fog water deposition fluxes in tropical mountain cloud forests (e.g. Eugster et al, 2006;Holwerda et al, 2006;Beiderwieden, 2007;Beiderwieden et al, 2008;Schmid et al, 2010), in temperate ecosystems (Burkard et al, 2002;Thalmann, 2002;Burkard, 2003), and deposition fluxes in rather arid areas (Westbeld et al, 2009). It has also been used as a single instrument for microphysical studies of fog (Gonser et al, 2011;Liu et al, 2011) and compared to other devices Schmid et al, 2010;Frumau et al, 2011).…”

Section: Fm-100: Fog Droplet Size Spectrometermentioning

confidence: 99%

“…Using light scattering interferometry, cloud droplets can also be measured in size, for example with the Phase Doppler Interferometer (PIP; 1 to 1000 µm, Baumgardner et al, 2011). However, for realistic operations a reasonable upper-bound was found to be D ≈ 100 µm (Chuang et al, 2008). Furthermore, imaging techniques can be used to capture the cloud's particle images.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)

Spiegel¹,

Zieger²,

Bukowiecki³

et al. 2012

Atmos. Meas. Tech.

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Abstract. Droplet size spectra measurements are crucial to obtain a quantitative microphysical description of clouds and fog. However, cloud droplet size measurements are subject to various uncertainties. This work focuses on the error analysis of two key measurement uncertainties arising during cloud droplet size measurements with a conventional droplet size spectrometer (FM-100): first, we addressed the precision with which droplets can be sized with the FM-100 on the basis of the Mie theory. We deduced error assumptions and proposed a new method on how to correct measured size distributions for these errors by redistributing the measured droplet size distribution using a stochastic approach. Second, based on a literature study, we summarized corrections for particle losses during sampling with the FM-100. We applied both corrections to cloud droplet size spectra measured at the high alpine site Jungfraujoch for a temperature range from 0 • C to 11 • C. We showed that Mie scattering led to spikes in the droplet size distributions using the default sizing procedure, while the new stochastic approach reproduced the ambient size distribution adequately. A detailed analysis of the FM-100 sampling efficiency revealed that particle losses were typically below 10 % for droplet diameters up to 10 µm. For larger droplets, particle losses can increase up to 90 % for the largest droplets of 50 µm at ambient wind speeds below 4.4 m s −1 and even to >90 % for larger angles between the instrument orientation and the wind vector (sampling angle) at higher wind speeds. Comparisons of the FM-100 to other reference instruments revealed that the total liquid water content (LWC) measured by the FM-100 was more sensitive to particle losses than to re-sizing based on Mie scattering, while the total number concentration was only marginally influenced by particle losses. Consequently, for further LWC measurements with the FM-100 we strongly recommend to consider (1) the error arising due to Mie scattering, and (2) the particle losses, especially for larger droplets depending on the set-up and wind conditions.

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Section: Sampling Lossesmentioning

confidence: 99%

Section: Fm-100: Fog Droplet Size Spectrometermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)

Spiegel¹,

Zieger²,

Bukowiecki³

et al. 2012

Atmos. Meas. Tech.

View full text Add to dashboard Cite

show abstract

“…A silica gel diffusion dryer dried the aerosol to < 40 % RH before it was distributed to the instruments. For the measurement of cloud droplet size distributions, a phase doppler interferometer (PDI) for single droplet measurements in the size range of 1 to 180 µm was used (Atrium Technologies; Chuang et al, 2008). The PDI was mounted on the outside, in front of ACTOS, to enable the detection of cloud droplets in situ.…”

Section: Measurementsmentioning

confidence: 99%

Aerosol arriving on the Caribbean island of Barbados: physical properties and origin

et al. 2016

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Abstract. The marine aerosol arriving at Barbados (Ragged Point) was characterized during two 3-week long measurement periods in November 2010 and April 2011, in the context of the measurement campaign CARRIBA (Cloud, Aerosol, Radiation and tuRbulence in the trade wInd regime over BArbados). Through a comparison between groundbased and airborne measurements it was shown that the former are representative of the marine boundary layer at least up to cloud base. In general, total particle number concentrations (N total ) ranged from as low as 100 up to 800 cm −3 , while number concentrations for cloud condensation nuclei (N CCN ) at a supersaturation of 0.26 % ranged from some 10 to 600 cm −3 . N total and N CCN depended on the air mass origin. Three distinct types of air masses were found. One type showed elevated values for both N total and N CCN and could be attributed to long-range transport from Africa, by which biomass burning particles from the Sahel region and/or mineral dust particles from the Sahara were advected. The second and third type both had values for N CCN below 200 cm −3 and a clear minimum in the particle number size distribution (NSD) around 70 to 80 nm (Hoppel minimum). While for one of these two types the accumulation mode was dominating (albeit less so than for air masses advected from Africa), the Aitken mode dominated the other and contributed more than 50 % of all particles. These Aitken mode particles likely were formed by new particle formation no more than 3 days prior to the measurements. Hygroscopicity of particles in the CCN size range was determined from CCN measurements to be κ = 0.66 on average, which suggests that these particles contain mainly sulfate and do not show a strong influence from organic material, which might generally be the case for the months during which measurements were made. The average κ could be used to derive N CCN from measured number size distributions, showing that this is a valid approach to obtain N CCN . Although the total particulate mass sampled on filters was found to be dominated by Na + and Cl − , this was found to be contributed by a small number of large particles (> 500 nm, mostly even in the super-micron size range). Based on a three-modal fit, a sea spray mode observed in the NSDs was found to contribute 90 % to the total particulate mass but only 4 to 10 % to N total and up to 15 % to N CCN . This is in accordance with finding no correlation between N total and wind speed.

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“…During the two flight dates the PDI was slightly misaligned and this had two consequences. First, as described by Chuang et al (2008), the PDI sample volume is determined by analyzing the distribution of droplet transit times. The low signal-noise ratio (SNR) resulting from misalignment led to unreliable transit times, so that a reliable estimate of the sample volume could not be obtained.…”

Section: The Cloud Responsementioning

confidence: 99%

The fine-scale structure of the trade wind cumuli over Barbados – an introduction to the CARRIBA project

et al. 2013

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Abstract. The CARRIBA (Cloud, Aerosol, Radiation and tuRbulence in the trade wInd regime over BArbados) project, focused on high resolution and collocated measurements of thermodynamic, turbulent, microphysical, and radiative properties of trade wind cumuli over Barbados, is introduced. The project is based on two one-month field campaigns in November 2010 (climatic wet season) and April 2011 (climatic dry season). Observations are based on helicopterborne and ground-based measurements in an area of 100 km 2 off the coast of Barbados. CARRIBA is accompanied by long-term observations at the Barbados Cloud Observatory located at the East coast of Barbados since early in 2010 and which provides a longer-term context for the CARRIBA measurements. The deployed instrumentation and sampling strategy are presented together with a classification of the meteorological conditions. The two campaigns were influenced by different air masses advected from the Caribbean area, the Atlantic Ocean, and the African continent which led to distinct aerosol conditions. Pristine conditions with low aerosol particle number concentrations of ∼100 cm 3 were alternating with periods influenced by Saharan dust or aerosol from biomass burning resulting in comparably high number concentrations of ∼ 500 cm 3 . The biomass burning aerosol was originating from both the Caribbean area and Africa. The shallow cumulus clouds responded to the different aerosol conditions with a wide range of mean droplet sizes and number concentrations. Two days with different aerosol and cloud microphysical properties but almost identical meteorological conditions have been analyzed in detail. The differences in the droplet number concentration and droplet sizes appear not to show any significant change for turbulent cloud mixing, but the relative roles of droplet inertia and sedimentation in initiating coalescence, as well as the cloud reflectivity, do change substantially.

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Airborne Phase Doppler Interferometry for Cloud Microphysical Measurements

Cited by 83 publications

References 27 publications

Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)

Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)

Aerosol arriving on the Caribbean island of Barbados: physical properties and origin

The fine-scale structure of the trade wind cumuli over Barbados – an introduction to the CARRIBA project

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