Improvement in Determination of Ice Water Content from Two-Dimensional Particle Imagery. Part II: Applications to Collected Data

2006 ◽  
Vol 45 (9) ◽  
pp. 1291-1303 ◽  
Author(s):  
R. Paul Lawson ◽  
Brad A. Baker
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Particle Mass ◽  
Two Dimensional ◽  
Projected Area ◽  
Ice Water Content ◽  
Rms Error ◽  
Particle Size And Shape ◽  
Ice Water

Abstract In Part I of this two-part series, a new relationship for ice particle mass M was derived based on an expanded dataset of photographed ice particles and melted drops. The new relationship resulted in a reduction of nearly 50% in the rms error in M. In this paper, new relationships for computing particle mass and ice water content from 2D particle imagery are compared with other relationships previously used in the literature. Comparison of the old and new relationships, when applied to data collected in natural clouds, shows that results using the old relationships differ from the new relationships by up to a factor of 3, depending on particle size and shape. One of the new relationships can be applied to existing (archived) datasets of two-dimensional images, provided that the number of occulted pixels in each image (i.e., projected area) is available.

Improvement in Determination of Ice Water Content from Two-Dimensional Particle Imagery. Part I: Image-to-Mass Relationships

2006 ◽  
Vol 45 (9) ◽  
pp. 1282-1290 ◽  
Author(s):  
Brad Baker ◽  
R. Paul Lawson
Keyword(s):  
Water Content ◽  
Linear Regression Analysis ◽  
Crystal Habit ◽  
Two Dimensional ◽  
Average Mass ◽  
Length Relationship ◽  
Ice Water Content ◽  
Rms Error ◽  
Ice Water

Abstract Ice water content in natural clouds is an important but difficult quantity to measure. The goal of a number of past studies was to find average relationships between the masses and lengths of ice particles to determine ice water content from in situ data, such as those routinely recorded with two-dimensional imaging probes. The general approach in these past studies was to measure maximum length L and mass M of a dataset of ice crystals collected at a ground site. Linear regression analysis was performed on the logarithms of the data to estimate an average mass-to-length relationship of the form M = αLβ. Relationships were determined for subsets of the dataset based on crystal habit (shape) as well as for the full dataset. In this study, alternative relationships for determining mass using the additional parameters of width W, area A, and perimeter P are explored. A 50% reduction in rms error in the determination of mass relative to using L alone is achieved using a single parameter that is a combination of L, W, A, and P. The new parameter is designed to take into account the shape of the ice particle without the need to classify the crystals first. An interesting result is that, when applied to the test dataset, the same reduction in rms error is also shown to be achievable using A alone. Using A alone facilitates the reanalysis and improvement of the determination of ice water content from large existing datasets of two-dimensional images, because A is simply the number of occulted pixels in the digital images. Possible sources of error in this study are investigated, as is the usefulness of first segregating the particles into crystal habits.

Measurement of Total Water with a Tunable Diode Laser Hygrometer: Inlet Analysis, Calibration Procedure, and Ice Water Content Determination

2007 ◽  
Vol 24 (3) ◽  
pp. 463-475 ◽  
Author(s):  
Sean M. Davis ◽  
A. Gannet Hallar ◽  
Linnea M. Avallone ◽  
William Engblom
Keyword(s):  
Particle Size ◽  
Water Vapor ◽  
Water Content ◽  
Diode Laser ◽  
Tunable Diode Laser ◽  
Calibration Data ◽  
Total Water ◽  
Wide Range ◽  
Ice Water Content ◽  
Ice Water

Abstract The University of Colorado closed-path tunable diode laser hygrometer (CLH), a new instrument for the in situ measurement of enhanced total water (eTW, the sum of water vapor and condensed water enhanced by a subisokinetic inlet), has recently been flown aboard the NASA DC-8 and WB-57F aircrafts. The CLH has the sensitivity necessary to quantify the ice water content (IWC) of extremely thin subvisual cirrus clouds (∼0.1 mg m−3), while still providing measurements over a large range of conditions typical of upper-tropospheric cirrus (up to 1 g m−3). A key feature of the CLH is its subisokinetic inlet system, which is described in detail in this paper. The enhancement and evaporation of ice particles that results from the heated subisokinetic inlet is described both analytically and based on computational fluid dynamical simulations of the flow around the aircraft. Laboratory mixtures of water vapor with an accuracy of 2%–10% (2σ) were used to calibrate the CLH over a wide range of water vapor mixing ratios (∼50–50 000 ppm) and pressures (∼100–1000 mb). The water vapor retrieval algorithm, which is based on the CLH instrument properties as well as on the spectroscopic properties of the water absorption line, accurately fits the calibration data to within the uncertainty of the calibration mixtures and instrument signal-to-noise ratio. A method for calculating cirrus IWC from the CLH enhanced total water measurement is presented. In this method, the particle enhancement factor is determined from an independent particle size distribution measurement and the size-dependent CLH inlet efficiency. It is shown that despite the potentially large uncertainty in particle size measurements, the error introduced by this method adds ∼5% error to the IWC calculation. IWC accuracy ranges from 20% at the largest IWC to 50% at small IWC (<5 mg m−3).

scholarly journals On the relationship of polar mesospheric cloud ice water content, particle radius and mesospheric temperature and its use in multi-dimensional models

2009 ◽  
Vol 9 (22) ◽  
pp. 8889-8901 ◽  
Author(s):  
A. W. Merkel ◽  
D. R. Marsh ◽  
A. Gettelman ◽  
E. J. Jensen
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Computational Cost ◽  
Cloud Microphysics ◽  
Effective Radius ◽  
Local Temperature ◽  
Decadal Scale ◽  
Ice Water Content ◽  
Ice Water ◽  
The Relationship

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).

Independent Evaluation of the Ability of Spaceborne Radar and Lidar to Retrieve the Microphysical and Radiative Properties of Ice Clouds

2006 ◽  
Vol 23 (2) ◽  
pp. 211-227 ◽  
Author(s):  
Robin J. Hogan ◽  
Malcolm E. Brooks ◽  
Anthony J. Illingworth ◽  
David P. Donovan ◽  
Claire Tinel ◽  
...  
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Multiple Scattering ◽  
Optical Depth ◽  
Radiative Properties ◽  
Molecular Scattering ◽  
Retrieval Algorithms ◽  
Ice Water Content ◽  
Ice Water ◽  
Better Than

Abstract The combination of radar and lidar in space offers the unique potential to retrieve vertical profiles of ice water content and particle size globally, and two algorithms developed recently claim to have overcome the principal difficulty with this approach—that of correcting the lidar signal for extinction. In this paper “blind tests” of these algorithms are carried out, using realistic 94-GHz radar and 355-nm lidar backscatter profiles simulated from aircraft-measured size spectra, and including the effects of molecular scattering, multiple scattering, and instrument noise. Radiation calculations are performed on the true and retrieved microphysical profiles to estimate the accuracy with which radiative flux profiles could be inferred remotely. It is found that the visible extinction profile can be retrieved independent of assumptions on the nature of the size distribution, the habit of the particles, the mean extinction-to-backscatter ratio, or errors in instrument calibration. Local errors in retrieved extinction can occur in proportion to local fluctuations in the extinction-to-backscatter ratio, but down to 400 m above the height of the lowest lidar return, optical depth is typically retrieved to better than 0.2. Retrieval uncertainties are greater at the far end of the profile, and errors in total optical depth can exceed 1, which changes the shortwave radiative effect of the cloud by around 20%. Longwave fluxes are much less sensitive to errors in total optical depth, and may generally be calculated to better than 2 W m−2 throughout the profile. It is important for retrieval algorithms to account for the effects of lidar multiple scattering, because if this is neglected, then optical depth is underestimated by approximately 35%, resulting in cloud radiative effects being underestimated by around 30% in the shortwave and 15% in the longwave. Unlike the extinction coefficient, the inferred ice water content and particle size can vary by 30%, depending on the assumed mass–size relationship (a problem common to all remote retrieval algorithms). However, radiative fluxes are almost completely determined by the extinction profile, and if this is correct, then errors in these other parameters have only a small effect in the shortwave (around 6%, compared to that of clear sky) and a negligible effect in the longwave.

scholarly journals Ice Microphysical Properties near the Tops of Deep Convective Cores Implied by the GPM Dual-Frequency Radar Observations

2019 ◽  
Vol 76 (9) ◽  
pp. 2899-2917 ◽  
Author(s):  
Xiang Ni ◽  
Chuntao Liu ◽  
Edward Zipser
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Deep Convection ◽  
Radar Reflectivity ◽  
Lookup Table ◽  
Dual Frequency ◽  
Ka Band ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
Ice Water

Abstract Using three years of observations from the Dual-Frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) Core Observatory, properties of the cores of deep convection are examined. First, deep convective systems are selected, defined as GPM precipitation features with maximum 20-dBZ echo-top heights above 10 km. The cores of deep convection are described by the profiles of Ku- and Ka-band radar reflectivity at the location of the highest echo top in each deep convective system. Then the dual-frequency ratio (DFR) profile is derived by subtracting Ka-band from Ku-band radar reflectivity. It is found that values of DFR are larger over land than over ocean in general near the top of the convection, which is consistent with larger ice particles in stronger updrafts in continental convection. The magnitude of DFR at 12 km is positively correlated with the convection intensity indicated by 20- and 30-dBZ echo tops. The microphysical properties including volume-weighted mean diameter, ice water content, and total ice particle number concentration are derived using a simple lookup table approach. Under the same particle size distribution assumption, the cores of deep convection over land have larger ice particle size, higher ice water content, and lower particle concentration than those over ocean at levels above 10 km, but with some distinct regional variations.

scholarly journals Understanding effective diameter and its application to terrestrial radiation in ice clouds

2011 ◽  
Vol 11 (7) ◽  
pp. 3417-3429 ◽  
Author(s):  
D. L. Mitchell ◽  
R. P. Lawson ◽  
B. Baker
Keyword(s):  
Water Content ◽  
Climate Modeling ◽  
Effective Diameter ◽  
Projected Area ◽  
Cloud Particle ◽  
Ice Clouds ◽  
Wave Resonance ◽  
Cloud Water Content ◽  
Ice Water Content ◽  
Ice Water

Abstract. The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, De, and their cloud water content (CWC), henceforth referred to as the De-CWC assumption. This study challenges this assumption, showing that while the De-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De

scholarly journals Understanding effective diameter and its application to terrestrial radiation in ice clouds

2010 ◽  
Vol 10 (12) ◽  
pp. 29405-29447
Author(s):  
D. L. Mitchell ◽  
R. P. Lawson ◽  
B. Baker
Keyword(s):  
Water Content ◽  
Climate Modeling ◽  
Effective Diameter ◽  
Projected Area ◽  
Cloud Particle ◽  
Ice Clouds ◽  
Wave Resonance ◽  
Cloud Water Content ◽  
Ice Water Content ◽  
Ice Water

Abstract. The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, De, and their cloud water content (CWC), henceforth referred to as the De–CWC assumption. This study challenges this assumption, showing that while the De–CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De

scholarly journals The Dimensional Characteristics of Ice Crystal Aggregates from Fractal Geometry

2010 ◽  
Vol 67 (5) ◽  
pp. 1605-1616 ◽  
Author(s):  
C. G. Schmitt ◽  
A. J. Heymsfield
Keyword(s):  
Fractal Dimension ◽  
Water Content ◽  
Fractal Geometry ◽  
Ice Crystal ◽  
Temperature Dependent ◽  
Projected Area ◽  
Cloud Particle ◽  
Self Consistent ◽  
Ice Water Content ◽  
Ice Water

Abstract Ice crystal aggregates imaged by aircraft particle imaging probes often appear to be fractal in nature. As such, their dimensional properties, mass, and projected area can be related using fractal geometry. In cloud microphysics, power-law mass (m)– and area (A)–dimensional (D) relationships (e.g., m = aDb) incorporate different manifestations of the fractal dimension as the exponent (b). In this study a self-consistent technique is derived for determining the mass and projected area properties of ice particles from fractal geometry. A computer program was developed to simulate the crystal aggregation process. The fractal dimension of the simulated aggregates was estimated using the box counting method in three dimensions as well as for two-dimensional projected images of the aggregates. The two- and three-dimensional fractal dimension values were found to be simply related. This relationship enabled the development of mass–dimensional relationships analytically from cloud particle images. This technique was applied to data collected during two field projects. The exponent in the mass–dimensional relationship, the fractal dimension, was found to be between 2.0 and 2.3 with a dependence on temperature noted for both datasets. The coefficient a in the mass–dimensional relationships was derived in a self-consistent manner. Temperature-dependent mass–dimensional relationships have been developed. Cloud ice water content estimated using the temperature-dependent relationship and particle size distributions agreed well with directly measured ice water content values. The results are appropriate for characterizing cloud particle properties in clouds with high concentrations of ice crystal aggregates.

scholarly journals Albedo-Ice Regression method for determining ice water content of polar mesospheric clouds using ultraviolet observations from space

2019 ◽  
Vol 12 (3) ◽  
pp. 1755-1766 ◽  
Author(s):  
Gary E. Thomas ◽  
Jerry Lumpe ◽  
Charles Bardeen ◽  
Cora E. Randall
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Average Error ◽  
Polar Mesospheric Clouds ◽  
Mode Of Operation ◽  
Ice Water Content ◽  
Mesospheric Clouds ◽  
Using Data ◽  
Ultraviolet Observations ◽  
Ice Water

Abstract. High spatial resolution images of polar mesospheric clouds (PMCs) from a camera array on board the Aeronomy of Ice in the Mesosphere (AIM) satellite have been obtained since 2007. The Cloud Imaging and Particle Size Experiment (CIPS) detects scattered ultraviolet (UV) radiance at a variety of scattering angles, allowing the scattering phase function to be measured for every image pixel. With well-established scattering theory, the mean particle size and ice water content (IWC) are derived. In the nominal mode of operation, approximately seven scattering angles are measured per cloud pixel. However, because of a change in the orbital geometry in 2016, a new mode of operation was implemented such that one scattering angle, or at most two, per pixel are now available. Thus particle size and IWC can no longer be derived from the standard CIPS algorithm. The Albedo-Ice Regression (AIR) method was devised to overcome this obstacle. Using data from both a microphysical model and from CIPS in its normal mode, we show that the AIR method provides sufficiently accurate average IWC so that PMC IWC can be retrieved from CIPS data into the future, even when albedo is not measured at multiple scattering angles. We also show from the model that 265 nm UV scattering is sensitive only to ice particle sizes greater than about 20–25 nm in (effective) radius and that the operational CIPS algorithm has an average error in retrieving IWC of -13±17 %.

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