scholarly journals Effective Radius of Ice Particles in Cirrus and Contrails

2011 ◽  
Vol 68 (2) ◽  
pp. 300-321 ◽  
Author(s):  
U. Schumann ◽  
B. Mayer ◽  
K. Gierens ◽  
S. Unterstrasser ◽  
P. Jessberger ◽  
...  

Abstract This paper discusses the ratio C between the volume mean radius and the effective radius of ice particles in cirrus and contrails. The volume mean radius is proportional to the third root of the ratio between ice water content and number of ice particles, and the effective radius measures the ratio between ice particle volume and projected cross-sectional area. For given ice water content and number concentration of ice particles, the optical depth scales linearly with C. Hence, C is an important input parameter for radiative forcing estimates. The ratio C in general depends strongly on the particle size distribution (PSD) and on the particle habits. For constant habits, C can be factored into a PSD and a habit factor. The PSD factor is generally less than one, while the habit factor is larger than one for convex or concave ice particles with random orientation. The value of C may get very small for power-law PSDs with exponent n between −4 and 0, which is often observed. For such PSDs, most of the particle volume is controlled by a few large particles, while most of the cross-sectional area is controlled by the many small particles. A new particle habit mix for contrail cirrus including small droxtal-shape particles is suggested. For measured cirrus and contrails, the dependence of C on volume mean particle radius, ambient humidity, and contrail age is determined. For cirrus, C varies typically between 0.4 and 1.1. In contrails, C = 0.7 ± 0.3, with uncertainty ranges increasing with the volume radius and contrail age. For the small particles in young contrails, the extinction efficiency in the solar range deviates considerably from the geometric optics limit.

2012 ◽  
Vol 51 (3) ◽  
pp. 655-671 ◽  
Author(s):  
Robin J. Hogan ◽  
Lin Tian ◽  
Philip R. A. Brown ◽  
Christopher D. Westbrook ◽  
Andrew J. Heymsfield ◽  
...  

AbstractThe assumed relationship between ice particle mass and size is profoundly important in radar retrievals of ice clouds, but, for millimeter-wave radars, shape and preferred orientation are important as well. In this paper the authors first examine the consequences of the fact that the widely used “Brown and Francis” mass–size relationship has often been applied to maximum particle dimension observed by aircraft Dmax rather than to the mean of the particle dimensions in two orthogonal directions Dmean, which was originally used by Brown and Francis. Analysis of particle images reveals that Dmax ≃ 1.25Dmean, and therefore, for clouds for which this mass–size relationship holds, the consequences are overestimates of ice water content by around 53% and of Rayleigh-scattering radar reflectivity factor by 3.7 dB. Simultaneous radar and aircraft measurements demonstrate that much better agreement in reflectivity factor is provided by using this mass–size relationship with Dmean. The authors then examine the importance of particle shape and fall orientation for millimeter-wave radars. Simultaneous radar measurements and aircraft calculations of differential reflectivity and dual-wavelength ratio are presented to demonstrate that ice particles may usually be treated as horizontally aligned oblate spheroids with an axial ratio of 0.6, consistent with them being aggregates. An accurate formula is presented for the backscatter cross section apparent to a vertically pointing millimeter-wave radar on the basis of a modified version of Rayleigh–Gans theory. It is then shown that the consequence of treating ice particles as Mie-scattering spheres is to substantially underestimate millimeter-wave reflectivity factor when millimeter-sized particles are present, which can lead to retrieved ice water content being overestimated by a factor of 4.


2015 ◽  
Vol 15 (20) ◽  
pp. 11729-11751 ◽  
Author(s):  
A. S. Ackerman ◽  
A. M. Fridlind ◽  
A. Grandin ◽  
F. Dezitter ◽  
M. Weber ◽  
...  

Abstract. The aeronautics industry has established that a threat to aircraft is posed by atmospheric conditions of substantial ice water content (IWC) where equivalent radar reflectivity (Ze) does not exceed 20–30 dBZ and supercooled water is not present; these conditions are encountered almost exclusively in the vicinity of deep convection. Part 1 (Fridlind et al., 2015) of this two-part study presents in situ measurements of such conditions sampled by Airbus in three tropical regions, commonly near 11 km and −43 °C, and concludes that the measured ice particle size distributions are broadly consistent with past literature with profiling radar measurements of Ze and mean Doppler velocity obtained within monsoonal deep convection in one of the regions sampled. In all three regions, the Airbus measurements generally indicate variable IWC that often exceeds 2 g m-3 with relatively uniform mass median area-equivalent diameter (MMDeq) of 200–300 μm. Here we use a parcel model with size-resolved microphysics to investigate microphysical pathways that could lead to such conditions. Our simulations indicate that homogeneous freezing of water drops produces a much smaller ice MMDeq than observed, and occurs only in the absence of hydrometeor gravitational collection for the conditions considered. Development of a mass mode of ice aloft that overlaps with the measurements requires a substantial source of small ice particles at temperatures of about −10 °C or warmer, which subsequently grow from water vapor. One conceivable source in our simulation framework is Hallett–Mossop ice production; another is abundant concentrations of heterogeneous ice freezing nuclei acting together with copious shattering of water drops upon freezing. Regardless of the production mechanism, the dominant mass modal diameter of vapor-grown ice is reduced as the ice-multiplication source strength increases and as competition for water vapor increases. Both mass and modal diameter are reduced by entrainment and by increasing aerosol concentrations. Weaker updrafts lead to greater mass and larger modal diameters of vapor-grown ice, the opposite of expectations regarding lofting of larger ice particles in stronger updrafts. While stronger updrafts do loft more dense ice particles produced primarily by raindrop freezing, we find that weaker updrafts allow the warm rain process to reduce competition for diffusional growth of the less dense ice expected to persist in convective outflow.


2013 ◽  
Vol 24 (4) ◽  
pp. e260-e268 ◽  
Author(s):  
M. S. Kristiansen ◽  
A. Uhrbrand ◽  
M. Hansen ◽  
J. M. Shiguetomi-Medina ◽  
K. Vissing ◽  
...  

2009 ◽  
Vol 9 (22) ◽  
pp. 8889-8901 ◽  
Author(s):  
A. W. Merkel ◽  
D. R. Marsh ◽  
A. Gettelman ◽  
E. J. Jensen

Abstract. The distribution of ice layers in the polar summer mesosphere (called polar mesospheric clouds or PMCs) is sensitive to background atmospheric conditions and therefore affected by global-scale dynamics. To investigate this coupling it is necessary to simulate the global distribution of PMCs within a 3-dimensional (3-D) model that couples large-scale dynamics with cloud microphysics. However, modeling PMC microphysics within 3-D global chemistry climate models (GCCM) is a challenge due to the high computational cost associated with particle following (Lagrangian) or sectional microphysical calculations. By characterizing the relationship between the PMC effective radius, ice water content (iwc), and local temperature (T) from an ensemble of simulations from the sectional microphysical model, the Community Aerosol and Radiation Model for Atmospheres (CARMA), we determined that these variables can be described by a robust empirical formula. The characterized relationship allows an estimate of an altitude distribution of PMC effective radius in terms of local temperature and iwc. For our purposes we use this formula to predict an effective radius as part of a bulk parameterization of PMC microphysics in a 3-D GCCM to simulate growth, sublimation and sedimentation of ice particles without keeping track of the time history of each ice particle size or particle size bin. This allows cost effective decadal scale PMC simulations in a 3-D GCCM to be performed. This approach produces realistic PMC simulations including estimates of the optical properties of PMCs. We validate the relationship with PMC data from the Solar Occultation for Ice Experiment (SOFIE).


2021 ◽  
Author(s):  
Sandra Vázquez-Martín ◽  
Thomas Kuhn ◽  
Salomon Eliasson

Abstract. Meteorological forecast and climate models require good knowledge of the microphysical properties of hydrometeors and the atmospheric snow and ice crystals in clouds. For instance, their size, cross-sectional area, shape, mass, and fall speed. Especially shape is an important parameter in that it strongly affects the scattering properties of ice particles, and consequently their response to remote sensing techniques. The fall speed and mass of ice particles are other important parameters both for numerical forecast models and for the representation of snow and ice clouds in climate models. In the case of fall speed, it is responsible for the rate of removal of ice from these models. The particle mass is a key quantity that connects the cloud microphysical properties to radiative properties. Using an empirical relationship between the dimensionless Reynolds and Best numbers, fall speed and mass can be derived from each other if particle size and cross-sectional area are also known. In this work, ground-based in-situ measurements of snow particle microphysical properties are used to analyse mass as a function of shape and the other properties particle size, cross-sectional area, and fall speed. The measurements for this study were done in Kiruna, Sweden during snowfall seasons of 2014 to 2019 and using the ground-based in-situ instrument Dual Ice Crystal Imager (D-ICI), which takes high-resolution side- and top-view images of natural hydrometeors. From these images, particle size (maximum dimension), cross-sectional area, and fall speed of individual particles are determined. The particles are shape classified according to the scheme presented in our previous work, in which particles sort into 15 different shape groups depending on their shape and morphology. Particle masses of individual ice particles are estimated from measured particle size, cross-sectional area, and fall speed. The selected dataset covers sizes from about 0.1 mm to 3.2 mm, fall speeds from 0.1 m s−1 to 1.6 m s−1, and masses from close to 0.2 μg to 320 μg. In our previous work, the fall speed relationships between particle size and cross-sectional area were studied. In this work, the same dataset is used to determine the particle mass, and consequently, the mass relationships between particle size, cross-sectional area, and fall speed are studied for these 15 shape groups. Furthermore, the mass relationships presented in this study are compared with the previous studies.


2014 ◽  
Vol 7 (9) ◽  
pp. 3007-3022 ◽  
Author(s):  
S. J. Abel ◽  
R. J. Cotton ◽  
P. A. Barrett ◽  
A. K. Vance

Abstract. This paper presents a comparison of ice water content (qi) data from a variety of measurement techniques on the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft. Data are presented from a range of cloud types measured during the PIKNMIX field experiment that include mixed-phase stratocumulus, cumulus congestus and cirrus clouds. These measurements cover a broad range of conditions in which atmospheric ice particles are found in nature, such as the low-ice-water-content environments typically found in midlatitude cirrus and the environments with much higher ice water content often observed in cold convective clouds. The techniques include bulk measurements from (i) a Nevzorov hot-wire probe, (ii) the difference between the measured total water content (condensed plus vapour) and the water vapour content of the atmosphere and (iii) a counterflow virtual impactor (CVI) (only for cirrus measurements). We also estimate the qi from integration of the measured particle size distribution (PSD) with assumptions on how the density of ice particles varies as a function of size. The results show that the only bulk ice water content technique capable of measuring high qi values (several g m−3) was the method of total water content minus water vapour. For low ice water contents we develop a new parametrisation of the Nevzorov baseline drift that enables the probe to be sensitive to qi ± 0.002 g m−3. In cirrus clouds the agreement between the Nevzorov and other bulk measurements was typically better than a factor of 2 for the CVI (qi > 0.008 g m−3) and the method of total water content minus water vapour (qi > 0.02 g m−3). Good agreement with the bulk measurements for all cases could be obtained with the estimate from the PSD provided that appropriate a priori assumptions on the mass–dimension relationship were made. This is problematic in the convective clouds sampled because pristine ice particles, heavily rimed particles and supercooled liquid drops were all present. In a cirrus case, we show that using a temperature-dependent mass–dimension relation was required to match the bulk measurement of qi.


2010 ◽  
Vol 27 (5) ◽  
pp. 793-810 ◽  
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
E. J. O’Connor ◽  
T. S. L’Ecuyer

Abstract In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.


2021 ◽  
Vol 21 (10) ◽  
pp. 7545-7565
Author(s):  
Sandra Vázquez-Martín ◽  
Thomas Kuhn ◽  
Salomon Eliasson

Abstract. Improved snowfall predictions require accurate knowledge of the properties of ice crystals and snow particles, such as their size, cross-sectional area, shape, and fall speed. The fall speed of ice particles is a critical parameter for the representation of ice clouds and snow in atmospheric numerical models, as it determines the rate of removal of ice from the modelled clouds. Fall speed is also required for snowfall predictions alongside other properties such as ice particle size, cross-sectional area, and shape. For example, shape is important as it strongly influences the scattering properties of these ice particles and thus their response to remote sensing techniques. This work analyzes fall speed as a function of particle size (maximum dimension), cross-sectional area, and shape using ground-based in situ measurements. The measurements for this study were done in Kiruna, Sweden, during the snowfall seasons of 2014 to 2019, using the ground-based in situ instrument Dual Ice Crystal Imager (D-ICI). The resulting data consist of high-resolution images of falling hydrometeors from two viewing geometries that are used to determine particle size (maximum dimension), cross-sectional area, area ratio, orientation, and the fall speed of individual particles. The selected dataset covers sizes from about 0.06 to 3.2 mm and fall speeds from 0.06 to 1.6 m s−1. Relationships between particle size, cross-sectional area, and fall speed are studied for different shapes. The data show in general low correlations to fitted fall speed relationships due to large spread observed in fall speed. After binning the data according to size or cross-sectional area, correlations improve, and we can report reliable parameterizations of fall speed vs. particle size or cross-sectional area for part of the shapes. For most of these shapes, the fall speed is better correlated with cross-sectional area than with particle size. The effects of orientation and area ratio on the fall speed are also studied, and measurements show that vertically oriented particles fall faster on average. However, most particles for which orientation can be defined fall horizontally.


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