Ice Cloud Retrievals and Analysis with the Compact Scanning Submillimeter Imaging Radiometer and the Cloud Radar System during CRYSTAL FACE

2005 ◽  
Vol 44 (6) ◽  
pp. 839-859 ◽  
Author(s):  
K. Franklin Evans ◽  
James R. Wang ◽  
Paul E. Racette ◽  
Gerald Heymsfield ◽  
Lihua Li
Keyword(s):  
Particle Diameter ◽  
Submillimeter Wave ◽  
Radar System ◽  
Regional Study ◽  
Bayesian Algorithm ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Brightness Temperatures ◽  
Ice Water

Abstract Submillimeter-wave radiometry is a new technique for determining ice water path (IWP) and particle size in upper-tropospheric ice clouds. The first brightness temperatures images of ice clouds above 340 GHz were measured by the Compact Scanning Submillimeter Imaging Radiometer (CoSSIR) during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) campaign in July 2002. CoSSIR operated with 12 channels from receivers at 183, 220, 380, 487, and 640 GHz. CoSSIR and the nadir-viewing 94-GHz Cloud Radar System (CRS) flew on the NASA ER-2 airplane based out of Key West, Florida. A qualitative comparison of the CoSSIR brightness temperatures demonstrates that the submillimeter-wave frequencies are more sensitive to anvil ice cloud particles than are the lower frequencies. A Bayesian algorithm, with a priori microphysical information from in situ cloud probes, is used to retrieve the IWP and median mass equivalent sphere particle diameter (Dme). Microwave scattering properties of random aggregates of plates and aggregates of frozen droplets are computed with the discrete dipole approximation (DDA) and an effective medium approximation tuned to DDA results. As a test of the retrievals, the vertically integrated 94-GHz radar backscattering is also retrieved from the CoSSIR data and compared with that measured by the CRS. The integrated backscattering typically agrees within 1–2 dB for IWP from 1000 to 10 000 g m−2, and while the disagreement increases for smaller IWP, it is typically within the Bayesian error bars. Retrievals made with only the three 183- and one 220-GHz channel are generally as good or better than those including 380 ± 6.2 and 640 GHz, because the CoSSIR submillimeter-wave channels were much noisier than expected. An algorithm to retrieve profiles of ice water content and Dme from CRS and CoSSIR data was developed. This Bayesian algorithm also retrieves the coefficients of an IWC–radar reflectivity power-law relation and could be used to evaluate radar-only ice cloud retrieval algorithms.

Snow Size Distribution Parameterization for Midlatitude and Tropical Ice Clouds

2007 ◽  
Vol 64 (12) ◽  
pp. 4346-4365 ◽  
Author(s):  
Paul R. Field ◽  
Andrew J. Heymsfield ◽  
Aaron Bansemer
Keyword(s):  
Water Content ◽  
Size Distribution ◽  
Tropical Rainfall Measuring Mission ◽  
Time Averaging ◽  
Size Distributions ◽  
Regional Study ◽  
Ice Clouds ◽  
Microphysical Process ◽  
Ice Water Content ◽  
Ice Water

Abstract Many microphysical process rates involving snow are proportional to moments of the snow particle size distribution (PSD), and in this study a moment estimation parameterization applicable to both midlatitude and tropical ice clouds is proposed. To this end aircraft snow PSD data were analyzed from tropical anvils [Tropical Rainfall Measuring Mission/Kwajelein Experiment (TRMM/KWAJEX), Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE)] and midlatitude stratiform cloud [First International Satellite Cloud Climatology Project Research Experiment (FIRE), Atmospheric Radiation Measurement Program (ARM)]. For half of the dataset, moments of the PSDs are computed and a parameterization is generated for estimating other PSD moments when the second moment (proportional to the ice water content when particle mass is proportional to size squared) and temperature are known. Subsequently the parameterization was tested with the other half of the dataset to facilitate an independent comparison. The parameterization for estimating moments can be applied to midlatitude or tropical clouds without requiring prior knowledge of the regime of interest. Rescaling of the tropical and midlatitude size distributions is presented along with fits to allow the user to recreate realistic PSDs given estimates of ice water content and temperature. The effects of using different time averaging were investigated and were found not to be adverse. Finally, the merits of a single-moment snow microphysics versus multimoment representations are discussed, and speculation on the physical differences between the rescaled size distributions from the Tropics and midlatitudes is presented.

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.

Quantification of the Effects of Shattering on Airborne Ice Particle Measurements

2013 ◽  
Vol 30 (11) ◽  
pp. 2527-2553 ◽  
Author(s):  
A. V. Korolev ◽  
E. F. Emery ◽  
J. W. Strapp ◽  
S. G. Cober ◽  
G. A. Isaac
Keyword(s):  
Number Concentration ◽  
Ice Clouds ◽  
Particle Measurements ◽  
Ice Cloud ◽  
Ice Water Content ◽  
High Concentrations ◽  
2D Data ◽  
Special Circumstances ◽  
Ice Water

Abstract Ice particle shattering poses a serious problem to the airborne characterization of ice cloud microstructure. Shattered ice fragments may contaminate particle measurements, resulting in artificially high concentrations of small ice. The ubiquitous observation of small ice particles has been debated over the last three decades. The present work is focused on the study of the effect of shattering based on the results of the Airborne Icing Instrumentation Evaluation (AIIE) experiment flight campaign. Quantitative characterization of the shattering effect was studied by comparing measurements from pairs of identical probes, one modified to mitigate shattering using tips designed for this study (K-tips) and the other in the standard manufacturer’s configuration. The study focused on three probes: the forward scattering spectrometer probe (FSSP), the optical array probe (OAP-2DC), and the cloud imaging probe (CIP). It has been shown that the overestimation errors of the number concentration in size distributions measured by 2D probes increase with decreasing size, mainly affecting particles smaller than approximately 500 μm. It was found that shattering artifacts may increase measured particle number concentration by 1 to 2 orders of magnitude. However, the associated increase of the extinction coefficient and ice water content derived from 2D data is estimated at only 20%–30%. Existing antishattering algorithms alone are incapable of filtering out all shattering artifacts from OAP-2DC and CIP measurements. FSSP measurements can be completely dominated by shattering artifacts, and it is not recommended to use this instrument for measurements in ice clouds, except in special circumstances. Because of the large impact of shattering on ice measurements, the historical data collected by FSSP and OAP-2DC should be reexamined by the cloud physics community.

scholarly journals Improved Radar Ice Water Content Retrieval Algorithms Using Coincident Microphysical and Radar Measurements

2005 ◽  
Vol 44 (9) ◽  
pp. 1391-1412 ◽  
Author(s):  
Andrew J. Heymsfield ◽  
Zhien Wang ◽  
Sergey Matrosov
Keyword(s):  
Water Content ◽  
Radar Reflectivity ◽  
Regional Study ◽  
Ice Clouds ◽  
Analytic Expressions ◽  
Ice Water Content ◽  
Particle Ensemble ◽  
Radar Measurements ◽  
Ice Water ◽  
Spaceborne Radar

Abstract Airborne radar reflectivity measurements at frequencies of 9.6 and 94 GHz, with collocated, in situ particle size distribution and ice water content measurements from the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) in Florida in July 2002, offer one of the first opportunities to evaluate and improve algorithms for retrieving ice water content from single-wavelength spaceborne radar measurements. Both ice water content and radar reflectivity depend on the distribution of particle mass with size. It is demonstrated that single, power-law, mass dimensional relationships are unable to adequately account for the dominating contribution of small particles at lower reflectivities and large particles at higher reflectivities. To circumvent the need for multiple, or complex, mass dimensional relationships, analytic expressions that use particle ensemble mean ice particle densities that are derived from the coincident microphysical and radar observations are developed. These expressions, together with more than 5000 CRYSTAL FACE size distributions, are used to develop radar reflectivity–ice water content relationships for the two radar wavelengths that appear to provide improvements over earlier relationships, at least for convectively generated stratiform ice clouds.

scholarly journals Ice hydrometeor profile retrieval algorithm for high-frequency microwave radiometers: application to the CoSSIR instrument during TC4

2012 ◽  
Vol 5 (9) ◽  
pp. 2277-2306 ◽  
Author(s):  
K. F. Evans ◽  
J. R. Wang ◽  
D. O'C Starr ◽  
G. Heymsfield ◽  
L. Li ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Relative Humidity ◽  
A Priori ◽  
Submillimeter Wave ◽  
Monte Carlo Integration ◽  
Cumulative Distribution ◽  
Retrieval Algorithm ◽  
Hybrid Technique ◽  
Ice Cloud ◽  
Ice Water

Abstract. A Bayesian algorithm to retrieve profiles of cloud ice water content (IWC), ice particle size (Dme), and relative humidity from millimeter-wave/submillimeter-wave radiometers is presented. The first part of the algorithm prepares an a priori file with cumulative distribution functions (CDFs) and empirical orthogonal functions (EOFs) of profiles of temperature, relative humidity, three ice particle parameters (IWC, Dme, distribution width), and two liquid cloud parameters. The a priori CDFs and EOFs are derived from CloudSat radar reflectivity profiles and associated ECMWF temperature and relative humidity profiles combined with three cloud microphysical probability distributions obtained from in situ cloud probes. The second part of the algorithm uses the CDF/EOF file to perform a Bayesian retrieval with a hybrid technique that uses Monte Carlo integration (MCI) or, when too few MCI cases match the observations, uses optimization to maximize the posterior probability function. The very computationally intensive Markov chain Monte Carlo (MCMC) method also may be chosen as a solution method. The radiative transfer model assumes mixtures of several shapes of randomly oriented ice particles, and here random aggregates of spheres, dendrites, and hexagonal plates are used for tropical convection. A new physical model of stochastic dendritic snowflake aggregation is developed. The retrieval algorithm is applied to data from the Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) flown on the ER-2 aircraft during the Tropical Composition, Cloud and Climate Coupling (TC4) experiment in 2007. Example retrievals with error bars are shown for nadir profiles of IWC, Dme, and relative humidity, and nadir and conical scan swath retrievals of ice water path and average Dme. The ice cloud retrievals are evaluated by retrieving integrated 94 GHz backscattering from CoSSIR for comparison with the Cloud Radar System (CRS) flown on the same aircraft. The rms difference in integrated backscattering is around 3 dB over a 30 dB range. A comparison of CoSSIR retrieved and CRS measured reflectivity shows that CoSSIR has the ability to retrieve low-resolution ice cloud profiles in the upper troposphere.

scholarly journals Why we need radar, lidar, and solar radiance observations to constrain ice cloud microphysics

2021 ◽  
Author(s):  
Florian Ewald ◽  
Silke Groß ◽  
Martin Wirth ◽  
Julien Delanoë ◽  
Stuart Fox ◽  
...  
Keyword(s):  
Water Content ◽  
Cloud Microphysics ◽  
Accurate Estimation ◽  
Crystal Shape ◽  
Radiative Effect ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Ice Water Content ◽  
Ice Water

Abstract. Ice clouds and their effect on Earth's radiation budget are one of the largest sources of uncertainty in climate change predictions. The uncertainty in predicting ice cloud feedbacks in a warming climate arises due to uncertainties in measuring and explaining their current optical and microphysical properties as well as from insufficient knowledge about their spatial and temporal distribution. This knowledge can be significantly improved by active remote sensing, which can help to explore the vertical profile of ice cloud microphysics, such as ice particle size and ice water content. This study focuses on the well-established variational approach VarCloud to retrieve ice cloud microphysics from radar-lidar measurements. While active backscatter retrieval techniques surpass the information content of most passive, vertically integrated retrieval techniques, their accuracy is limited by essential assumptions about the ice crystal shape. Since most radar-lidar retrieval algorithms rely heavily on universal mass-size relationships to parameterize the prevalent ice particle shape, biases in ice water content and ice water path can be expected in individual cloud regimes. In turn, these biases can lead to an erroneous estimation of the radiative effect of ice clouds. In many cases, these biases could be spotted and corrected by the simultaneous exploitation of measured solar radiances. The agreement with measured solar radiances is a logical prerequisite for an accurate estimation of the radiative effect of ice clouds. To this end, this study exploits simultaneous radar, lidar, and passive measurements made on board the German High Altitude and Long Range Research Aircraft. By using the ice clouds derived with VarCloud as an input to radiative transfer calculations, simulated solar radiances are compared to measured solar radiances made above the actual clouds. This radiative closure study is done using different ice crystal models to improve the knowledge of the prevalent ice crystal shape. While in one case aggregates were capable of reconciling radar, lidar, and solar radiance measurements, this study also analyses a more problematic case for which no radiative closure could be achieved. In this case, simultaneously acquired in-situ measurements could narrow this inability to an unexpected high ice crystal number concentration.

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

2010 ◽  
Vol 10 (8) ◽  
pp. 20069-20124
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
P. T. May ◽  
J. Haynes ◽  
C. Jakob ◽  
...  
Keyword(s):  
Large Scale ◽  
Cloud Fraction ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Mean Differences ◽  
Ice Water ◽  
Lidar Observations

Abstract. 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, cloud fraction as derived considering a typical large-scale model grid box), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, terminal fall speed, 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 rationale for characterizing this variability is to provide an observational basis to which model outputs can be compared for the different regimes or large-scale characteristics and from which new parameterizations accounting for the large-scale context can be derived. The mean vertical variability of ice cloud occurrence and microphysical properties is large (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). Our results also indicate that, at least in the northern Australian region, the upper part of the troposphere can be split into three distinct layers characterized by different statistically-dominant microphysical processes. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is found to be large, producing mean differences of up to a factor of 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes, a factor of 3 to 4 for the ISCCP regimes and the MJO phases, and mean differences of a factor of 2 typically in all microphysical properties analysed in the present paper between large-scale atmospheric regimes or MJO phases. Large differences in occurrence (up to 60–80%) are also found in the main patterns of the cloud fraction distribution of ice clouds (fractions smaller than 0.3 and larger than 0.9). 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 (almost no detectable diurnal cycle) to values in excess of 2.0 (very large diurnal amplitude).

scholarly journals The Characterization of Ice Cloud Properties from Doppler Radar Measurements

2007 ◽  
Vol 46 (10) ◽  
pp. 1682-1698 ◽  
Author(s):  
Julien Delanoë ◽  
A. Protat ◽  
D. Bouniol ◽  
Andrew Heymsfield ◽  
Aaron Bansemer ◽  
...  
Keyword(s):  
Water Content ◽  
Weather Prediction ◽  
Doppler Velocity ◽  
Fall Velocity ◽  
Ice Cloud ◽  
Cloud Radar ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Radar Measurements ◽  
Ice Water

Abstract The paper describes an original method that is complementary to the radar–lidar algorithm method to characterize ice cloud properties. The method makes use of two measurements from a Doppler cloud radar (35 or 95 GHz), namely, the radar reflectivity and the Doppler velocity, to recover the effective radius of crystals, the terminal fall velocity of hydrometeors, the ice water content, and the visible extinction from which the optical depth can be estimated. This radar method relies on the concept of scaling the ice particle size distribution. An error analysis using an extensive in situ airborne microphysical database shows that the expected errors on ice water content and extinction are around 30%–40% and 60%, respectively, including both a calibration error and a bias on the terminal fall velocity of the particles, which all translate into errors in the retrieval of the density–diameter and area–diameter relationships. Comparisons with the radar–lidar method in areas sampled by the two instruments also demonstrate the accuracy of this new method for retrieval of the cloud properties, with a roughly unbiased estimate of all cloud properties with respect to the radar–lidar method. This method is being systematically applied to the cloud radar measurements collected over the three-instrumented sites of the European Cloudnet project to validate the representation of ice clouds in numerical weather prediction models and to build a cloud climatology.

scholarly journals A two-habit model for the microphysical and optical properties of ice clouds

2014 ◽  
Vol 14 (24) ◽  
pp. 13719-13737 ◽  
Author(s):  
C. Liu ◽  
P. Yang ◽  
P. Minnis ◽  
N. Loeb ◽  
S. Kato ◽  
...  
Keyword(s):  
Optical Properties ◽  
Near Infrared ◽  
Cloud Model ◽  
In Situ Measurements ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Sensing Applications ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ice Water

Abstract. To provide a better representation of natural ice clouds, a novel ice cloud model is developed by assuming an ice cloud to consist of an ensemble of hexagonal columns and 20-element aggregates with specific habit fractions at each particle size bin. The microphysical and optical properties of this two-habit model (THM) are compared with both laboratory and in situ measurements, and its performance in downstream satellite remote sensing applications is assessed. The ice water contents and median mass diameters calculated based on the THM closely agree with in situ measurements made during 11 field campaigns. In this study, the scattering, absorption, and polarization properties of ice crystals are calculated with a combination of the invariant imbedding T matrix, pseudo-spectral time domain, and improved geometric-optics methods over an entire practical range of particle sizes. The phase functions, calculated based on the THM, show close agreement with counterparts from laboratory and in situ measurements and from satellite-based retrievals. When the THM is applied to the retrievals of cloud microphysical and optical properties from MODIS (the Moderate Resolution Imaging Spectroradiometer) observations, excellent spectral consistency is achieved; specifically, the retrieved cloud optical thicknesses based on the visible/near infrared bands and the thermal infrared bands agree quite well. Furthermore, a comparison between the polarized reflectivities observed by the PARASOL satellite and from theoretical simulations illustrates that the THM can be used to represent ice cloud polarization properties.

scholarly journals Why we need radar, lidar, and solar radiance observations to constrain ice cloud microphysics

2021 ◽  
Vol 14 (7) ◽  
pp. 5029-5047
Author(s):  
Florian Ewald ◽  
Silke Groß ◽  
Martin Wirth ◽  
Julien Delanoë ◽  
Stuart Fox ◽  
...  
Keyword(s):  
Water Content ◽  
Cloud Microphysics ◽  
Accurate Estimation ◽  
Crystal Shape ◽  
Radiative Effect ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Ice Water Content ◽  
Ice Water

Abstract. Ice clouds and their effect on earth's radiation budget are one of the largest sources of uncertainty in climate change predictions. The uncertainty in predicting ice cloud feedbacks in a warming climate arises due to uncertainties in measuring and explaining their current optical and microphysical properties as well as from insufficient knowledge about their spatial and temporal distribution. This knowledge can be significantly improved by active remote sensing, which can help to explore the vertical profile of ice cloud microphysics, such as ice particle size and ice water content. This study focuses on the well-established variational approach VarCloud to retrieve ice cloud microphysics from radar–lidar measurements. While active backscatter retrieval techniques surpass the information content of most passive, vertically integrated retrieval techniques, their accuracy is limited by essential assumptions about the ice crystal shape. Since most radar–lidar retrieval algorithms rely heavily on universal mass–size relationships to parameterize the prevalent ice particle shape, biases in ice water content and ice water path can be expected in individual cloud regimes. In turn, these biases can lead to an erroneous estimation of the radiative effect of ice clouds. In many cases, these biases could be spotted and corrected by the simultaneous exploitation of measured solar radiances. The agreement with measured solar radiances is a logical prerequisite for an accurate estimation of the radiative effect of ice clouds. To this end, this study exploits simultaneous radar, lidar, and passive measurements made on board the German High Altitude and Long Range Research Aircraft. By using the ice clouds derived with VarCloud as an input to radiative transfer calculations, simulated solar radiances are compared to measured solar radiances made above the actual clouds. This radiative closure study is done using different ice crystal models to improve the knowledge of the prevalent ice crystal shape. While in one case aggregates were capable of reconciling radar, lidar, and solar radiance measurements, this study also analyses a more problematic case for which no radiative closure could be achieved. In this case, collocated in situ measurements indicate that the lack of closure may be linked to unexpectedly high values of the ice crystal number density.

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