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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

Platnick, S.↗
DOE OSTI2025

Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES

Satellite remote sensing retrievals of cloud effective radius (CER) are widely used for studies of aerosol–cloud interactions. Such retrievals, however, rely on forward radiative transfer (RT) calculations using simplified assumptions that can lead to retrieval errors when the real atmosphere deviates from the forward model. Here, coincident airborne remote sensing and in situ observations obtained during NASA's ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign are used to evaluate retrievals of CER for marine boundary layer stratocumulus clouds and to explore impacts of forward RT model assumptions and other confounding factors. Specifically, spectral CER retrievals from the Enhanced MODIS Airborne Simulator (eMAS) and the Research Scanning Polarimeter (RSP) are compared with polarimetric retrievals from RSP and with CER derived from droplet size distributions (DSDs) observed by the Phase Doppler Interferometer (PDI) and a combination of the Cloud and Aerosol Spectrometer (CAS) and the Two-Dimensional Stereo Probe (2D-S). The sensitivities of the eMAS and RSP spectral retrievals to assumptions about the DSD effective variance (CEV) and liquid water complex index of refraction are explored. CER and CEV inferred from eMAS spectral reflectance observations of the backscatter glory provide additional context for the spectral CER retrievals. The spectral and polarimetric CER retrieval agreement is case dependent, and updating the retrieval RT assumptions, including using RSP polarimetric CEV retrievals as a constraint, yields mixed results that are tied to differing sensitivities to vertical heterogeneity. Moreover, the in situ cloud probes, often used as the benchmark for remote sensing CER retrieval assessments, themselves do not agree, with PDI DSDs yielding CER values 1.3–1.6 µm larger than CAS and with CEV roughly 50 %–60 % smaller than CAS. Implications for the interpretation of spectral and polarimetric CER retrievals and their agreement are discussed.

Meyer, Kerry [NASA Goddard Space Flight Center (GS↗
DOE OSTI2021

Cloud optical depth and liquid effective radius retrievals from SPHOT zenith radiances

A new three-channel (440, 870, and 1640 nm) retrieval algorithm for cloud optical depth has recently been developed by Christine Chiu and her co-workers [Chiu et al., 2012]. This VAP is to implement the three-channel cloud optical depth retrieval algorithm as an ARM operational VAP. First, simultaneously retrieved cloud optical depth and effective radius datasets will be generated by using the pre-calibrated zenith radiance measurements taken from the ARM Sun-Photometer (SPHOT) and the NASA AERONET and Satellite-based surface albedo derived from MODSI. Finally, the algorithm produces uncertainties along with the retrieval products. This VAP outputs a daily NetCDF file.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Subpixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bispectral Method

The bispectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VIS/NIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring subpixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In the literature, the retrievals of τ and re are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on τ is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on re only by the subpixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of subpixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how subpixel cloud reflectance variations impact the τ and re retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from subpixel reflectance variations in operational satellite cloud products and to help understand the differences in τ and re retrievals between two instruments.

reflectance↗
NASA NTRS2017

A Framework for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method.

The so-called bi-spectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

reflectance↗
NASA NTRS2014

Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

Cloud physics↗
NASA NTRS2007

Retrievals and Comparisons of Various MODIS-Spectrum Inferred Water Cloud Droplet Effective Radii

Cloud droplet effective radius retrievals from different Aqua MODIS nearinfrared channels (2.1- micrometer, 3.7- micrometer, and 1.6- micrometer) show considerable differences even among most confident QC pixels. Both Collection 004 and Collection 005 MOD06 show smaller mean effective radii at 3.7- micrometer wavelength than at 2.1- micrometer and 1.6- micrometer wavelengths. Differences in effective radius retrievals between Collection 004 and Collection 005 may be affected by cloud top height/temperature differences, which mainly occur for optically thin clouds. Changes in cloud top height and temperature for thin clouds have different impacts on the effective radius retrievals from 2.1- micrometer, 3.7- micrometer, and 1.6- micrometer channels. Independent retrievals (this study) show, on average, more consistency in the three effective radius retrievals. This study is for Aqua MODIS only.

Fu-Lung, Chang↗
NASA NTRS2019

Retrieval of Liquid Water Cloud Properties from POLDER-3 Measurements Using a Neural Network Ensemble Approach

This paper describes a neural network algorithm for the estimation of liquid water cloud optical properties from the Polarization and Directionality of Earth's Reflectances-3 (POLDER-3) instrument aboard the Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The algorithm has been trained on synthetic multi-angle, multi-wavelength measurements of reflectance and polarization and has been applied to the processing of 1 year of POLDER-3 data. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) products show that the neural network algorithm has a low bias of around 2 in cloud optical thickness (COT) and between 1 and 2µm in the cloud effective radius. Comparisons with existing POLDER-3 datasets suggest that the proposed scheme may have enhanced capabilities for cloud effective radius retrieval, at least over land. An additional feature of the presented algorithm is that it provides COT and effective radius retrievals at the native POLDER-3 Level 1B pixel level.

Di Noia, Antonio↗
NASA NTRSDate not supplied

RSP Data Status, Updates and Plans from the Team

•All radiance (L1C), aerosol and cloud (L2) products are in the archive. •Revised calibration performed at GSFC in July 2021 applied to reprocessing. •Clouds have smaller drops and higher optical depths (larger droplet number concentrations) in winter than in summer. Cloud top droplet size distributions tend to be narrow with roughly 80% having an effective variance of less than 0.07. This is relevant to how well bulk auto-conversion parameterizations are likely to work at cloud top (order of magnitude effects) and also to assumptions used in the remote sensing of droplet number (~ 10% effect). Real refractive index and effective radius retrievals are consistent with hygroscopic growth of aerosols Real refractive index and effective variance retrievals imply the presence of an insoluble fraction of aerosols Future work on clouds will look at differences in cloud top drizzle formation and auto-conversion rates between the different campaigns and at how well mixed phase clouds can be detected (if at all) from sensors such as VIIRS and PACE OCI.

Research Scanning Polarimeter↗
NASA NTRS2011

An Assessment of Differences Between Cloud Effective Particle Radius Retrievals for Marine Water Clouds from Three MODIS Spectral Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product provides three separate 1 km resolution retrievals of cloud particle effective radii (r (sub e)), derived from 1.6, 2.1 and 3.7 micron band observations. In this study, differences among the three size retrievals for maritime water clouds (designated as r (sub e), 1.6 r (sub e), 2.1 and r (sub e),3.7) were systematically investigated through a series of case studies and global analyses. Substantial differences are found between r (sub e),3.7 and r (sub e),2.1 retrievals (delta r (sub e),3.7-2.l), with a strong dependence on cloud regime. The differences are typically small, within +/- 2 micron, over relatively spatially homogeneous coastal stratocumulus cloud regions. However, for trade wind cumulus regimes, r (sub e),3.7 was found to be substantially smaller than r (sub e),2.1, sometimes by more than 10 micron. The correlation of delta r(sub e),3.7-2.1 with key cloud parameters, including the cloud optical thickness (tau), r (sub e) and a cloud horizontal heterogeneity index (H-sigma) derived from 250 m resolution MODIS 0.86 micron band observations, were investigated using one month of MODIS Terra data. It was found that differences among the three r (sub e) retrievals for optically thin clouds (tau <5) are highly variable, ranging from - 15 micron to 10 micron, likely due to the large MODIS retrieval uncertainties when the cloud is thin. The delta r (sub e),3.7-2.1 exhibited a threshold-like dependence on both r (sub e),2.l and H-sigma. The re,3.7 is found to agree reasonably well with re,2.! when re,2.l is smaller than about 15J-Lm, but becomes increasingly smaller than re,2.1 once re,2.! exceeds this size. All three re retrievals showed little dependence when H-sigma < 0.3 (defined as standard deviation divided by the mean for the 250 m pixels within a 1 km pixel retrieval). However, for H-=sigma >0.3, both r (sub e),1.6 and r (sub e),2.1 were seen to increase quickly with H-sigma. On the other hand, r (sub e),3.7 statistics showed little dependence on H-sigma and remained relatively stable over the whole range of H-sigma values. Potential contributing causes to the substantial r (sub e),3.7 and r (sub e),2.1 differences are discussed. In particular, based on both 1-D and 3-D radiative transfer simulations, we have elucidated mechanisms by which cloud heterogeneity and 3-D radiative effects can cause large differences between r (sub e),3.7 and r (sub e),2.l retrievals for highly inhomogeneous clouds. Our results suggest that the contrast in observed delta r (sub e)3.7-2.1 between cloud regimes is correlated with increases in both cloud r (sub e) and H-sigma. We also speculate that in some highly inhomogeneous drizzling clouds, vertical structure induced by drizzle and 3-D radiative effects might operate together to cause dramatic differences between r (sub e),3.7 and r (sub e),2.1 retrievals.

Platnick, Steven↗
NASA NTRS2021

Joint cloud water path and rainwater path retrievals from airborne ORACLES observations

This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar – third generation (APR-3) passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ∼10 %–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two-thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g/sq. m and almost all CWPs (99 %) between 6 to 445 g/sq. m. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP), with more than 70 % of raining clouds having less than 10 g/sq. m of rainwater. In heavier warm rain (i.e., rain rate exceeding 40 mm/h or 1000 mm/d), however, RWP is observed to exceed 2500 g/sq. m. CWP (RWP) is found to be approximately 30 g/sq. m (7 g/sq. m) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud–precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

algorithm↗
NASA NTRS1999

A Solar Reflectance Method for Retrieving Cloud Optical Thickness and Droplet Size Over Snow and Ice Surfaces

Cloud optical thickness and effective radius retrievals from solar reflectance measurements are traditionally implemented using a combination of spectral channels that are absorbing and non-absorbing for water particles. Reflectances in non-absorbing channels (e.g., 0.67, 0.86, 1.2 micron spectral window bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2. 1, and 3.7 micron window bands) provide cloud particle size information. Cloud retrievals over ice and snow surfaces present serious difficulties. At the shorter wavelengths, ice is bright and highly variable, both characteristics acting to significantly increase cloud retrieval uncertainty. In contrast, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. A modification to the traditional cloud retrieval technique is devised. The new algorithm uses only a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 from May - June 1998 during the Arctic FIRE-ACE field deployment. Data from several coordinated ER-2 and University of Washington CV-580 in situ aircraft observations of liquid water stratus clouds are examined. MAS retrievals of optical thickness, droplet effective radius, and liquid water path are shown to be in good agreement with the in situ measurements. The initial success of the technique has implications for future operational satellite cloud retrieval algorithms in polar and wintertime regions.

Platnick, S.↗
NASA NTRS2009

Estimate of the Impact of Absorbing Aerosol Over Cloud on the MODIS Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path

Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the MODIS tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the average LWP difference and the estimated bias in MODIS cloud optical thickness attributable to the impact of overlaying biomass burning aerosol exceed the instantaneous uncertainty in the retrievals.

Wilcox, Eric M.↗
NASA NTRS2010

Effects of Ice Particle Size Vertical Inhomogeneity on the Passive Remote Sensing of Ice Clouds

The solar reflectance bi-spectral (SRBS) and infrared split-window (IRSpW) methods are two of the most popular techniques for passive ice cloud property retrievals from multispectral imagers. Ice clouds are usually assumed to be vertically homogeneous in global operational algorithms based on these methods, although significant vertical variations of ice particle size are typically observed in ice clouds. In this Study we investigate uncertainties in retrieved optical thickness, effective particle size, and ice water path introduced by a homogeneous cloud assumption in both the SRBS and IRSpW methods, and focus on whether the assumption can lead to significant discrepancies between the two methods. The study simulates the upwelling spectral radiance associated with vertically structured clouds and passes the results through representative SRBS and IRSpW retrieval algorithms. Cloud optical thickness is limited to values for which IRSpW retrievals are possible (optical thickness less than about 7). When the ice cloud is optically thin and yet has a significant ice particle size vertical variation, it is found that both methods tend to underestimate the effective radius and ice water path. The reason for the underestimation is the nonlinear dependence of ice particle scattering properties (extinction and single scattering albedo) on the effective radius. Because the nonlinearity effect is stronger in the IRSpW than the SRBS method, the IRSpW-based IWP tends to be smaller than the SRBS counterpart. When the ice cloud is moderately optically thick, the IRSpW method is relatively insensitive to cloud vertical structure and effective radius retrieval is weighted toward smaller ice particle size, while the weighting function makes the SRBS method more sensitive to the ice particle size in the upper portion of the cloud. As a result, when ice particle size increases monotonically toward cloud base, the two methods are in qualitative agreement; in the event that ice particle size decreases toward cloud base, the effective radius and ice water path retrievals based on the SRBS method are substantially larger than those from the IRSpW. The main findings of this Study Suggest that the homogenous cloud assumption can affect the SRBS and IRSpW methods to different extents and, consequently, can lead to significantly different retrievals. Therefore caution should be taken when comparing and combining the ice cloud property retrievals from these two methods.

Zhang, Zhibo↗
NASA NTRS2007

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

This study compares cirrus particle effective radius retrieved by a CALIPSO-like method with two similar methods using MODIS, MODI Airborne Simulator (MAS), and GOES imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-micrometer, 11.15-micrometer and 12.05-micrometer bands to infer the microphysical properties of cirrus clouds. The two other methods, sing passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the CERES team at LaRC (Langley Research Center) in support of CERES algorithms; the two algorithms will be referred to as MOD06- and LaRC-method, respectively. The three techniques are compared at two different latitudes: (i) the mid-latitude ice clouds study uses 18 days of observations at the Palaiseau ground-based site in France (SIRTA: Site Instrumental de Recherche par Teledetection Atmospherique) including a ground-based 532 nm lidar and the Moderate Resolution Imaging Spectrometer (MODIS) overpasses on the Terra Platform, (ii) the tropical ice clouds study uses 14 different flight legs of observations collected in Florida, during the intensive field experiment CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers-Florida Area Cirrus Experiment), including the airborne Cloud Physics Lidar (CPL) and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness, but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote-sensing method (CALIPSO-like) for the study of sub-visible ice clouds, in both mid-latitudes and tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds.

Chiriaco, M.↗
NASA NTRS2006

Impact of Three-Dimensional Radiative Effects on Satellite Retrievals of Cloud Droplet Sizes

There are several dozen papers that study the effects of cloud horizontal inhomogeneity on the retrievals of cloud optical thickness, but only a few of them deal with cloud droplet sizes. This paper is one of the first comprehensive attempts to fill this gap: It takes a close theoretical look at the radiative effects of cloud 3-D structure in retrievals of droplet effective radii. Under some general assumptions, it was found that ignoring subpixel (unresolved) variability produces a negative bias in the retrieved effective radius, while ignoring cloud inhomogeneity at scales larger than a pixel scale (resolved variability), on the contrary, leads to overestimation of the domain average droplet size. The theoretical results are illustrated with examples from Large Eddy Simulations (LES) of cumulus (Cu) and stratocumulus (Sc) cloud fields. The analysis of cloud drop size distributions retrieved from both LES fields confirms that ignoring shadowing in 1-D retrievals results in substantial overestimation of effective radii which is more pronounced for broken Cu than for Sc clouds. Collocated measurements of broken Cu clouds by Moderate Resolution Imaging Spectrometer (MODIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are used to check simulations and theory with observations. The analysis of ASTER and MODIS data and associated derived products recommends against blindly using retrieved effective radii for broken cloud fields, especially if one wants to relate aerosol amounts to cloud droplet sizes.

Marshak, Alexander↗
NASA NTRS1996

A Comparison of Cloud Microphysical and Optical Properties during TOGA-COARE

The impact of cirrus clouds on climate is an issue of research interest currently. Whether cirrus clouds heat or cool the Earth-atmosphere system depends on the cloud shortwave albedo and infrared reflectance and absorptance. These in turn are determined by the size distribution, phase, and composition of particles in the clouds. The TOGA-COARE campaign presented an excellent opportunity to study cirrus clouds and their influence on climate. In this campaign, a microphysics instrument package was flown aboard the DC-8 aircraft at medium altitudes in cirrus clouds. This package included a 2D Greyscale Cloud Particle Probe, a Forward Scattering Spectrometer Aerosol Probe, and an ice crystal replicator. At the same time the ER-2 equipped with a radiation measurement system flew coordinated flight tracks above the DC-8 at very high altitude. The radiation measurement made were short and long wave fluxes, as well as narrowband fluxes, both upwelling and downwelling. In addition LIDAR data is available. The existence of these data sets allows for a the comparison of radiation measurement with microphysical measurements. For example, the optical depth and effective radius retrieved from the ER-2 radiation measurements can be compared to the microphysical data. Conversely, the optical properties and fluxes produced by the clouds can be calculated from the microphysical measurements and compared to those measured aboard the ER-2. The assumptions required to make these comparisons are discussed. Typical microphysical results show a prevalence of micron-sized particles, in addition to the cloud particles that exceed 100 mm. The large number of small particles or "haze" cause the effective cloud radii to shift to smaller sizes, leading to changes in optical parameters.

Strawa, A. W.↗