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Cirrus are cloud types that are recognized to have a strong impact on the Earth-atmosphere radiation balance. This impact is however still poorly understood, due to the difficulties in describing the large variability of their properties in global climate models. Consequently, numerous airborne and space-borne missions have been dedicated to their study in the last decades. The satellite constellation A-Train has for instance proven to be particularly helpful for the study of cirrus. More particularly, the Infrared Imaging Radiometer (IIR) carried onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite shows a great sensitivity to the radiative and microphysical properties of these clouds. Our study presents a novel methodology that uses the thermal infrared measurements of IIR to retrieve the ice crystal effective size and optical thickness of cirrus. This methodology is based on an optimal estimation scheme, which possesses the advantage of attributing precise uncertainties to the retrieved parameters. Two IIR airborne validation campaigns have been chosen as case studies for illustrating the results of our retrieval method. It is observed that optical thicknesses could be accurately retrieved but that large uncertainties may occur on the effective diameters. Strong agreements have also been found between the products of our method when separately applied to the measurements of IIR and of the airborne radiometer CLIMAT-AV, which consolidates the results of previous validation studies of IIR level-1 measurements. Comparisons with in situ observations and with operational products of IIR are also discussed and appear to be coherent with our results. However, we have found that the quality of our retrievals can be strongly impacted by uncertainties related to the choice of a pristine crystal model and by poor constraints on the properties of possible liquid cloud layers underneath cirrus. Simultaneous retrievals of liquid clouds radiative and microphysical properties and/or the use of different ice crystal models should therefore be considered in order to improve the quality of the results.

The influence is investigated of the assumed ice particle microphysical and optical model on inferring ice cloud optical thickness (τ) from satellite measurements of the Earth's reflected shortwave radiance. Ice cloud τ are inferred, and subsequently compared, using products from MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER (POLarization and Directionality of the Earth's Reflectances). POLDER τ values are found to be substantially smaller than those from collocated MODIS data. It is shown that this difference is caused primarily by the use of different ice particle bulk scattering models in the two retrievals, and more specifically, the scattering phase function. Furthermore, the influence of the ice particle model on the derivation of ice cloud radiative forcing (CRF) from satellite retrievals is studied. Three sets of shortwave CRF are calculated using different combinations of the retrieval and associated ice particle models. It is shown that the uncertainty associated with an ice particle model may lead to two types of errors in estimating CRF from satellite retrievals. One stems from the retrieval itself and the other is due to the optical properties, such as the asymmetry factor, used for CRF calculations. Although a comparison of the CRFs reveals that these two types of errors tend to cancel each other, significant differences are still found between the three CRFs, which indicates that the ice particle model affects not only optical thickness retrievals but also CRF calculations. In addition to CRF, the effect of the ice particle model on the derivation of seasonal variation of τ from satellite measurements is discussed. It is shown that optical thickness retrievals based on the same MODIS observations, but derived using different assumptions of the ice particle model, can be substantially different. These differences can be divided into two parts. The first-order difference is mainly caused by the differences in the asymmetry factor. The second-order difference is related to seasonal changes in the sampled scattering angles and therefore dependent on the sun-satellite viewing geometry. Because of this second-order difference, the use of different ice particle models may lead to a different understanding of the seasonal variation of τ.

In remote sensing applications, clouds are generally characterized by two properties: cloud optical thickness (COT) and effective radius of water–ice particles (Reff), as well as additionally by geometric properties when specific information is available. Most of the current operational passive remote sensing algorithms use a mono-angular bispectral method to retrieve COT and Reff. They are based on pre-computed lookup tables while assuming a homogeneous plane-parallel cloud layer. In this work, we use the formalism of the optimal estimation method, applied to airborne near-infrared high-resolution multi-angular measurements, to retrieve COT and Reff as well as the corresponding uncertainties related to the measurement errors, the non-retrieved parameters, and the cloud model assumptions. The measurements used were acquired by the airborne radiometer OSIRIS (Observing System Including PolaRization in the Solar Infrared Spectrum), developed by the Laboratoire d'Optique Atmosphérique. It provides multi-angular measurements at a resolution of tens of meters, which is very suitable for refining our knowledge of cloud properties and their high spatial variability. OSIRIS is based on the POLDER (POlarization and Directionality of the Earth's Reflectances) concept as a prototype of the future 3MI (Multi-viewing Multi-channel Multi-polarization Imager) planned to be launched on the EUMETSAT-ESA MetOp-SG platform in 2024. The approach used allows the exploitation of all the angular information available for each pixel to overcome the radiance angular effects. More consistent cloud properties with lower uncertainty compared to operational mono-directional retrieval methods (traditional bispectral method) are then obtained. The framework of the optimal estimation method also provides the possibility to estimate uncertainties of different sources. Three types of errors were evaluated: (1) errors related to measurement uncertainties, which reach 6 % and 12 % for COT and Reff, respectively, (2) errors related to an incorrect estimation of the ancillary data that remain below 0.5 %, and (3) errors related to the simplified cloud physical model assuming independent pixel approximation. We show that not considering the in-cloud heterogeneous vertical profiles and the 3D radiative transfer effects leads to an average uncertainty of 5 % and 4 % for COT and 13 % and 9 % for Reff.

The features detected in monolayer atmospheric columns sounded by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and classified as cloud or aerosol layers by the CALIOP version 4 (V4) cloud and aerosol discrimination (CAD) algorithm are reassessed using perfectly collocated brightness temperatures measured by the Imaging Infrared Radiometer (IIR) aboard the same satellite. Using the IIR's three wavelength measurements of layers that are confidently classified by the CALIOP CAD algorithm, we calculate two-dimensional (2-D) probability distribution functions (PDFs) of IIR brightness temperature differences (BTDs) for different cloud and aerosol types. We then compare these PDFs with 1-D radiative transfer simulations for ice and water clouds and dust and marine aerosols. Using these IIR 2-D BTD signature PDFs, we develop and deploy a new IIR-based CAD algorithm and compare the classifications obtained to the results reported by the CALIOP-only V4 CAD algorithm. IIR observations are shown to be able to identify clouds with a good accuracy. The IIR cloud identifications agree very well with layers classified as confident clouds by the V4 CAD algorithm (88 %). More importantly, simultaneous use of IIR information reduces the ambiguity in a notable fraction of “not confident” V4 cloud classifications. 28 % and 14 % of the ambiguous V4 cloud classifications are reclassified more appropriately as confident cloud layers through the use of the IIR observations in the tropics and in the midlatitudes, respectively. IIR observations are of relatively little help in deriving high-confidence classifications for most aerosols, as the low altitudes and small optical depths of aerosol layers yield IIR signatures that are similar to those of clear skies. However, misclassifications of aerosol layers, such as dense dust or elevated smoke layers, by the V4 CAD algorithm can be corrected to cloud layer classification by including IIR information. 10 %, 16 %, and 6 % of the ambiguous V4 dust, polluted dust, and tropospheric elevated smoke, respectively, are found to be misclassified cloud layers by the IIR measurements.

The algorithm presented in this paper was developed to retrieve ice water content (IWC) profiles in cirrus clouds. It is based on optimal estimation theory and combines ground-based visible lidar and thermal infrared (TIR) radiometer measurements in a common retrieval framework in order to retrieve profiles of IWC together with a correction factor for the backscatter intensity of cirrus cloud particles. As a first step, we introduce a method to retrieve extinction and IWC profiles in cirrus clouds from the lidar measurements alone and demonstrate the shortcomings of this approach due to the backscatter-to-extinction ambiguity. As a second step, we show that TIR radiances constrain the backscattering of the ice crystals at the visible lidar wavelength by constraining the ice water path (IWP) and hence the IWC, which is linked to the optical properties of the ice crystals via a realistic bulk ice microphysical model. The scattering phase function obtained from the microphysical model is flat around the backscatter direction (i.e., there is no backscatter peak). We show that using this flat backscattering phase function to define the backscatter-to-extinction ratio of the ice crystals in the retrievals with the lidar-only algorithm results in an overestimation of the IWC, which is inconsistent with the TIR radiometer measurements. Hence, a synergy algorithm was developed that combines the attenuated backscatter profiles measured by the lidar and the measurements of TIR radiances in a common optimal estimation framework to retrieve the IWC profile together with a correction factor for the phase function of the bulk ice crystals in the backscattering direction. We show that this approach yields consistent lidar and TIR results. The resulting lidar ratios for cirrus clouds are found to be consistent with previous independent studies.

Accurate calculations of shortwave reflectances in clear-sky aerosol-laden atmospheres are necessary for various applications in atmospheric sciences. However, computational cost becomes increasingly important for some applications such as data assimilation of top-of-atmosphere reflectances in models of atmospheric composition. This study aims to provide a benchmark that can help in assessing these two requirements in combination. We describe a protocol and input data for 44 080 cases involving various solar and viewing geometries, four different surfaces (one oceanic bidirectional reflectance function and three albedo values for a Lambertian surface), eight aerosol optical depths, five wavelengths, and four aerosol types. We first consider two models relying on the discrete ordinate method: VLIDORT (in vector and scalar configurations) and DISORT (scalar configuration only). We use VLIDORT in its vector configuration as a reference model and quantify the loss of accuracy due to (i) neglecting the effect of polarization in DISORT and VLIDORT (scalar) models and (ii) decreasing the number of streams in DISORT. We further test two other models: the 6SV2 model, relying on the successive orders of scattering method, and Forward-Lobe Two-Stream Radiance Model (FLOTSAM), a new model under development by two of the authors. Typical mean fractional errors of 2.8 % and 2.4 % for 6SV2 and FLOTSAM are found, respectively. Computational cost depends on the input parameters but also on the code implementation and application as some models solve the radiative transfer equations for a range of geometries while others do not. All necessary input and output data are provided as a Supplement as a potential resource for interested developers and users of radiative transfer models.

Simulations of total and polarized cloud reflectance angular signatures such as the ones measured by the multi-angular and polarized radiometer POLDER3/PARASOL are used to evaluate cloud heterogeneity effects on cloud parameter retrievals. Effects on optical thickness, albedo, effective radius and variance of the cloud droplet size distribution and aerosol parameters above cloud are analyzed. Three different clouds that have the same mean optical thicknesses were generated: the first with a flat top, the second with a bumpy top and the last with a fractional cloud cover. At small scale (50 m), for oblique solar incidence, the illumination effects lead to higher total but also polarized reflectances. The polarized reflectances even reach values that cannot be predicted by the 1-D homogeneous cloud assumption. At the POLDER scale (7 km × 7 km), the angular signature is modified by a combination of the plane–parallel bias and the shadowing and illumination effects. In order to quantify effects of cloud heterogeneity on operational products, we ran the POLDER operational algorithms on the simulated reflectances to retrieve the cloud optical thickness and albedo. Results show that the cloud optical thickness is greatly affected: biases can reach up to −70, −50 or +40 % for backward, nadir and forward viewing directions, respectively. Concerning the albedo of the cloudy scenes, the errors are smaller, between −4.7 % for solar incidence angle of 20° and up to about +8 % for solar incidence angle of 60°. We also tested the heterogeneity effects on new algorithms that allow retrieving cloud droplet size distribution and cloud top pressures and also aerosol above clouds. Contrary to the bi-spectral method, the retrieved cloud droplet size parameters are not significantly affected by the cloud heterogeneity, which proves to be a great advantage of using polarized measurements. However, the cloud top pressure obtained from molecular scattering in the forward direction can be biased up to about 60 hPa (around 550 m). Concerning the aerosol optical thickness (AOT) above cloud, the results are different depending on the available angular information. Above the fractional cloud, when only side scattering angles between 100 and 130° are available, the AOT is underestimated because of the plane–parallel bias. However, for solar zenith angle of 60° it is overestimated because the polarized reflectances are increased in forward directions.

Information content analyses on cloud top altitude (CTOP) and geometrical thickness (CGT) from multi-angular A-band measurements in the case of monolayer homogeneous clouds are conducted. In the framework of future multi-angular radiometer development, we compared the potential performances of the 3MI (Multi-viewing, Multi-channel and Multi-polarization Imaging) instrument developed by EUMETSAT, which is an extension of POLDER/PARASOL instrument and MSPI (Multiangle SpectroPolarimetric Imager) developed by NASA's Jet Propulsion Laboratory. Quantitative information content estimates were realized for thin, moderately opaque and opaque clouds for different surface albedo and viewing geometry configurations. Analyses show that retrieval of CTOP is possible with a high accuracy in most of the cases investigated. Retrieval of CGT is also possible for optically thick clouds above a black surface, at least when CGT > 1–2 km and for thin clouds for CGT > 2–3 km. However, for intermediate optical thicknesses (COT ≃ 4), we show that the retrieval of CGT is not simultaneously possible with CTOP. A comparison between 3MI and MSPI shows a higher information content for MSPI's measurements, traceable to a thinner filter inside the oxygen A-band, yielding higher signal-to-noise ratio for absorption estimation. Cases of cloud scenes above bright surfaces are more complex but it is shown that the retrieval of CTOP remains possible in almost all situations while the information content on CGT appears to be insufficient in many cases, particularly for COT

In this study, various ice particle habits are investigated in conjunction with inferring the optical properties of ice clouds for use in the Global Change Observation Mission-Climate (GCOM-C) satellite programme. We develop a database of the single-scattering properties of five ice habit models: plates, columns, droxtals, bullet rosettes, and Voronoi. The database is based on the specification of the Second Generation Global Imager (SGLI) sensor on board the GCOM-C satellite, which is scheduled to be launched in 2017 by the Japan Aerospace Exploration Agency. A combination of the finite-difference time-domain method, the geometric optics integral equation technique, and the geometric optics method is applied to compute the single-scattering properties of the selected ice particle habits at 36 wavelengths, from the visible to the infrared spectral regions. This covers the SGLI channels for the size parameter, which is defined as a single-particle radius of an equivalent volume sphere, ranging between 6 and 9000 µm. The database includes the extinction efficiency, absorption efficiency, average geometrical cross section, single-scattering albedo, asymmetry factor, size parameter of a volume-equivalent sphere, maximum distance from the centre of mass, particle volume, and six nonzero elements of the scattering phase matrix. The characteristics of calculated extinction efficiency, single-scattering albedo, and asymmetry factor of the five ice particle habits are compared. Furthermore, size-integrated bulk scattering properties for the five ice particle habit models are calculated from the single-scattering database and microphysical data. Using the five ice particle habit models, the optical thickness and spherical albedo of ice clouds are retrieved from the Polarization and Directionality of the Earth's Reflectances-3 (POLDER-3) measurements, recorded on board the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The optimal ice particle habit for retrieving the SGLI ice cloud properties is investigated by adopting the spherical albedo difference (SAD) method. It is found that the SAD is distributed stably due to the scattering angle increases for bullet rosettes with an effective diameter (Deff) of 10 µm and Voronoi particles with Deff values of 10, 60, and 100 µm. It is confirmed that the SAD of small bullet-rosette particles and all sizes of Voronoi particles has a low angular dependence, indicating that a combination of the bullet-rosette and Voronoi models is sufficient for retrieval of the ice cloud's spherical albedo and optical thickness as effective habit models for the SGLI sensor. Finally, SAD analysis based on the Voronoi habit model with moderate particle size (Deff = 60 µm) is compared with the conventional general habit mixture model, inhomogeneous hexagonal monocrystal model, five-plate aggregate model, and ensemble ice particle model. The Voronoi habit model is found to have an effect similar to that found in some conventional models for the retrieval of ice cloud properties from space-borne radiometric observations.

This is the first paper to investigate the relationship between the shape of the scattering phase function of cirrus and the relative humidity with respect to ice (RHi, using space-based solar radiometric angle-dependent measurements. The relationship between RHi and the complexity of ice crystals has been previously studied using data from aircraft field campaigns and laboratory cloud chambers. However, to the best of our knowledge, there have been no studies to date that explore this relationship through the use of remotely sensed space-based angle-dependent solar radiometric measurements. In this paper, one case study of semi-transparent cirrus, which occurred on 25 January 2010 off the north-east coast of Scotland, is used to explore the possibility of such a relationship. Moreover, for the first time, RHi fields predicted by a high-resolution numerical weather prediction (NWP) model are combined with satellite retrievals of ice crystal complexity. The NWP model was initialised at midnight, on 25 January 2010, and the mid-latitude RHi field was extracted from the NWP model at 13:00 UTC. At about the same time, there was a PARASOL (Polarization and Anisotropy of Reflectance for Atmospheric science coupled with Observations from a Lidar) overpass, and the PARASOL swath covered the NWP-model-predicted RHi field. The cirrus case was located over Scotland and the North Sea. From the satellite channel based at 0.865 μm, the directionally averaged and directional spherical albedos were retrieved between the scattering angles of about 80 and 130°. An ensemble model of cirrus ice crystals is used to predict phase functions that vary between phase functions that exhibit optical features (referred to as pristine) and featureless phase functions. For each of the PARASOL pixels, the phase function that best minimised differences between the spherical albedos was selected. This paper reports, for this one case study, an association between the most featureless phase function model and the highest values of NWP-predicted RHi (i.e. when RHi > 1.0). For pixels associated with NWP-model-predicted RHi < 1, it was impossible to generally discriminate between phase function models at the 5% significance level. It is also shown that the NWP model prediction of the vertical profile of RHi is in good agreement with dropsonde, in situ measurements and independent aircraft-based physical retrievals of RHi. Furthermore, the NWP model prediction of the cirrus cloud-top height and its vertical extent is also found to be in good agreement with aircraft-based lidar measurements.

Ice clouds are an important element in the radiative balance of the earth's climate system, but their microphysical and optical properties still are not well constrained, especially ice particle habit and the degree of particle surface roughness. In situ observations have revealed common ice particle habits and evidence for surface roughness, but these observations are limited. An alternative is to infer the ice particle shape and surface roughness from satellite observations of polarized reflectivity since they are sensitive to both particle shape and degree of surface roughness. In this study an adding–doubling radiative transfer code is used to simulate polarized reflectivity for nine different ice habits and one habit mixture, along with 17 distinct levels of the surface roughness. A lookup table (LUT) is constructed from the simulation results and used to infer shape and surface roughness from PARASOL satellite polarized reflectivity data over the ocean. Globally, the retrievals yield a compact aggregate of columns as the most commonly retrieved ice habit. Analysis of PARASOL data from the tropics results in slightly more aggregates than in midlatitude or polar regions. Some level of surface roughness is inferred in nearly 70% of PARASOL data, with mean and median roughness near σ = 0.2 and 0.15, respectively. Tropical region analyses have 20% more pixels retrieved with particle surface roughness than in midlatitude or polar regions. The global asymmetry parameter inferred at a wavelength of 0.865 μm has a mean value of 0.77 and a median value of 0.75.

This article is the second in a series of studies investigating the benefits of multispectral measurements to improve the atmospheric parameter retrievals. In the first paper, we presented an information content (IC) analysis from the thermal infrared (TIR) and shortwave infrared (SWIR) bands of Thermal And Near infrared Sensor for carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument dedicated to greenhouse gas retrieval in clear sky conditions. This second paper presents the potential of the spectral synergy from TIR to visible for aerosol characterization, and their impact on the retrieved CO2 and CH4 column concentrations. The IC is then used to determine the most informative spectral channels for the simultaneous retrieval of greenhouse gas total columns and aerosol parameters. The results show that a channel selection spanning the four bands can improve the computation time and retrieval accuracy. Therefore, the spectral synergy allows obtaining up to almost seven different aerosol parameters, which is comparable to the most informative dedicated instruments. Moreover, a channel selection from the TIR to visible bands allows retrieving CO2 and CH4 total columns simultaneously in the presence of one aerosol layer with a similar accuracy to using all channels together to retrieve each gas separately in clear sky conditions.

The Greenhouse gases Observing SATellite (GOSAT) mission, and in particular the Thermal And Near infrared Sensor for carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument, has the advantage of being able to measure simultaneously the same field of view in different spectral ranges with a high spectral resolution. These features allow studying the benefits of using multispectral measurements to improve the CO2 and CH4 retrievals. In order to quantify the impact of the spectral synergy on the retrieval accuracy, we performed an information content (IC) analysis from simulated spectra corresponding to the three infrared bands of TANSO-FTS. The advantages and limitations of using thermal and shortwave infrared simultaneously are discussed according to surface type and state vector composition. The IC is then used to determine the most informative spectral channels for the simultaneous retrieval of CO2 and CH4. The results show that a channel selection spanning the three infrared bands can improve the computation time and retrieval accuracy. Therefore, a selection of less than 700 channels from the thermal infrared (TIR) and shortwave infrared (SWIR) bands allows retrieving CO2 and CH4 simultaneously with a similar accuracy to using all channels together to retrieve each gas separately.

Most of the current aerosol retrievals from passive sensors are restricted to cloud-free scenes, which strongly reduces our ability to monitor the aerosol properties at a global scale and to estimate their radiative forcing. The presence of aerosol above clouds (AAC) affects the polarized light reflected by the cloud layer, as shown by the spaceborne measurements provided by the POlarization and Directionality of Earth Reflectances (POLDER) instrument on the PARASOL satellite. In a previous work, a first retrieval method was developed for AAC scenes and evaluated for biomass-burning aerosols transported over stratocumulus clouds. The method was restricted to the use of observations acquired at forward scattering angles (90–120°) where polarized measurements are highly sensitive to fine-mode particle scattering. Non-spherical particles in the coarse mode, such as mineral dust particles, do not much polarize light and cannot be handled with this method. In this paper, we present new developments that allow retrieving also the properties of mineral dust particles above clouds. These particles do not much polarize light but strongly reduce the polarized cloud bow generated by the liquid cloud layer beneath and observed for scattering angles around 140°. The spectral attenuation can be used to qualitatively identify the nature of the particles (i.e. accumulation mode versus coarse mode, i.e. mineral dust particles versus biomass-burning aerosols), whereas the magnitude of the attenuation is related to the optical thickness of the aerosol layer. We also use the polarized measurements acquired in the cloud bow to improve the retrieval of both the biomass-burning aerosol properties and the cloud microphysical properties. We provide accurate polarized radiance calculations for AAC scenes and evaluate the contribution of the POLDER polarization measurements for the simultaneous retrieval of the aerosol and cloud properties. We investigate various scenes with mineral dust particles and biomass-burning aerosols above clouds. For clouds, our results confirm that the droplet size distribution is narrow in high-latitude ocean regions and that the droplet effective radii retrieved from both polarization measurements and from total radiance measurements are generally close for AAC scenes (departures smaller than 2 μm). We found that the magnitude of the primary cloud bow cannot be accurately estimated with a plane parallel transfer radiative code. The errors for the modeling of the polarized cloud bow are between 4 and 8% for homogenous cloudy scenes, as shown by a 3-D radiative transfer code. These effects only weakly impact the retrieval of the Aerosol Optical Thickness (AOT) performed with a mineral dust particle model for which the microphysical properties are entirely known (relative error smaller than 6%). We show that the POLDER polarization measurements allow retrieving the AOT, the fine-mode particle size, the Ångström exponent and the fraction of spherical particles. However, the complex refractive index and the coarse-mode particle size cannot be accurately retrieved with the present polarization measurements. Our complete and accurate algorithm cannot be applied to process large amounts of data, so a simpler algorithm was developed to retrieve the AOT and the Ångström exponent above clouds in an operational way. Illustrations are provided for July–August 2008 near the African coast. Large mean AOTs above clouds at 0.865 μm (>0.3) are retrieved for oceanic regions near the coasts of South Africa that correspond to biomass-burning aerosols, whereas even larger mean AOTs above clouds for mineral dust particles (>0.6) are also retrieved near the coasts of Senegal. For these regions and time period, the direct AAC radiative forcing is likely to be significant. The final aim of this work is the global monitoring of the AAC properties and the estimation of the direct aerosol radiative forcing in cloudy scenes.

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the " r e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the " r e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.