Ice Cloud Optical Properties Research Articles

A new approach to crystal habit retrieval from far-infrared spectral radiance measurements

Abstract. To generate reliable climate predictions, global models need accurate estimates of all the energy fluxes contributing to the Earth's radiation budget (ERB). Clouds in general, and more specifically ice clouds, play a key role in the determination of the ERB as they may exert either a feedback or a forcing action, depending on their optical and microphysical properties and physical state (solid/liquid). To date, accurate statistics and climatologies of cloud parameters are not available. Specifically, the ice cloud composition in terms of ice crystal shape (or habit) is one of the parameters with the largest uncertainty. The Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) experiment, foreseen to be the ninth Earth Explorer mission of the European Space Agency, will measure, for the first time spectrally resolved from space, the entire upwelling spectrum emitted by the Earth from 100 to 1600 cm−1. The far-infrared portion of the Earth spectrum, especially from 200 to 600 cm−1, is very sensitive to cloud ice crystal shapes; thus, FORUM measurements could also represent an opportunity to study the ice cloud composition in terms of ice crystal habit mixtures. To investigate this possibility, we developed an accurate and advanced scheme allowing us to model ice cloud optical properties – also in cases of clouds composed of mixed ice crystal habits. This feature is in fact necessary because in situ measurements acquired over the years also point out that the shape of ice cloud crystals varies depending on the crystal size range. In our model, the resulting cloud optical properties are also determined by the input habit fractions. Thus, the retrieval of these fractions from spectral radiance measurements can be attempted. Using 375 different cloudy scenarios, we assess the performance of our retrieval scheme in the determination of crystal habit mixtures starting from FORUM-simulated measurements. The most relevant error components affecting the retrieved cloud parameters are not very large and are of random nature; thus, FORUM measurements will allow us to set up an accurate climatology of cloud parameters. To provide an example of the benefit that one could get from the habit mixture retrievals, we also show the improved accuracy of the thermal outgoing fluxes calculations compared to using assumed mixtures.

A Robust Ice Cloud Optical Property Model for Lidar-Based Remote Sensing Applications

A Robust Ice Cloud Optical Property Model for Lidar-Based Remote Sensing Applications

Novel Parameterization of Ice Cloud Effective Diameter from Collocated CALIOP-IIR and CloudSat Retrievals

Abstract Satellite-based measurements of global ice cloud microphysical properties are sampled to develop a novel set of physical parameterizations, relating to cloud layer temperature and effective diameter De, that can be implemented for two separate applications: in numerical weather prediction models and lidar-based cloud radiative forcing studies. Ice cloud optical properties (i.e., spectral scattering and absorption) are estimated based on the effective size and habit mixture of the cloud particles. Historically, the ice cloud De has been parameterized from aircraft in situ measurements. However, aircraft-based parameterizations are opportunistic in that they only represent specific types of clouds (e.g., convective anvil, tropopause-topped cirrus) in the regions in which they were sampled and, in some cases, are limited in fully resolving the entire vertical cloud layer. Breaking away from the aircraft-based parameterization paradigm, this study is the first of its kind to attempt a parameterization of De as a function of temperature, ice water content (IWC), and lidar-derived extinction from satellite-based global oceanic measurements of ice clouds. Data from both active and passive remote sensing sensors from two of NASA’s A-Train satellites, CloudSat and CALIPSO, are collected to guide development of globally robust parameterizations of all ice cloud types and one exclusively for cirrus clouds. Significance Statement We derived unique parameterizations of ice crystal effective size from global satellite measurements in an effort to more robustly and consistently represent ice clouds in numerical models for weather forecasting and climate energy balance studies. Based on our results, effective ice crystal size is easily solved based on temperature and visible cloud translucence. By knowing the size of the ice crystals, we can then estimate cloud scattering and absorption. In comparison with aircraft-based parameterizations, the satellite data reveal that ice crystal effective sizes are much smaller, on global average, for ice clouds occurring in relatively warm layers (>230 K), indicating that many ice clouds are more reflective than previously believed.

Diverse cloud radiative effects and global surface temperature simulations induced by different ice cloud optical property parameterizations

The representation of ice cloud optical properties in climate models has long been a difficult problem. Very different ice cloud optical property parameterization schemes developed based on very different assumptions of ice particle shape habits, particle size distributions, and surface roughness conditions, are used in various models. It is not clear as to how simulated climate variables are affected by the ice cloud optical property parameterizations. A total of five ice cloud optical property parameterization schemes, including three based on the ice habit mixtures suitable for general ice clouds, mid-latitude synoptic ice clouds, and tropical deep convective ice clouds, and the other two based on single ice habits (smooth hexagonal column and severely roughened column aggregate), are developed under a same framework and are implemented in the National Center for Atmospheric Research Community Atmospheric Model version 5. A series of atmosphere-only climate simulations are carried out for each of the five cases with different ice parameterizations. The differences in the simulated top of the atmosphere shortwave and longwave cloud radiative effects (CREs) are evaluated, and the global averaged net CRE differences among different cases range from − 1.93 to 1.03 Wm−2. The corresponding changes in simulated surface temperature are found to be most prominent on continental regions which amount to several degrees in Kelvin. Our results indicate the importance of choosing a reasonable ice cloud optical property parameterization in climate simulations.

Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

Assessing the accuracy and efficiency of longwave radiative transfer models involving scattering effect with cloud optical property parameterizations

A radiative transfer model (RTM) that accurately and explicitly accounts for both absorbing and scattering effects requires a substantial amount of computational effort. In the longwave (LW) spectral regime, the atmosphere is optically opaque and absorbs a large portion of terrestrial thermal radiation. To alleviate the computational burden, clouds are assumed to be only absorptive in most general circulation models (GCMs) and their scattering effects are neglected. Using parameterizations of cloud bulk single-scattering properties derived from the latest cloud optical property models for satellite remote sensing, this study analyzes the numerical accuracy and efficiency of a variety of LW RTMs . The approaches considered in this study include the absorption approximation (AA), the absorption approximation with scattering parameterization (ASA), the two-stream approximation (2S), a hybrid two- and four-stream approximation (2/4S), and the discrete ordinate radiative transfer (DISORT) with multiple streams. These approximations are benchmarked against 128-stream DISORT calculation. After evaluating the full ranges of ice and water cloud optical and microphysical properties using these RTMs, we find that neglecting LW scattering effect causes simulation errors as large as ±15% by using the AA method. Among these RTMs, the 2/4S method provides an optimal balance between computational efficiency and accuracy, leading to the maximum cloud emissivity errors within ±5%, 25th to 75th percentile errors about ±1%, and almost zero net bias. Therefore, the 2/4S approximation is computationally accurate and yet affordable option for incorporating cloud longwave scattering effect into the radiation schemes used in weather and climate models.

Oriented Ice Crystals: A Single-Scattering Property Database for Applications to Lidar and Optical Phenomenon Simulations

Abstract A database (TAMUoic2019) of the scattering, absorption, and polarization properties of horizontally oriented hexagonal plates (HOPs) and horizontally oriented hexagonal columns (HOCs) at three wavelengths (355, 532, and 1064 nm) is developed for applications to radiative transfer simulations and remote sensing implementations involving oriented ice crystals. The maximum dimension of oriented ice crystals ranges from 50 to 10 000 μm in 165 discrete size bins. The database accounts for 94 incident directions. The single-scattering properties of oriented ice crystals are computed with the physical-geometric optics method (PGOM), which is consistent with the invariant-imbedding T-matrix method for particles with size parameters larger than approximately 100–150. Note that the accuracy of PGOM increases as the size parameter increases. PGOM computes the two-dimensional phase matrix as a function of scattering polar and azimuth angles, and the phase matrix significantly varies with the incident direction. To derive the bulk optical properties of ice clouds for practical radiative transfer applications, the optical properties of individual HOPs and HOCs are averaged over the probability distribution of the tilting angle of oriented ice crystals based on the use of the TAMUoic2019 database. Simulations of lidar signals associated with ice clouds based on the bulk optical properties indicate the importance of the fraction of oriented ice crystals and the probability distribution of the tilting angle. Simulations of optical phenomena caused by oriented ice crystals demonstrate that the computed single-scattering properties of oriented ice crystals are physically rational.

A Review of Ice Cloud Optical Property Models for Passive Satellite Remote Sensing

The current wealth of spaceborne passive and active measurements from ultraviolet to the infrared wavelengths provides an unprecedented opportunity to construct ice cloud bulk optical property models that lead to consistent ice cloud property retrievals across multiple sensors and platforms. To infer the microphysical and radiative properties of ice clouds from these satellite measurements, the general approach is to assume an ice cloud optical property model that implicitly assumes the habit (shape) and size distributions of the ice particles in these clouds. The assumption is that this ice optical property model will be adequate for global retrievals. In this review paper, we first summarize the key optical properties of individual particles and then the bulk radiative properties of their ensemble, followed by a review of the ice cloud models developed for application to satellite remote sensing. We illustrate that the random orientation condition assumed for ice particles is arguably justified for passive remote sensing applications based on radiometric measurements. The focus of the present discussion is on the ice models used by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Clouds and Earth’s Radiant Energy System (CERES) science teams. In addition, we briefly review the ice cloud models adopted by the Polarization and Directionality of the Earth’s Reflectance (POLDER) and the Himawari-8 Advanced Himawari Imager (AHI) for ice cloud retrievals. We find that both the MODIS Collection 6 ice model and the CERES two-habit model result in spectrally consistent retrievals.

The retrieval of ice cloud parameters from multi-spectral satellite observations of reflectance using a modified XBAER algorithm

Retrieval of ice cloud properties from passive remote satellite instruments using multispectral observations of the upwelling radiance at the top of atmosphere is challenging. This requires an accurate separation of the surface spectral reflectance below the cloud and that coming from the ice cloud particle. In this paper, a weighting-function based method is described, which retrieves ice cloud optical thickness (COT) and ice cloud crystal effective radius (CER). The retrieval algorithm belongs to the newly developed eXtensible Bremen Aerosol Retrieval (XBAER) algorithm family, and is called XBAER-ice. The XBAER-ice retrieval uses a surface reflectance parameterization minimizing the impact of surface scattering on the retrieval of optically thin ice cloud properties. A fractal model is used to describe the ice cloud optical properties. The comparison of COT and CER between XBAER-ice and latest Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products shows good agreement. We note that ice cloud property retrievals are particularly sensitive to assumptions about the ice particle shape. The comparison between satellite derived COTs using both the MODIS C6 product and XBAER-ice algorithm agree well with Atmospheric Radiation Measurement (ARM) in-situ measurements (with correlation coefficient above 0.9) whereas CERs show poorer agreement (~0.6). The global spatial distribution patterns and values of COT from ice clouds retrieved by using the MODIS C6 and XBAER-ice algorithms show a high degree of consistency. The XBAER-ice derived ice cloud CER values are systematically smaller than the MODIS C6 product, but both products have similar spatial distribution patterns. The XBAER-ice offers a potential alternative algorithm for the synergistic operational retrieval of ice cloud properties from the observations of Ocean and Land Colour Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) onboard Sentinel-3.

Simulation of the brightness temperatures observed by the visible infrared imaging radiometer suite instrument (Erratum)

Clouds play a large role in the Earth’s global energy budget, but the impact of cirrus clouds is still widely questioned and researched. Cirrus clouds reside high in the atmosphere and due to cold temperatures are comprised of ice crystals. Gaining a better understanding of ice cloud optical properties and the distribution of cirrus clouds provides an explanation for the contribution of cirrus clouds to the global energy budget. Using radiative transfer models (RTMs), accurate simulations of cirrus clouds can enhance the understanding of the global energy budget as well as improve the use of global climate models. A newer, faster RTM such as the visible infrared imaging radiometer suite (VIIRS) fast radiative transfer model (VFRTM) is compared to a rigorous RTM such as the line-by-line radiative transfer model plus the discrete ordinates radiative transfer program. By comparing brightness temperature (BT) simulations from both models, the accuracy of the VFRTM can be obtained. This study shows root-mean-square error <0.2 K for BT difference using reanalysis data for atmospheric profiles and updated ice particle habit information from the moderate-resolution imaging spectroradiometer collection 6. At a higher resolution, the simulated results of the VFRTM are compared to the observations of VIIRS resulting in a <1.5 % error from the VFRTM for all cases. The VFRTM is validated and is an appropriate RTM to use for global cloud retrievals.

Simulation of the brightness temperatures observed by the visible infrared imaging radiometer suite instrument

Clouds play a large role in the Earth’s global energy budget, but the impact of cirrus clouds is still widely questioned and researched. Cirrus clouds reside high in the atmosphere and due to cold temperatures are comprised of ice crystals. Gaining a better understanding of ice cloud optical properties and the distribution of cirrus clouds provides an explanation for the contribution of cirrus clouds to the global energy budget. Using radiative transfer models (RTMs), accurate simulations of cirrus clouds can enhance the understanding of the global energy budget as well as improve the use of global climate models. A newer, faster RTM such as the visible infrared imaging radiometer suite (VIIRS) fast radiative transfer model (VFRTM) is compared to a rigorous RTM such as the line-by-line radiative transfer model plus the discrete ordinates radiative transfer program. By comparing brightness temperature (BT) simulations from both models, the accuracy of the VFRTM can be obtained. This study shows root-mean-square error <0.2 K for BT difference using reanalysis data for atmospheric profiles and updated ice particle habit information from the moderate-resolution imaging spectroradiometer collection 6. At a higher resolution, the simulated results of the VFRTM are compared to the observations of VIIRS resulting in a <1.5 % error from the VFRTM for all cases. The VFRTM is validated and is an appropriate RTM to use for global cloud retrievals.

Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4°C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

A comparison of Aqua MODIS ice and liquid water cloud physical and optical properties between collection 6 and collection 5.1: Pixel‐to‐pixel comparisons

AbstractWe compare differences in ice and liquid water cloud physical and optical properties between Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (C6) and collection 5.1 (C51). The C6 cloud products changed significantly due to improved calibration, improvements based on comparisons with the Cloud‐Aerosol Lidar with Orthogonal Polarization, treatment of subpixel liquid water clouds, introduction of a roughened ice habit for C6 rather than the use of smooth ice particles in C51, and more. The MODIS cloud products form a long‐term data set for analysis, modeling, and various purposes. Thus, it is important to understand the impact of the changes. Two cases are considered for C6 to C51 comparisons. Case 1 considers pixels with valid cloud retrievals in both C6 and C51, while case 2 compares all valid cloud retrievals in each collection. One year (2012) of level‐2 MODIS cloud products are examined, including cloud effective radius (CER), optical thickness (COT), water path, cloud top pressure (CTP), cloud top temperature, and cloud fraction. Large C6–C51 differences are found in the ice CER (regionally, as large as 15 μm) and COT (decrease in annual average by approximately 25%). Liquid water clouds have higher CTP in marine stratocumulus regions in C6 but lower CTP globally (−5 hPa), and there are 66% more valid pixels in C6 (case 2) due to the treatment of pixels with subpixel clouds. Simulated total cloud radiative signatures from C51 and C6 are compared to Clouds and the Earth's Radiant Energy System Energy Balanced And Filled (EBAF) product. The C6 CREs compare more closely with the EBAF than the C51 counterparts.

A comparison of Aqua MODIS ice and liquid water cloud physical and optical properties between collection 6 and collection 5.1: Cloud radiative effects

AbstractIn our companion study, we show how cloud property products change from MODIS (Moderate Resolution Imaging Spectroradiometer) collection 5.1 (C51) to collection 6 (C6) for both ice and liquid water clouds through a pixel‐to‐pixel comparison. However, the question remains as to the full impacts of these cloud property differences between collections on the inference of cloud radiative effects (CREs). In this study, we address this question from a modeling perspective using one year (2012) of MODIS gridded annual‐averaged ice/liquid water cloud properties at 0.5° × 0.5° spatial resolution. The rapid radiative transfer model for general circulation model applications is used to simulate the broadband radiative fluxes at the top of the atmosphere under clear‐sky and cloudy‐sky conditions. The shortwave, longwave, and net radiative effects of ice, liquid water, and total clouds are derived individually assuming different cloud optical property parameterization schemes. The results provide quantifications of ice and liquid water CRE contributions to the total CRE. We find significant differences in the simulated CREs between C6 and C51 for ice clouds (up to 23 W m−2 for the shortwave CRE) and liquid water clouds (approximately −4.5 W m−2 for the shortwave CRE). The C6 total CRE provides the closest match with the Clouds and the Earth's Radiant Energy System Energy Balanced And Filled product. Sensitivity studies are performed to estimate the impacts of different ice optical parameterization schemes and multilayer cloud overlap assumptions. Results show that the C6–C51 CRE differences are larger than the CRE variations caused by the other factors.

Comparing simulated PSC optical properties with CALIPSO observations during the 2010 Antarctic winter

AbstractWe simulate polar stratospheric clouds (PSCs) during the Antarctic winter of 2010 using the Specified Dynamics version of the Whole Atmosphere Community Climate Model/Community Aerosol and Radiation Model for Atmospheres (SD‐WACCM/CARMA) model. The current PSC model contains microphysical schemes for supercooled ternary solutions (STS) and nitric acid trihydrate (NAT) particles, as well as a prognostic treatment for PSC ice particles and dehydration. Our simulations and CALIPSO satellite data suggest two major NAT particle formation mechanisms. The first mechanism is the nucleation of NAT from STS. Our model, with homogeneous nucleation rates of NAT from STS constrained by observations from the Arctic winter of 2010–2011, reproduces optical properties observed by CALIPSO over Antarctica in May and the timing of denitrification observed by the Microwave Limb Sounder within their uncertainties. On the other hand, the CALIPSO data indicate that our simulations are missing clouds containing small NAT particles with large number densities. We suggest these particles are most likely to form from ice clouds or STS in gravity waves, as found by previous investigations. The simulated cloud coverage agrees with the CALIPSO cloud coverage within a few percent on average with a correlation coefficient of 0.83. However, using the CALIPSO classification algorithm, simulated ice clouds often fall into Mix categories under the denitrified and dehydrated conditions. The model needs an improved ice microphysical representation, not only to allow ice particles to be a source of NAT but also to provide information on ice cloud particle number and size so that ice cloud optical properties can be more precisely calculated for comparison with CALIPSO data.

Improved ice particle optical property simulations in the ultraviolet to far-infrared regime

To derive the bulk radiative properties of ice clouds, aircraft contrails and snow grains, which are fundamental to atmospheric radiative transfer calculations in downstream applications, it is necessary to accurately simulate the scattering of light by individual ice particles. An ice particle optical property database reported in 2013 (hereafter, TAMUice2013) is updated (hereafter, TAMUice2016) to incorporate recent advances in computation of the optical properties of nonspherical particles. Specifically, we employ the invariant imbedding T-matrix (II-TM) method to compute the optical properties of particles with small to moderate size parameters. Both versions use the Improved Geometric Optics Method (IGOM) to compute the optical properties of large ice crystals, but TAMUice2016 improves the treatment of inhomogeneous waves inside the scattering particles in the case where ice is absorptive such as at infrared wavelengths. To bridge the gap between the extinction efficiencies computed from the II-TM and the IGOM, TAMUice2016 includes spectrally dependent higher order terms of the edge effect in addition to the first order counterpart considered in TAMUice2013. Furthermore, the differences between TAMUice2013 and TAMUice2016 are quantified with respect to the computation of the bulk optical properties of ice clouds.

Improvements on the ice cloud modeling capabilities of the Community Radiative Transfer Model

AbstractNoticeable improvements on the ice cloud modeling capabilities of the Community Radiative Transfer Model (CRTM) are reported, which are based on the most recent advances in understanding ice cloud microphysical (particularly, ice particle habit/shape characteristics) and optical properties. The new CRTM ice cloud model is derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 ice cloud habit model, which represents ice particles as severely roughened hexagonal ice column aggregates with a gamma size distribution. The single‐scattering properties of the new ice particle model are derived from a state‐of‐the‐art ice optical property library and are constructed as look‐up tables for rapid CRTM computations. Various sensitivity studies concerning instrument‐specific applications and simulations are performed to validate CRTM against satellite observations. In particular, radiances in a spectral region covering the infrared wavelengths are simulated. Comparisons of brightness temperatures between CRTM simulations and observations (from MODIS, the Atmospheric Infrared Sounder, and the Advanced Microwave Sounding Unit) show that the new ice cloud optical property look‐up table substantially enhances the performance of the CRTM under ice cloud conditions.

The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua.

The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties (optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases-daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes collectively can result in significant changes relative to C5, though the magnitude depends on the dataset and the pixel's retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud optical property datasets, other MODIS cloud datasets are discussed when relevant.

Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission

Abstract. 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.

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

Abstract. Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (&lt; 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum, 5–15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single-habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.