Mass content wl derived by DMT, using CAM and OPM as a function of wl derived using a constant wire temperature and dry-air term parameterization by the Reynolds and Prandtl numbers (Zukauskas and Ziugzda 1985) for measurements made with a PMS LWC hot-wire sensor mounted on the Aerocommander aircraft during the 2011 CAIPEEX over the Indian Ocean. The clouds sampled were all liquid water with no ice.
(left) Measured PC/PR (black) from Nevzorov wt sensor. Cases include data from (top) a trailing stratiform region of a mesoscale convective system collected using the University of North Dakota (UND) Citation, (middle) supercooled convective showers collected using the UND Citation, and (bottom) midlatitude cirrus collected using the FAAM BAe-146 research aircraft. K parameter calculated by G1 and G2 shown in red and green, respectively. (right) Comparison of the calculated wt from G1 and G2. The red line is the 1:1 line.
(left) Activity-based coincidence-corrected concentration as a function of raw (measured) concentration from the FSSP for values of fixed m of 0.54 (red) and 0.71 (blue) and for the statistical method of Brenguier and Amodei (green) for data collected during 2013 COPE over southwest England using the University of Wyoming King Air for 3–4-min penetrations on 3 days during periods that did not appear to contain any precipitation-sized particles. (right) Activity-based coincidence-corrected concentrations from the FSSP for the same dataset shown in (left), but compared to measured concentrations from a CDP on the same aircraft.
Example of size distribution from CDP in fair-weather cumulus cloud sampled during FAAM flight B792 from 44 139 to 44 154 s after 0000 local time and from a 3–30-μm polydisperse bead sample (provided by Whitehouse Scientific) plotted using the manufacturer’s specifications and using the Rosenberg et al. (2012) calibration converting from σ to D. Errors bars are 1-sigma and are dominated by the calibration errors. The manufacturer does not provide bin width uncertainties, so the data processed with the manufacturer’s specifications have no error bars included.
Synthetically generated gamma function describing N(Dmax) for synthetically generated particles from the 2DC, CIP, and 2DS following the procedure discussed in the text. (right) Example images from the 2DS, CIP, and 2DC for time frames of approximately 0.2, 0.25, and 0.75 s long, respectively, with scales indicated at the bottom of the figure.
Images of three 200-μm particles synthetically generated for a 2DS probe. Table 11-2 gives estimated Lp, Wp, Dmax, Pp, and Ap from different processing algorithms for these 3 particles. The Z positions (relative to midpoint between the arms) of the particles are 21.4 mm (particle 28), 24.2 mm (particle 83), and 0.1 mm (particle 517).
Relationship between particle length determined from a gray probe depending upon whether 70% or 50% shadowing was used to define the particles. This comparison was constructed from water droplets measured with an airborne CIP-Gray probe. The embedded filmstrip shows representative particles that were imaged by the probe for the time period analyzed.
(top) N(Dmax) as function of Dmax using six different definitions of Dmax; (bottom) the ratio of N(Dmax)/N(Ds) for Dmax using different definitions of maximum dimension indicated by DT, DP, DA, DL, DH, and Ds for data collected in the trailing stratiform region of a mesoscale convective system sampled on 20 May 2011 during the Mid-Latitude Clouds, Convection and Chemistry Experiment (MC3E). Adapted from Wu and McFarquhar (2016), who provide the definitions of DT, DP, DA, DL, DH, and DS. The DT and DP are denoted as Lp and Wp, respectively, in this study.
Habit fraction by number for 30-s time intervals produced from different algorithms [UM09 and SPEC CPIView (SPEC)] for ice crystals with Dmax > 50 μm imaged by CPI during the (top) Tropical Warm Pool International Cloud Experiment (TWP-ICE) and (bottom) Indirect and Semi-Direct Aerosol Campaign (ISDAC). UM09 has 12 habits: small- (SQ), medium- (MQ), and large-quasi sphere (LQ), plate (PLT), aggregates of plates (APs), bullet rosette (BR), aggregates of bullet rosettes (ABRs), column (COL), aggregates of columns (ACs), dendrite (DEN), capped column (CC), and unclassified (UC). SPEC has 7 habits: spheroid (SPR), PLT, rosette (ROS), COL, budding rosette (BROS), small irregular (SIR), and big irregular (BIR).
N(Dmax) as a function of Dmax from several processing algorithms applied to the same raw data file obtained by a CIP and PIP installed on the NOAA P-3 aircraft in Hurricane Isaac in 2012. The three-letter acronyms in front of the CIP/PIP refer to different processing algorithms: the specific algorithms for each SD were not identified at the 2014 MIT workshop.
Normalized frequency distribution of interarrival times recorded by a 2DS probe installed on a French Falcon aircraft during the collaborative 2014 HAIC/HIWC project on 18 Feb 2014. Solid lines represent best fits to modes of peaks describing naturally occurring particles and shattered artifacts, generated following approach of Jackson et al. (2014).
Normalized frequency distribution of interarrival time as function of flight time for HAIC/HIWC flight on 18 Feb. 2014. Different colored lines represent τ1 (purple), τ2 (yellow) and three different thresholds used to define boundary between naturally occurring particles and shattered artifacts: twice τ2 (gray), the interarrival time between τ1 and τ2 with smallest measured frequency of occurrence (red, minimum of raw frequency) and the interarrival time between τ1 and τ2 with the smallest frequency of occurrence based on fit curves to the frequency of occurrence for the two Gaussian distributions (cyan, minimum of fitted curves).
