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At least 19 records

Observed and Bin Model Simulated Evolution of Drop Size Distributions in High-Based Cumulus Congestus Over the United Arab Emirates

This study examines microphysical processes in developing high-based cumulus congestus over the United Arab Emirates using aircraft observations and a large-eddy-simulation model with bin microphysics. A notable feature of this case is the lack of mm-sized drops despite having a liquid cloud layer >3.5 km deep, contrasting with copious large drops observed in maritime tropical cumulus congestus having a similar vertical extent. Modeled drop size distributions are similar to observations at various temperatures between 9.5 and –12°C, including the lack of mm-sized drops. Cloud dilution leads to low-to-moderate liquid water contents (~0.5–1.5 g m –3 ) in most of the cloud core, several times smaller than adiabatic values. Dilution is enhanced in the inflowing branch of the toroidal circulations associated with individual cloud thermals, which are favored regions for secondary droplet activation (activation above cloud base). Secondary activation in general contributes substantially to the droplet population. Turning it off leads to a sharp decrease in droplet concentration and increase in mean size aloft, but does little to increase rain drop production. Warm rain generation (or lack thereof) in this case is therefore determined more by the sub-cloud aerosol and the cloud base droplet size distribution (DSD) than DSD evolution aloft from secondary droplet activation. Decreasing the aerosol concentration by a factor of 10 greatly increases production of large drops via collision-coalescence. Thus, despite its high base (low temperatures) and substantial dilution, the simulated cloud is thermodynamically and dynamically capable of rapidly producing copious mm-sized drops from collision-coalescence under pristine aerosol conditions.

54 ENVIRONMENTAL SCIENCES↗

Small-Scale Drop-Size Variability: Empirical Models for Drop-Size-Dependent Clustering in Clouds

By analyzing aircraft measurements of individual drop sizes in clouds, it has been shown in a companion paper that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)), where 0 less than or equals D(r) less than or equals 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and a Poisson distribution of cloud drops, these models illustrate strong drop clustering, especially with larger drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics, including how fast rain can form. For radiative transfer theory, clustering of large drops enhances their impact on the cloud optical path. The clustering phenomenon also helps explain why remotely sensed cloud drop size is generally larger than that measured in situ.

Marshak, Alexander↗

Evaluating Entrainment–Mixing Characteristics through Direct Comparisons of Drop Size Distributions Using In Situ Observations from ACE-ENA

Abstract Constraining the impacts of entrainment and associated mixing (i.e., entrainment–mixing) on cloud properties continues to be difficult, partly due to observational uncertainties as well as a lacking consensus of which methodologies for diagnosing entrainment–mixing are most appropriate. This study introduces a novel method to evaluate the presence and degree of inhomogeneous and homogeneous mixing using ∼100 h of in situ observations from a research aircraft over the northeastern Atlantic. Specifically, drop size distributions are compared between regions containing negligible and significant entrainment for select flight legs, making a direct characterization of the degree of homogeneous and inhomogeneous mixing possible. A measure of drop concentration variance is used as a proxy variable to diagnose entrainment–mixing. Results correspond well with entrainment–mixing metrics, showing lower Damköhler numbers where drop size distributions shift toward smaller drop sizes (i.e., inhomogeneous mixing) and greater transition length scales where drop size distributions do not (i.e., homogeneous mixing). Inhomogeneous mixing occurs in most samples from Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) (regardless of homogeneous mixing frequencies increasing with increasing spatial resolution from ∼100 to ∼10 m) and is associated with decreased drop size relative dispersion and both greater aerosol and drop concentrations compared with homogeneous mixing. Precipitating clouds have a greater frequency of homogeneous mixing compared with nonprecipitating clouds. The proposed methodology is similarly applied to in situ observations of southeast Pacific stratocumulus, shallow convective clouds over central Oklahoma and low-level clouds over the Southern Ocean. All four locations are primarily dominated by inhomogeneous mixing with minimal variability among each region.

Clouds↗

Automated holographic drop-size analyzer

System analyzes drop-size distribution in liquid-droplet-spray combustion fields. Holographic camera takes "stop-motion" hologram of combustion volume; it is then viewed by vidicon camera connected to digital data-processing system that identifies particles or droplets, determining their size and count, and displays histogram of drop-size distribution in holographic field.

Feinstein, S. P.↗

Nasa Glenn Icing Research Tunnel: 2018 Change in Drop-Sizing Equations Due to Change in Cloud Droplet Probe Sample Area

Although there has been no physical change to the cloud drop diameters in the NASA Glenn Icing Research Tunnel (IRT), the IRT cloud calibration team now has an improved understanding of the facility’s drop-sizing instrumentation, which has resulted in a recent change to the drop-sizing equations. Only the calculated values given in the previous calibration report have changed. In 2017, IRT staff found reason to believe that since at least 2014, the sample area for its Cloud Droplet Probe (CDP) (Droplet Measurement Technologies, Inc.) has been closer to 0.289 mm2, rather than the user manual’s suggested value of 0.24 mm2. In September 2017, the probe’s sample area was measured both before and after the probe was realigned, and the end sample area was measured to be 0.248 mm2. Following the probe’s realignment, drop size measurements were made in the IRT using the CDP as well as optical array probes OAP–230X and OAP–230Y (Particle Measurement Systems, Inc.). These measurements suggested that 0.289 mm2 was the more accurate value for historical measurements. When the CDP sample area used for calculations was changed from 0.24 to 0.289 mm2, distributions previously reported to have a median volumetric diameter (MVD) between 30 and 100 μm were instead calculated to have MVD values 10 to 18 percent higher. The analyses that led to these conclusions are reported in this paper, as well as the new drop-sizing equations that have been developed for the corrected measurement values. This report contains updates to drop-sizing data for the IRT’s “normal” operating conditions (MVD < 50 μm) and discusses the effects on the IRT’s “large-drop” conditions (Mod1 nozzles, Pair < 10 psig), but it does not include updates to the drop-sizing equations for those large-drop conditions.

Particle sizing↗

Initial drop size and velocity distributions for airblast coaxial atomizers

Phase Doppler measurements were used to determine initial drop size and velocity distributions after a complete disintegration of coaxial liquid jets. The Sauter mean diameter (SMD) distribution was found to be strongly affected by the structure and behavior of the preceding liquid intact jet. The axial measurement stations were determined from the photographs of the coaxial liquid jet at very short distances (1-2 mm) downstream of the observed break-up locations. Minimum droplet mean velocities were found at the center, and maximum velocities were near the spray boundary. Size-velocity correlations show that the velocity of larger drops did not change with drop size. Drop rms velocity distributions have double peaks whose radial positions coincide with the maximum mean velocity gradients.

Eroglu, H.↗

Spray drop size and velocity measurements using the Phase/Doppler Particle Analyzer

Detailed measurements of the drop size and velocity distributions were obtained for a swirl chamber pressure atomizer. These data were obtained with the Phase/Doppler Particle Analyzer manufactured by Aerometrics, Inc. Direct measurements of the size distributions revealed the evolving characteristics of the spray. Size velocity correlations were used to evaluate the effect of velocity relaxation on the size distributions. The simultaneous measurement of drop size and velocity was of major importance in accurately describing the changes in the local drop size distributions and mass flux.

Bachalo, W. D.↗

Drop size distributions and related properties of fog for five locations measured from aircraft

Fog drop size distributions were collected from aircraft as part of the Synthetic Vision Technology Demonstration Program. Three west coast marine advection fogs, one frontal fog, and a radiation fog were sampled from the top of the cloud to the bottom as the aircraft descended on a 3-degree glideslope. Drop size versus altitude versus concentration are shown in three dimensional plots for each 10-meter altitude interval from 1-minute samples. Also shown are median volume radius and liquid water content. Advection fogs contained the largest drops with median volume radius of 5-8 micrometers, although the drop sizes in the radiation fog were also large just above the runway surface. Liquid water content increased with height, and the total number of drops generally increased with time. Multimodal variations in number density and particle size were noted in most samples where there was a peak concentration of small drops (2-5 micrometers) at low altitudes, midaltitude peak of drops 5-11 micrometers, and high-altitude peak of the larger drops (11-15 micrometers and above). These observations are compared with others and corroborate previous results in fog gross properties, although there is considerable variation with time and altitude even in the same type of fog.

Zak, J. Allen↗

Phase Doppler Interferometry for Efficient Cloud Drop Size Distribution, Number Density, and LWC Measurements

Threats to aviation safety as a result of super-cooled large drops (SLD) has been addressed by the FAA rules change (14 CFR Part 25) with the additional icing certification requirement. SLD clouds often consist of bi-modal drop size spectra leading to significant problems in simulating and characterizing these conditions in situ and in icing wind tunnels. Legacy instrumentation for measuring drop size distributions and liquid water content are challenged under these conditions. The large size range measurement problem is addressed with the development of the Phase Doppler Interferometer, Flight Probe Dual-Range (PDI FPDR). The method is described in this report along with the measurement capabilities including the dynamic measurement range and overall working size range. The PDI instrument bases drop size measurements on the light wavelength as the measurement length scale. The light wavelength is a much more robust scale, especially as compared to the light scattering intensity. Additionally, methods for accurately characterizing the sample volume in situ based on measured drop velocity and transit time are reviewed, given the importance of this parameter for merging results and measuring LWC. Droplet coincidence in the sample volume can be problematic so this condition is treated with an innovative signal parsing approach. Measurement examples acquired in the NASA IRT are provided. Measurements of LWC showed good agreement with the Artium Particle Imaging (PI) instrument but diverged from the tunnel calibration results for larger MVD values.

42 ENGINEERING↗

Velocity and drop size measurements in a confined, swirl-stabilized, combusting spray

Drop size and velocity measurements in a confined, swirl-stabilized, reacting spray are presented. The configuration consisted of a center-mounted research air-assist atomizer surrounded by a coflowing air stream. A quartz tube surrounded the burner and provided the confinement. Both the air-assist and coflow streams had swirl imparted to them in the same direction with 45-degree-angle swirlers. The fuel and air entered the combustor at ambient temperature. The gas-phase measurements reported were obtained from the velocity drops with a mean diameter of four microns. Heptane fuel was used for all the experiments. Measurements of drop size and velocity, gas-phase velocity and drop number flux are reported for axial distances of 23, 5, 10, 15, 25, and 50 mm downstream of the nozzle. The measurements were performed using a two-component phase/Doppler particle analyzer. Profiles across the entire flowfield are presented.

Bulzan, Daniel L.↗

Sensitivity of a GCM climate simulation to differences in continental versus maritime cloud drop size

Extensive observations indicate a distinct difference between maritime and continental effective drop size, r(sub e), for warm clouds. The latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM2) is used to explore the sensitivity of differentiating between continental and maritime r(sub e) on the simulated climate. The results of this study indicate that the smaller drop size over continents leads to a reduction of surface-absorbed solar radiation from 20 to 60 W/sq m. This reduction in surface solar flux leads to a cooling of the continents by up to -3.5 K. The reduction in surface solar flux and temperature also leads to a reduction in latent heat flux and precipitation over land. In the January simulation, there is a significant shift in tropical precipitation associated with the Australian monsoon. This shift leads to a response in the extra tropical geopotential height field over the western United States. All of these changes reduce biases in the current version of CCM2.

Kiehl, J. T.↗

Small-Scale Drop Size Variability: Impact on Estimation of Cloud Optical Properties

Most cloud radiation models and conventional data processing techniques assume that the mean number of drops of a given radius is proportional to volume. The analysis of microphysical data on liquid water drop sizes shows that, for sufficiently small volumes, this proportionality breaks down; the number of cloud drops of a given radius is instead proportional to the volume raised to a drop size-dependent nonunit power. The coefficient of proportionality, a generalized drop concentration, is a function of the drop size. For abundant small drops the power is unity as assumed in the conventional approach. However, for rarer large drops, it falls increasingly below unity. This empirical fact leads to drop clustering, with the larger drops exhibiting a greater degree of clustering. The generalized drop concentration shows the mean number of drops per cluster, while the power characterizes the occurrence frequency of clusters. With a fixed total number of drops in a cloud, a decrease in frequency of clusters is accompanied by a corresponding increase in the generalized concentration. This initiates a competing process missed in the conventional models: an increase in the number of drops per cluster enhances the impact of rarer large drops on cloud radiation while a decrease in the frequency suppresses it. Because of the nonlinear relationship between the number of clustered drops and the volume, these two opposite tendencies do not necessarily compensate each other. The data analysis suggests that clustered drops likely have a stronger radiative impact compared to their unclustered counterpart; ignoring it results in underestimation of the contribution from large drops to cloud horizontal optical path.

Knyazikhin, Y.↗

The Influence of SLD Drop Size Distributions on Ice Accretion in the NASA Icing Research Tunnel

An ice shape database has been created to document ice accretions on a 21-inch chord NACA0012 model and a 72-inch chord NACA 23012 airfoil model resulting from an exposure to a Supercooled Large Drop (SLD) icing cloud with a bimodal drop size distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions used in the test matrix were based upon previously used conditions on the same models but with an alternate approach to evaluation of drop distribution effects. Ice shapes resulting from the bimodal distribution as well as from equivalent monomodal drop size distributions were obtained and compared. Results indicate that the ice shapes resulting from the monomodal and bimodal drop size distributions had similar shapes, but the bimodal distributions had greater mass and volume measurements and icing limits that extended further back on the chord of the model.

Potapczuk, Mark G.↗

3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer

Determining the Z-R relationship (where Z is the radar reflectivity factor and R is rainfall rate) from disdrometer data has been and is a common goal of cloud physicists and radar meteorology researchers. The usefulness of this quantity has traditionally been limited since radar represents a volume measurement, while a disdrometer corresponds to a point measurement. To solve that problem, a 3D-DSD (drop-size distribution) method of determining an equivalent 3D Z-R was developed at the University of Central Florida and tested at the Kennedy Space Center, FL. Unfortunately, that method required a minimum of three disdrometers clustered together within a microscale network (.1-km separation). Since most commercial disdrometers used by the radar meteorology/cloud physics community are high-cost instruments, three disdrometers located within a microscale area is generally not a practical strategy due to the limitations of these kinds of research budgets. A relatively simple modification to the 3D-DSD algorithm provides an estimate of the 3D-DSD and therefore, a 3D Z-R measurement using a single disdrometer. The basis of the horizontal extrapolation is mass conservation of a drop size increment, employing the mass conservation equation. For vertical extrapolation, convolution of a drop size increment using raindrop terminal velocity is used. Together, these two independent extrapolation techniques provide a complete 3DDSD estimate in a volume around and above a single disdrometer. The estimation error is lowest along a vertical plane intersecting the disdrometer position in the direction of wind advection. This work demonstrates that multiple sensors are not required for successful implementation of the 3D interpolation/extrapolation algorithm. This is a great benefit since it is seldom that multiple sensors in the required spatial arrangement are available for this type of analysis. The original software (developed at the University of Central Florida, 1998.- 2000) has also been modified to read standardized disdrometer data format (Joss-Waldvogel format). Other modifications to the software involve accounting for vertical ambient wind motion, as well as evaporation of the raindrop during its flight time.

Lane, John↗

Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar Data

Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter D m from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. Here, this estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of C-Band Polarimetric Radar-Based Drop Size Distribution Measurements to Maximum Diameter Assumptions

The estimation of rain drop size distribution (DSD) parameters from polarimetric radar observations is accomplished by first establishing a relationship between differential reflectivity (Z(sub dr)) and the central tendency of the rain DSD such as the median volume diameter (D0). Since Z(sub dr) does not provide a direct measurement of DSD central tendency, the relationship is typically derived empirically from rain drop and radar scattering models (e.g., D0 = F[Z (sub dr)] ). Past studies have explored the general sensitivity of these models to temperature, radar wavelength, the drop shape vs. size relation, and DSD variability. Much progress has been made in recent years in measuring the drop shape and DSD variability using surface-based disdrometers, such as the 2D Video disdrometer (2DVD), and documenting their impact on polarimetric radar techniques. In addition to measuring drop shape, another advantage of the 2DVD over earlier impact type disdrometers is its ability to resolve drop diameters in excess of 5 mm. Despite this improvement, the sampling limitations of a disdrometer, including the 2DVD, make it very difficult to adequately measure the maximum drop diameter (D(sub max)) present in a typical radar resolution volume. As a result, D(sub max) must still be assumed in the drop and radar models from which D0 = F[Z(sub dr)] is derived. Since scattering resonance at C-band wavelengths begins to occur in drop diameters larger than about 5 mm, modeled C-band radar parameters, particularly Z(sub dr), can be sensitive to D(sub max) assumptions. In past C-band radar studies, a variety of D(sub max) assumptions have been made, including the actual disdrometer estimate of D(sub max) during a typical sampling period (e.g., 1-3 minutes), D(sub max) = C (where C is constant at values from 5 to 8 mm), and D(sub max) = M*D0 (where the constant multiple, M, is fixed at values ranging from 2.5 to 3.5). The overall objective of this NASA Global Precipitation Measurement Mission (GPM/PMM Science Team)-funded study is to document the sensitivity of DSD measurements, including estimates of D0, from C-band Z(sub dr) and reflectivity to this range of D(sub max) assumptions. For this study, GPM Ground Validation 2DVD's were operated under the scanning domain of the UAHuntsville ARMOR C-band dual-polarimetric radar. Approximately 7500 minutes of DSD data were collected and processed to create gamma size distribution parameters using a truncated method of moments approach. After creating the gamma parameter datasets the DSD's were then used as input to a T-matrix model for computation of polarimetric radar moments at C-band. All necessary model parameterizations, such as temperature, drop shape, and drop fall mode, were fixed at typically accepted values while the D(sub max) assumption was allowed to vary in sensitivity tests. By hypothesizing a DSD model with D(sub max) (fit) from which the empirical fit to D0 = F[Z(sub dr)] was derived via non-linear least squares regression and a separate reference DSD model with D(sub max) (truth), bias and standard error in D0 retrievals were estimated in the presence of Z(sub dr) measurement error and hypothesized mismatch in D(sub max) assumptions. Although the normalized standard error for D0 = F[Z(sub dr)r] can increase slightly (as much as from 11% to 16% for all 7500 DSDs) when the D(sub max) (fit) does not match D(sub max) (truth), the primary impact of uncertainty in D(sub max) is a potential increase in normalized bias error in D0 (from 0% to as much as 10% over all 7500 DSDs, depending on the extent of the mismatch between D(sub max) (fit) and D(sub max) (truth)). For DSDs characterized by large Z(sub dr) (Z(sub dr) > 1.5 to 2.0 dB), the normalized bias error for D0 estimation at C-band is sometimes unacceptably large (> 10%), again depending on the extent of the hypothesized D(sub max) mismatch. Modeled errors in D0 retrievals from Z(sub dr) at C-band are demonstrated in detail and comparedo similar modeled retrieval errors at S-band and X-band where the sensitivity to D(sub max) is expected to be less. The impact of D(sub max) assumptions to the retrieval of other DSD parameters such as Nw, the liquid water content normalized intercept parameter, are also explored. Likely implications for DSD retrievals using C-band polarimetric radar for GPM are assessed by considering current community knowledge regarding D(sub max) and quantifying the statistical distribution of Z(sub dr) from ARMOR over a large variety of meteorological conditions. Based on these results and the prevalence of C-band polarimetric radars worldwide, a call for more emphasis on constraining our observational estimate of D(sub max) within a typical radar resolution volume is made

Carey, Lawrence D.↗