Comments on “Effective Radius of Ice Cloud Particle Populations Derived from Aircraft Probes”

2007 ◽  
Vol 24 (8) ◽  
pp. 1495-1503 ◽  
Author(s):  
Timothy J. Garrett
2010 ◽  
Vol 10 (10) ◽  
pp. 23091-23108 ◽  
Author(s):  
J. H. Jiang ◽  
H. Su ◽  
C. Zhai ◽  
S. T. Massie ◽  
M. R. Schoeberl ◽  
...  

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.


2011 ◽  
Vol 11 (2) ◽  
pp. 457-463 ◽  
Author(s):  
J. H. Jiang ◽  
H. Su ◽  
C. Zhai ◽  
S. T. Massie ◽  
M. R. Schoeberl ◽  
...  

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.


2006 ◽  
Vol 23 (3) ◽  
pp. 361-380 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Carl Schmitt ◽  
Aaron Bansemer ◽  
Gerd-Jan van Zadelhoff ◽  
Matthew J. McGill ◽  
...  

Abstract The effective radius (re) is a crucial variable in representing the radiative properties of cloud layers in general circulation models. This parameter is proportional to the condensed water content (CWC) divided by the extinction (σ). For ice cloud layers, parameterizations for re have been developed from aircraft in situ measurements 1) indirectly, using data obtained from particle spectrometer probes and assumptions or observations about particle shape and mass to get the ice water content (IWC) and area to get σ, and recently 2) from probes that derive IWC and σ more directly, referred to as the direct approach, even though the extinction is not measured directly. This study compares [IWC/σ] derived from the two methods using datasets acquired from comparable instruments on two aircraft, one sampling clouds at midlevels and the other at upper levels during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) field program in Florida in 2002. A penetration by one of the aircraft into a cold midlatitude orographic wave cloud composed of small particles is further evaluated. The σ and IWC derived by each method are compared and evaluated in different ways for each aircraft dataset. Direct measurements of σ exceed those derived indirectly by a factor of 2–2.5. The IWC probes, relying on ice sublimation, appear to measure accurately except when the IWC is high or the particles too large to sublimate completely during the short transit time through the probe. The IWC estimated from the particle probes are accurate when direct measurements are available to provide constraints and give useful information in high IWC/large particle situations. Because of the discrepancy in σ estimates between the direct and indirect approaches, there is a factor of 2–3 difference in [IWC/σ] between them. Although there are significant uncertainties involved in its use, comparisons with several independent data sources suggest that the indirect method is the more accurate of the two approaches. However, experiments are needed to resolve the source of the discrepancy in σ.


2019 ◽  
Vol 12 (8) ◽  
pp. 4361-4377 ◽  
Author(s):  
Alexandre Guillaume ◽  
Brian H. Kahn ◽  
Eric J. Fetzer ◽  
Qing Yue ◽  
Gerald J. Manipon ◽  
...  

Abstract. A method is described to classify cloud mixtures of cloud top types, termed cloud scenes, using cloud type classification derived from the CloudSat radar (2B-CLDCLASS). The scale dependence of the cloud scenes is quantified. For spatial scales at 45 km (15 km), only 18 (10) out of 256 possible cloud scenes account for 90 % of all observations and contain one, two, or three cloud types. The number of possible cloud scenes is shown to depend on spatial scale with a maximum number of 210 out of 256 possible scenes at a scale of 105 km and fewer cloud scenes at smaller and larger scales. The cloud scenes are used to assess the characteristics of spatially collocated Atmospheric Infrared Sounder (AIRS) thermodynamic-phase and ice cloud property retrievals within scenes of varying cloud type complexity. The likelihood of ice and liquid-phase detection strongly depends on the CloudSat-identified cloud scene type collocated with the AIRS footprint. Cloud scenes primarily consisting of cirrus, nimbostratus, altostratus, and deep convection are dominated by ice-phase detection, while stratocumulus, cumulus, and altocumulus are dominated by liquid- and undetermined-phase detection. Ice cloud particle size and optical thickness are largest for cloud scenes containing deep convection and cumulus and are smallest for cirrus. Cloud scenes with multiple cloud types have small reductions in information content and slightly higher residuals of observed and modeled radiance compared to cloud scenes with single cloud types. These results will help advance the development of temperature, specific humidity, and cloud property retrievals from hyperspectral infrared sounders that include cloud microphysics in forward radiative transfer models.


2011 ◽  
Vol 11 (16) ◽  
pp. 8363-8384 ◽  
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
P. T. May ◽  
J. Haynes ◽  
C. Jakob ◽  
...  

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.


2020 ◽  
Author(s):  
Hui Su ◽  
Yuan Wang ◽  
Jonathan Jiang ◽  
Feng Xu ◽  
Yuk Yung

<p>Ice cloud particle size is important to determining ice cloud radiative effect and precipitating rate. However, there is a lack of accurate ice particle effective radius (R<sub>ei</sub>) observation on the global scale and the parameterization of R<sub>ei</sub> in climate models is poorly constrained. We conduct a modeling study to assess the sensitivity of climate simulations to R<sub>ei</sub>. Perturbations to R<sub>ei</sub> are represented in ice fall speed parameterization and radiation scheme, respectively, in NCAR CESM1 model with a slab ocean configuration. We show that an increase in ice fall speed due to a larger R<sub>ei</sub> results in a longwave cooling dominating over a shortwave warming, a global mean surface temperature decrease, and precipitation suppression. Similar longwave and shortwave cloud radiative effect changes occur when R<sub>ei</sub> is perturbed in the radiation scheme. Perturbing falling snow particle size (R<sub>es</sub>) results in much smaller changes in the climate responses. We further show that varying R<sub>ei</sub> and R<sub>es</sub> by 50% to 200% relative to the control experiment can cause climate sensitivity to differ by +12.3% to −6.2%. A future mission under design with combined multi-frequency microwave radiometers and cloud radar can reduce the uncertainty ranges of R<sub>ei</sub> and R<sub>es</sub> from a factor of 2 to ±25%, which would help reducing the climate sensitivity uncertainty pertaining to ice cloud particle size by approximately 60%.</p><p> </p>


2010 ◽  
Vol 28 (2) ◽  
pp. 621-631 ◽  
Author(s):  
P. S. Bhattacharjee ◽  
Y. C. Sud ◽  
X. Liu ◽  
G. K. Walker ◽  
R. Yang ◽  
...  

Abstract. A common deficiency of many cloud-physics parameterizations including the NASA's microphysics of clouds with aerosol-cloud interactions (hereafter called McRAS-AC) is that they simulate lesser (larger) than the observed ice cloud particle number (size). A single column model (SCM) of McRAS-AC physics of the GEOS4 Global Circulation Model (GCM) together with an adiabatic parcel model (APM) for ice-cloud nucleation (IN) of aerosols were used to systematically examine the influence of introducing ammonium sulfate (NH4)2SO4 aerosols in McRAS-AC and its influence on the optical properties of both liquid and ice clouds. First an (NH4)2SO4 parameterization was included in the APM to assess its effect on clouds vis-à-vis that of the other aerosols. Subsequently, several evaluation tests were conducted over the ARM Southern Great Plain (SGP) and thirteen other locations (sorted into pristine and polluted conditions) distributed over marine and continental sites with the SCM. The statistics of the simulated cloud climatology were evaluated against the available ground and satellite data. The results showed that inclusion of (NH4)2SO4 into McRAS-AC of the SCM made a remarkable improvement in the simulated effective radius of ice cloud particulates. However, the corresponding ice-cloud optical thickness increased even more than the observed. This can be caused by lack of horizontal cloud advection not performed in the SCM. Adjusting the other tunable parameters such as precipitation efficiency can mitigate this deficiency. Inclusion of ice cloud particle splintering invoked empirically further reduced simulation biases. Overall, these changes make a substantial improvement in simulated cloud optical properties and cloud distribution particularly over the Intertropical Convergence Zone (ITCZ) in the GCM.


2015 ◽  
Vol 8 (3) ◽  
pp. 1361-1383 ◽  
Author(s):  
S. E. LeBlanc ◽  
P. Pilewskie ◽  
K. S. Schmidt ◽  
O. Coddington

Abstract. A new retrieval scheme for cloud optical thickness, effective radius, and thermodynamic phase was developed for ground-based measurements of cloud shortwave solar spectral transmittance. Fifteen parameters were derived to quantify spectral variations in shortwave transmittance due to absorption and scattering of liquid water and ice clouds, manifested by shifts in spectral slopes, curvatures, maxima, and minima. To retrieve cloud optical thickness and effective particle radius, a weighted least square fit that matched the modeled parameters was applied. The measurements for this analysis were made with the ground-based Solar Spectral Flux Radiometer in Boulder, Colorado, between May 2012 and January 2013. We compared the cloud optical thickness and effective radius from the new retrieval to two other retrieval methods. By using multiple spectral features, we find a closer fit (with a root mean square difference over the entire spectra of 3.1% for a liquid water cloud and 5.9% for an ice cloud) between measured and modeled spectra compared to two other retrieval methods which diverge by a root mean square of up to 6.4% for a liquid water cloud and 22.5% for an ice cloud. The new retrieval introduced here has an average uncertainty in effective radius (± 1.2 μm) smaller by factor of at least 2.5 than two other methods when applied to an ice cloud.


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