scholarly journals Influence of convection and aerosol pollution on ice cloud particle effective radius

2010 ◽  
Vol 10 (10) ◽  
pp. 23091-23108 ◽  
Author(s):  
J. H. Jiang ◽  
H. Su ◽  
C. Zhai ◽  
S. T. Massie ◽  
M. R. Schoeberl ◽  
...  
Keyword(s):  
Climate Models ◽  
Analytical Formula ◽  
Effective Radius ◽  
Cloud Particle ◽  
Ice Cloud ◽  
Geographical Regions ◽  
Aerosol Pollution ◽  
Ice Water Content ◽  
Aerosol Effects ◽  
Ice Water

Abstract. Satellite observations show that ice cloud effective radius (re) increases with ice water content (IWC) but decreases with aerosol optical thickness (AOT). Using least-squares fitting to the observed data, we obtain an analytical formula to describe the variations of re with IWC and AOT for several regions with distinct characteristics of re-IWC-AOT relationships. As IWC directly relates to convective strength and AOT represents aerosol loading, our empirical formula provides a means to quantify the relative roles of dynamics and aerosols in controlling re in different geographical regions, and to establish a framework for parameterization of aerosol effects on re in climate models.

scholarly journals Influence of convection and aerosol pollution on ice cloud particle effective radius

2011 ◽  
Vol 11 (2) ◽  
pp. 457-463 ◽  
Author(s):  
J. H. Jiang ◽  
H. Su ◽  
C. Zhai ◽  
S. T. Massie ◽  
M. R. Schoeberl ◽  
...  
Keyword(s):  
Climate Models ◽  
Analytical Formula ◽  
Effective Radius ◽  
Cloud Particle ◽  
Ice Cloud ◽  
Geographical Regions ◽  
Aerosol Pollution ◽  
Ice Water Content ◽  
Aerosol Effects ◽  
Ice Water

Abstract. Satellite observations show that ice cloud effective radius (re) increases with ice water content (IWC) but decreases with aerosol optical thickness (AOT). Using least-squares fitting to the observed data, we obtain an analytical formula to describe the variations of re with IWC and AOT for several regions with distinct characteristics of re-IWC-AOT relationships. As IWC directly relates to convective strength and AOT represents aerosol loading, our empirical formula provides a means to quantify the relative roles of dynamics and aerosols in controlling re in different geographical regions, and to establish a framework for parameterization of aerosol effects on re in climate models.

scholarly journals The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

2011 ◽  
Vol 11 (16) ◽  
pp. 8363-8384 ◽  
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
P. T. May ◽  
J. Haynes ◽  
C. Jakob ◽  
...  
Keyword(s):  
Large Scale ◽  
Effective Radius ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Mean Differences ◽  
Ice Water ◽  
Lidar Observations

Abstract. The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

Simulation of remote sensing of clouds and humidity from space using a combined platform of radar and multi-frequency microwave radiometers

2020 ◽  
Author(s):  
Jonathan Jiang ◽  
Hui Su ◽  
Qing Yue ◽  
Pekka Kangaslahti
Keyword(s):  
Remote Sensing ◽  
Effective Diameter ◽  
Cloud Particle ◽  
Ice Cloud ◽  
Cloud Properties ◽  
Thermodynamic Conditions ◽  
Ice Water Content ◽  
Microwave Radiometers ◽  
Cloud Ice ◽  
Ice Water

<p>We present a simulated simultaneous retrieval of mass mean cloud ice particle effective diameter, ice water content, water vapor, and temperature profiles using a combination of a 94-GHz cloud radar and multi-frequency (118, 183, 240, 310, 380, 664, and 850 GHz) millimeter- and submillimeter-wave radiometers from a space platform. The retrieval capabilities and uncertainties of the combined radar and microwave radiometers are quantified. We show that this combined active and passive remote sensing approach with SmallSat technologies addresses a gap in the current state-of-the-art remote sensing measurements of ice cloud properties, especially deriving vertical profiles of ice cloud particle sizes in the atmosphere together with the ambient thermodynamic conditions. Therefore, this new approach can serve as a plausible candidate for future missions that target cloud and precipitation processes to improve weather forecasts and climate predictions.  </p>

scholarly journals A Comparison among Four Different Retrieval Methods for Ice-Cloud Properties Using Data from CloudSat, CALIPSO, and MODIS

2011 ◽  
Vol 50 (9) ◽  
pp. 1952-1969 ◽  
Author(s):  
Thorwald H. M. Stein ◽  
Julien Delanoë ◽  
Robin J. Hogan
Keyword(s):  
Water Content ◽  
Effective Radius ◽  
Retrieval Algorithm ◽  
Empirical Formulas ◽  
Mean Values ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
The Mean ◽  
Ice Water

AbstractThe A-Train constellation of satellites provides a new capability to measure vertical cloud profiles that leads to more detailed information on ice-cloud microphysical properties than has been possible up to now. A variational radar–lidar ice-cloud retrieval algorithm (VarCloud) takes advantage of the complementary nature of the CloudSat radar and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar to provide a seamless retrieval of ice water content, effective radius, and extinction coefficient from the thinnest cirrus (seen only by the lidar) to the thickest ice cloud (penetrated only by the radar). In this paper, several versions of the VarCloud retrieval are compared with the CloudSat standard ice-only retrieval of ice water content, two empirical formulas that derive ice water content from radar reflectivity and temperature, and retrievals of vertically integrated properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) radiometer. The retrieved variables typically agree to within a factor of 2, on average, and most of the differences can be explained by the different microphysical assumptions. For example, the ice water content comparison illustrates the sensitivity of the retrievals to assumed ice particle shape. If ice particles are modeled as oblate spheroids rather than spheres for radar scattering then the retrieved ice water content is reduced by on average 50% in clouds with a reflectivity factor larger than 0 dBZ. VarCloud retrieves optical depths that are on average a factor-of-2 lower than those from MODIS, which can be explained by the different assumptions on particle mass and area; if VarCloud mimics the MODIS assumptions then better agreement is found in effective radius and optical depth is overestimated. MODIS predicts the mean vertically integrated ice water content to be around a factor-of-3 lower than that from VarCloud for the same retrievals, however, because the MODIS algorithm assumes that its retrieved effective radius (which is mostly representative of cloud top) is constant throughout the depth of the cloud. These comparisons highlight the need to refine microphysical assumptions in all retrieval algorithms and also for future studies to compare not only the mean values but also the full probability density function.

The impact of ice cloud particle microphysics on the uncertainty of ice water content retrievals

2011 ◽  
Vol 112 (2) ◽  
pp. 189-196 ◽  
Author(s):  
Wenbo Sun ◽  
Yongxiang Hu ◽  
Bing Lin ◽  
Zhaoyan Liu ◽  
Gorden Videen
Keyword(s):  
Water Content ◽  
Cloud Particle ◽  
Ice Cloud ◽  
Ice Water Content ◽  
Ice Water ◽  
The Impact

Refinements to Ice Particle Mass Dimensional and Terminal Velocity Relationships for Ice Clouds. Part II: Evaluation and Parameterizations of Ensemble Ice Particle Sedimentation Velocities

2007 ◽  
Vol 64 (4) ◽  
pp. 1068-1088 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Gerd-Jan van Zadelhoff ◽  
David P. Donovan ◽  
Frederic Fabry ◽  
Robin J. Hogan ◽  
...  
Keyword(s):  
Climate Models ◽  
Doppler Radar ◽  
Terminal Velocity ◽  
Fall Velocity ◽  
Particle Sedimentation ◽  
Cloud Properties ◽  
Wide Range ◽  
Single Moment ◽  
Ice Water Content ◽  
Ice Water

Abstract This two-part study addresses the development of reliable estimates of the mass and fall speed of single ice particles and ensembles. Part I of the study reports temperature-dependent coefficients for the mass-dimensional relationship, m = aDb, where D is particle maximum dimension. The fall velocity relationship, Vt = ADB, is developed from observations in synoptic and low-latitude, convectively generated, ice cloud layers, sampled over a wide range of temperatures using an assumed range for the exponent b. Values for a, A, and B were found that were consistent with the measured particle size distributions (PSD) and the ice water content (IWC). To refine the estimates of coefficients a and b to fit both lower and higher moments of the PSD and the associated values for A and B, Part II uses the PSD from Part I plus coincident, vertically pointing Doppler radar returns. The observations and derived coefficients are used to evaluate earlier, single-moment, bulk ice microphysical parameterization schemes as well as to develop improved, statistically based, microphysical relationships. They may be used in cloud and climate models, and to retrieve cloud properties from ground-based Doppler radar and spaceborne, conventional radar returns.

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 ◽  
...  
Keyword(s):  
Water Content ◽  
Effective Radius ◽  
Cross Sectional Area ◽  
Sectional Area ◽  
Small Particles ◽  
Particle Volume ◽  
Cross Sectional ◽  
Ice Particles ◽  
Ice Water Content ◽  
Ice Water

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.

scholarly journals An Inverse Problem Approach for the Retrieval of Ice Particle Mass from In Situ Measurements

2017 ◽  
Vol 34 (11) ◽  
pp. 2457-2473 ◽  
Author(s):  
Pierre Coutris ◽  
Delphine Leroy ◽  
Emmanuel Fontaine ◽  
Alfons Schwarzenboeck
Keyword(s):  
Inverse Problem ◽  
Particle Size ◽  
Power Law ◽  
In Situ Measurements ◽  
Ice Cloud ◽  
Size Dependent ◽  
Microphysical Properties ◽  
Ice Water Content ◽  
Ice Water

AbstractMass–dimensional relationships have been published for decades to characterize the microphysical properties of ice cloud particles. Classical retrieval methods employ a simplifying assumption that restricts the form of the mass–dimensional relationship to a power law, an assumption that was proved inaccurate in recent studies. In this paper, a nonstandard approach that leverages optimal use of in situ measurements to remove the power-law constraint is presented. A model formulated as a linear system of equations relating ice particle mass to particle size distribution (PSD) and ice water content (IWC) is established, and the mass retrieval process consists of solving the inverse problem with numerical optimization algorithms. First, the method is applied to a synthetic crystal dataset in order to validate the selected algorithms and to tune the regularization strategy. Subsequently, the method is applied to in situ measurements collected during the High Altitude Ice Crystal–High Ice Water Content field campaigns. Preliminary results confirm the method is efficient at retrieving size-dependent masses from real data despite a significant amount of noise: the IWC values calculated from the retrieved masses are in good agreement with reference IWC measurements (errors on the order of 10%–15%). The possibility to retrieve ice particle size–dependent masses combined with the flexibility left for sorting datasets as a function of parameters such as cloud temperature, cloud type, or convective index makes this approach well suited for studying ice cloud microphysical properties.

Analytical Solutions to the Stochastic Kinetic Equation for Liquid and Ice Particle Size Spectra. Part II: Large-Size Fraction in Precipitating Clouds

2008 ◽  
Vol 65 (7) ◽  
pp. 2044-2063 ◽  
Author(s):  
Vitaly I. Khvorostyanov ◽  
Judith A. Curry
Keyword(s):  
Kinetic Equation ◽  
Water Content ◽  
Analytical Solutions ◽  
Algebraic Function ◽  
Size Fraction ◽  
Cloud Particle ◽  
Size Spectra ◽  
Large Size ◽  
Ice Water Content ◽  
Ice Water

Abstract The stochastic kinetic equation is solved analytically for precipitating particles that can be identified as rain, snow, and graupel. The general solution for the size spectra of the large-size particles is represented by the product of an exponential term and a term that is an algebraic function of radius. The slope of the exponent consists of the Marshall–Palmer slope and an additional integral that is a function of the radius. Both the integral and algebraic terms depend on the condensation and accretion rates, vertical velocity, turbulence coefficient, terminal velocity of the particles, and the vertical gradient of the liquid (ice) water content. At sufficiently large radii, the radius dependence of the algebraic term is a power law, and the spectra have the form of gamma distributions. Simple analytical expressions are derived for the slopes and indices of the size distributions. These solutions provide explanations of the observed dependencies of the cloud particle spectra in different phases and size regimes on temperature, height, turbulence, vertical velocities, liquid or ice water content, and other cloud properties. These analytical solutions and expressions for the slopes and shape parameters can be used for parameterization of the spectra of precipitating particles and related quantities (e.g., optical properties, radar reflectivities) in bulk cloud microphysical parameterizations and in remote sensing techniques.

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