Retrieval of Aerosol Optical Depth Above Clouds from OMI Observations: Sensitivity Analysis, Case Studies

A large fraction of the atmospheric aerosol load reaching the free troposphere is frequently located above low clouds. Most commonly observed aerosols above clouds are carbonaceous particles generally associated with biomass burning and boreal forest fires, and mineral aerosols originated in arid and semi-arid regions and transported across large distances, often above clouds. Because these aerosols absorb solar radiation, their role in the radiative transfer balance of the earth atmosphere system is especially important. The generally negative (cooling) top of the atmosphere direct effect of absorbing aerosols, may turn into warming when the light-absorbing particles are located above clouds. The actual effect depends on the aerosol load and the single scattering albedo, and on the geometric cloud fraction. In spite of its potential significance, the role of aerosols above clouds is not adequately accounted for in the assessment of aerosol radiative forcing effects due to the lack of measurements. In this paper we discuss the basis of a simple technique that uses near-UV observations to simultaneously derive the optical depth of both the aerosol layer and the underlying cloud for overcast conditions. The two-parameter retrieval method described here makes use of the UV aerosol index and reflectance measurements at 388 nm. A detailed sensitivity analysis indicates that the measured radiances depend mainly on the aerosol absorption exponent and aerosol-cloud separation. The technique was applied to above-cloud aerosol events over the Southern Atlantic Ocean yielding realistic results as indicated by indirect evaluation methods. An error analysis indicates that for typical overcast cloudy conditions and aerosol loads, the aerosol optical depth can be retrieved with an accuracy of approximately 54% whereas the cloud optical depth can be derived within 17% of the true value

Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 3 details the advanced CERES methods for performing scene identification and inverting each CERES scanner radiance to a top-of-the-atmosphere (TOA) flux. CERES determines cloud fraction, height, phase, effective particle size, layering, and thickness from high-resolution, multispectral imager data. CERES derives cloud properties for each pixel of the Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and the Earth Observing System (EOS) moderate-resolution imaging spectroradiometer. Cloud properties for each imager pixel are convolved with the CERES footprint point spread function to produce average cloud properties for each CERES scanner radiance. The mean cloud properties are used to determine an angular distribution model (ADM) to convert each CERES radiance to a TOA flux. The TOA fluxes are used in simple parameterization to derive surface radiative fluxes. This state-of-the-art cloud-radiation product will be used to substantially improve our understanding of the complex relationship between clouds and the radiation budget of the Earth-atmosphere system

Biases in droplet radii and optical depths of marine stratocumulus retrieved from MODIS imagery

The 2007 Intergovernmental Panel on Climate Change assessment established that the effect of clouds on climate contributes the largest uncertainty in predicting the future climate. Satellite observations provide an opportunity for learning about the behavior of clouds. This thesis seeks to assess the accuracy of cloud properties retrieved from multispectral satellite imagery and test the usefulness of satellite data in verifying conclusions based on aircraft observations that marine stratus appear to be formed through the nearly adiabatic ascent of moist air. Retrievals of cloud optical depth, a measure of cloud thickness, using 0.64-μm reflectances and droplet radii using separately 1.6, 2.1, and 3.7-μm reflectances were obtained with the MODerateresolution Imaging Spectroradiometer (MODIS). Owing to different amounts of absorption by liquid water in the near infrared, with the least at 1.6 μm and the most at 3.7 μm, the growth of droplet radius with cloud thickness should result in the largest droplet radii retrieved using the 3.7-μm reflectances and the smallest using 1.6-μm reflectances. Droplet radii retrieved using the 2.1-μm reflectances, however, are often the largest, and those retrieved using 3.7-μm reflectances are often the smallest. In addition aircraft observations indicate that the relationships between droplet radius, re, and optical depth, t, d ln r / d lnt e ,should be approximately equal to 0.2 for marine stratocumulus. While satellite observations in optically thick, overcast regions yielded d ln re/d ln t consistent with this result, retrievals for regions with broken clouds often yielded d ln r / d lnt e substantially smaller than 0.2. Clouds often exhibit large horizontal and vertical variability. In this thesis a simple radiative transfer model was used to predict reflectances at visible and near infrared wavelengths for clouds formed through the adiabatic ascent of moist air, and then a retrieval scheme based on vertically uniform clouds was used to determine if the departures from the behavior expected for adiabatic clouds might be caused by the assumption of spatial uniformity used in the retrievals. The simulations indicated that at all cloud thicknesses the progression of droplet size using 1.6, 2.1, and 3.7-μm reflectances followed that suggested by the absorptive properties of liquid water. The simulation also indicated, however, contrary to the observations, that when the clouds were optically thin, d ln r / d lnt e should be greater than 0.2, the value expected for the adiabatic ascent of moist air. The simulation was adapted to account for the effects of horizontal variations within clouds. Each 1-km pixel was given a subpixel distribution of optical depths based on a gamma distribution with mean taken from MODIS pixel-scale optical depths and variance given by Kato et al. (2006), obtained from Large Eddy Simulations of marine stratocumulus. Each subpixel was allowed to develop vertically following the adiabatic ascent of moist air. The average of the reflectances for the subpixels was used to retrieve the cloud properties for the pixels, and these properties were compared with the average properties of the subpixels. The retrievals obtained using 1.6-μm reflectances were most strongly affected by the addition of subpixel variations in optical depth and droplet radius. Mean droplet radius retrieved in the simulation was largest when using 1.6-μm reflectances, followed by that retrieved using 2.1 and 3.7-μm reflectances. The simulation of large droplet radii at the shorter wavelengths indicated that the large droplets observed in MODIS may result from horizontal variations within the 1-km MODIS pixel. The values of d ln r / d lnt e calculated for horizontally heterogeneous clouds were close to 0.2, but showed variations that extend both above and below this value, consistent with the MODIS observations. To illustrate the findings based on the simulations, visible optical depth and droplet radius were retrieved for MODIS 500-m pixels overcast by marine stratocumulus. The 500-m pixels were used to represent the subpixel variability within 2-km pixels constructed from the 500-m pixels. Differences between cloud properties retrieved using average radiances and averages of the subpixel properties were compared for overcast and broken-cloud regions using both MODIS and the Partly Cloudy Pixel Retrieval (PCPR) schemes for identifying the overcast 2-km pixels. In the regions overcast by optically thick marine stratocumulus, both methods of identifying overcast pixels led to small biases in the retrieved droplet radii and optical depths. Values of d ln r / d lnt e obtained in the overcast regions using the PCPR identifications were closer to the value of 0.2 expected for adiabatic clouds than those obtained using MODIS identifications. Additionally, values of d ln r / d lnt e calculated using the 500-m overcast pixels yielded better results than those calculated using the 2-km pixels. In regions containing broken clouds, the PCPR identification provided a smaller bias than the MODIS identification, however both methods showed greater biases than those calculated for regions overcast by optically thick marine stratocumulus. Values of d ln r / d lnt e for the regions containing broken clouds showed a positive value when using the PCPR scheme to identify overcast pixels, and a negative value when using the MODIS cloud mask to identify overcast pixels. Consistent with the results from the overcast regions, the d ln r / d lnt e obtained for the 500-m overcast pixels were in closer conformity with adiabatic clouds than the values obtained for the 2-km pixels using both the MODIS and PCPR identifications

Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment

The Along-Track Scanning Radiometers (ATSRs) provide a long time-series of measurements suitable for the retrieval of cloud properties. This work evaluates the freely-available Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) dataset (version 3) created from the ATSR-2 (1995�2003) and Advanced ATSR (AATSR; 2002 onwards) records. Users are recommended to consider only retrievals flagged as high-quality, where there is a good consistency between the measurements and the retrieved state (corresponding to about 60% of converged retrievals over sea, and more than 80% over land). Cloud properties are found to be generally free of any significant spurious trends relating to satellite zenith angle. Estimates of the random error on retrieved cloud properties are suggested to be generally appropriate for optically-thick clouds, and up to a factor of two too small for optically-thin cases. The correspondence between ATSR-2 and AATSR cloud properties is high, but a relative calibration difference between the sensors of order 5�10% at 660 nm and 870 nm limits the potential of the current version of the dataset for trend analysis. As ATSR-2 is thought to have the better absolute calibration, the discussion focusses on this portion of the record. Cloud-top heights from GRAPE compare well to ground-based data at four sites, particularly for shallow clouds. Clouds forming in boundary-layer inversions are typically around 1 km too high in GRAPE due to poorly-resolved inversions in the modelled temperature profiles used. Global cloud fields are compared to satellite products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements, and a climatology of liquid water content derived from satellite microwave radiometers. In all cases the main reasons for differences are linked to differing sensitivity to, and treatment of, multi-layer cloud systems. The correlation coefficient between GRAPE and the two MODIS products considered is generally high (greater than 0.7 for most cloud properties), except for liquid and ice cloud effective radius, which also show biases between the datasets. For liquid clouds, part of the difference is linked to choice of wavelengths used in the retrieval. Total cloud cover is slightly lower in GRAPE (0.64) than the CALIOP dataset (0.66). GRAPE underestimates liquid cloud water path relative to microwave radiometers by up to 100 g m�2 near the Equator and overestimates by around 50 g m�2 in the storm tracks. Finally, potential future improvements to the algorithm are outlined

Evaluating The Impact Of Above-Cloud Aerosols On Cloud Optical Depth Retrievals From Modis

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (visible and shortwave infrared), the impacts of above-cloud absorbing aerosols on the standard COD retrievals are evaluated. For fine-mode aerosol particles, aerosol optical depth (AOD) values diminish sharply from the visible to the shortwave infrared channels. Thus, a suppressed above-cloud particle radiance aliasing effect occurs for COD retrievals using shortwave infrared channels. Aerosol Index (AI) from the spatially and temporally collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African sub-continent. MODIS and OMI Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to constrain cloud phase and provide contextual above-cloud AOD values. The frequency of occurrence of above-cloud aerosols is depicted on a global scale for the spring and summer seasons from OMI and CALIOP, thus indicating the significance of the problem. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10–20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1.0. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS visible and shortwave in channels are vulnerable to dust particle aliasing, and thus a COD impact cannot be isolated with this method. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above–cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS shortwave infrared COD products

Studying Clouds and Aerosols with Lidar Depolarization Ratio and Backscatter Relationships

This dissertation consists of three parts, each devoted to a particular issue of significant importance for CALIPSO lidar observation of depolarization ratio (delta) and backscatter (gamma?) to improve current understanding of the microphysical properties of clouds and aerosols. The relationships between depolarization ratio and backscatter allow us to retrieve particle thermodynamic phase and shape and/or orientation of aerosols and clouds. The first part is devoted to the investigation of the relationships between lidar backscatter and the corresponding depolarization ratio for different cloud classifications and aerosol types. For each cloud and aerosol types, layer-averaged backscatter and backscattering depolarization ratio from the CALIPSO measurements are discussed. The present results demonstrate the unique capabilities of the CALIPSO lidar instrument for determining cloud phase and aerosols subtypes. In the second part, we evaluate the MODIS IR cloud phase with the CALIPSO cloud products. The three possible misclassifications of MODIS IR cloud phasealgorithm, which are studied by Nasiri and Kahn (2008) with radiative transfer modeling, are tested by comparing between MODIS IR phase and CALIOP observations. The current results support their hypotheses, which is that the MODIS phase algorithm may tend to classify thin cirrus clouds as water clouds or mixed phase clouds or unknown, and classify midlevel and/or mid-temperature clouds as mixed or unknown phase. In the third part, we present a comparison of mineral dust aerosol retrievals from two instruments, MODIS and CALIPSO lidar. And, we implement and evaluate a new mineral dust detection algorithm based on the analysis of thin dust radiative signature. In comparison, three commonly used visible and IR mineral dust detection algorithms, including BTD procedure, D parameter method, and multi-channel image algorithm, are evaluated with CALIPSO aerosol classification. The comparison reveals that those dust detection algorithms are not effective for optically thin dust layers, but for thick dust storm. The new algorithm using discriminant analysis with CALIPSO observation is much better in detecting thin dust layer of optical thickness between 0.1 and 2

Final report on studies of space/time variability of marine boundary layer characteristics

August 1990.Appendix A originally presented as Melanie A. Wetzel's dissertation (Colorado State University, 1990) under the title: Investigation of a remote sensing technique for droplet-effective radius.Includes bibliographical references.ONR Contract no. N00014-86-C-0459