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IRAS images of nearby dark clouds

We have investigated approximately 100 nearby molecular clouds using the extensive, all-sky database of IRAS. The clouds in this study cover a wide range of physical properties including visual extinction, size, mass, degree of isolation, homogeneity and morphology. IRAS 100 and 60 micron co-added images were used to calculate the 100 micron optical depth of dust in the clouds. These images of dust optical depth compare very well with (12)CO and (13)CO observations, and can be related to H2 column density. From the optical depth images we locate the edges of dark clouds and the dense cores inside them. We have identified a total of 43 `IRAS clouds' (regions with A(sub v) greater than 2) which contain a total of 255 `IRAS cores' (regions with A(sub v) greater than 4) and we catalog their physical properties. We find that the clouds are remarkably filamentary, and that the cores within the clouds are often distributed along the filaments. The largest cores are usually connected to other large cores by filaments. We have developed selection criteria to search the IRAS Point Source Catalog for stars that are likely to be associated with the clouds and we catalog the IRAS sources in each cloud or core. Optically visible stars associated with the clouds have been identified from the Herbig and Bell catalog. From these data we characterize the physical properties of the clouds including their star-formation efficiency.

Wood, Douglas O. S.↗

Comparison of cloud fields from atmospheric general circulation model, in situ and satellite measurements

This paper focuses on the comparison of cloud amounts derived from an atmospheric general circulation model (AGCM), Satellite-observed clouds, and Ground-based cloud observations. Unlike Earth Radiation Budget Experiment (ERBE)-type comparisons it does not mix potential errors in the cloud amount with those in the radiation code embedded in the model. Long term cloud climatologies were used to compare global cloud amounts and regional seasonal cycles. The AGCM successfully reproduced the signatures of the warm pool and North Pacific seasonal cycle cloudiness but failed in the low stratus region off the coast of South America, a known problem for AGCMs. The data sets also reproduced the anomaly signature associated with El Nino in the warm pool region, but the model amounts were lower. Global results had a similar success rate, with the model generally producing lower total cloud compared to the satellite and in situ measurements. To compare cloud vertical distributions the cloud height may need to be validated using the corresponding radiation fields. Unfortunately there were also some large discrepancies between the two observed cloud data sets. While tremendously improved over the last decade the character of the observed cloud data sets, must be substantially enhanced before they will be useful in validating AGCMs by any but the crudest levels of comparison.

Haskins, Robert D.↗

Global Survey of the Relationship Between Cloud Droplet Size and Albedo Using ISCCP

Aerosols affect climate through direct and indirect effects. The direct effect of aerosols (e.g., sulfates) includes reflection of sunlight back toward space and for some aerosols (e.g., smoke particles), absorption in the atmosphere; both effects cool the Earth's surface. The indirect effect of aerosols refers to the modification of cloud microphysical properties, thereby affecting the radiation balance. Higher concentrations of Cloud Condensation Nuclei (CCN) generally produce higher concentrations of cloud droplets, which are also usually assumed to lead to decreased cloud droplet sizes. The result is an increase in cloud albedo, producing a net radiative cooling, opposite to the warming caused by greenhouse gases (Charlson et al. 1992). The change in clouds that is directly induced by an increase of aerosol concentration is an increase of cloud droplet number density, N; but is is usually assumed that cloud droplet size decreases as if the water mass density Liquid Water Content (LWC) were constant. There is actually no reason why this should be the case. Shifting the cloud droplet size distribution to more numerous smaller droplets can change the relative rates of condensational and coalescence growth, leading to different LWC (e.g., Rossow 1978). Moreover, the resulting change in cloud albedo is usually ascribed to more efficient scattering by smaller droplets, when in fact it is the increase in droplet number density (assuming constant LWC) that produces the most important change in cloud albedo: e.g., holding N constant and decreasing the droplet size would actually decrease the scattering cross-section and, thus, the albedo much more than it is increased by the increased scattering efficiency.

Han, Qingyuan↗

The EOS CERES Global Cloud Mask

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Berendes, T. A.↗

Satellite Analyses of Cirrus Cloud Properties During the FIRE Phase 2 Cirrus Intensive Field Observations over Kansas

The First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Phase II Intensive Field Observations (IFO) were taken over southeastern Kansas between November 13 and December 7,1991, to determine cirrus cloud properties. The observations include in situ microphysical data; surface, aircraft, and satellite remote sensing; and measurements of divergence over meso- and smaller-scale areas using wind profilers. Satellite remote sensing of cloud characteristics is an essential aspect for understanding and predicting the role of clouds in climate variations. The objectives of the satellite cloud analysis during FIRE are to validate cloud property retrievals, develop advanced methods for extracting cloud information from satellite-measured radiances, and provide multiscale cloud data for cloud process studies and for verification of cloud generation models. This paper presents the initial results of cloud property analyses during FIRE-II using Geostationary Operational Environmental Satellite (GOES) data and NOAA Advanced Very High Resolution Radiometer (AVHRR) radiances.

Minnis, Patrick↗

A Simple Model of Cirrus Horizontal Inhomogeneity and Cloud Fraction

A simple model of horizontal inhomogeneity and cloud fraction in cirrus clouds has been formulated on the basis that all internal horizontal inhomogeneity in the ice mixing ratio is due to variations in the cloud depth, which are assumed to be Gaussian. The use of such a model was justified by the observed relationship between the normalized variability of the ice water mixing ratio (and extinction) and the normalized variability of cloud depth. Using radar cloud depth data as input, the model reproduced well the in-cloud ice water mixing ratio histograms obtained from horizontal runs during the FIRE2 cirrus campaign. For totally overcast cases the histograms were almost Gaussian, but changed as cloud fraction decreased to exponential distributions which peaked at the lowest nonzero ice value for cloud fractions below 90%. Cloud fractions predicted by the model were always within 28% of the observed value. The predicted average ice water mixing ratios were within 34% of the observed values. This model could be used in a GCM to produce the ice mixing ratio probability distribution function and to estimate cloud fraction. It only requires basic meteorological parameters, the depth of the saturated layer and the standard deviation of cloud depth as input.

Smith, Samantha A.↗

Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)

Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better understanding of the upscale cascade and suggesting new cloud-radiation parameterizations for climate models.

Cahalan, R. F.↗

The Role of Clear Sky Identification in the Study of Cloud Radiative Effects: Combine Analysis from ISCCP and the Scanner of Radiation Budget (ScaRaB)

Since the effect of clouds on the earth's radiation balance is often estimated as the difference of net radiative fluxes at the top of the atmosphere between all situations and monthly averaged clear sky situations of the same regions, a reliable identification of clear sky is important for the study of cloud radiative effects. The Scanner for Radiation Balance (ScaRaB) radiometer on board the Russian Meteor-3/7 satellite provided earth radiation budget observations from March 1994 to February 1995 with two ERBE-Re broad-band longwave and shortwave channels. Two narrow-band channels, in the infrared atmospheric window and in the visible band, have been added to the ScaRaB instrument to improve the cloud scene identification. The International Satellite Cloud Climatology Project (ISCCP) method for cloud detection and determination of cloud and surface properties uses the same narrow-band channels as ScaRaB, but is employed to a collection of measurements at a better spatial resolution of about 5 km. By applying the original ISCCP algorithms to the ScaRaB data, the clear sky frequency is about 5% lower than the one over quasi-simultaneous original ISCCP data, an indication that the ISCCP cloud detection is quite stable. However, one would expect an about 10 to 20% smaller clear sky occurrence over the larger ScaRaB pixels. Adapting the ISCCP algorithms to the reduced spatial resolution of 60 km and to the different time sampling of the ScaRaB data leads therefore to a reduction of a residual cloud contamination. A sensitivity study with time-space collocated ScaRaB and original ISCCP data at a spatial resolution of 1deg longitude x 1deg latitude shows that the effect of clear sky identification method plays a higher role on the clear sky frequency and therefore on the statistics than on the zonal mean values of the clear sky fluxes. Nevertheless, the zonal outgoing longwave fluxes corresponding to ERBE clear sky are in general about 2 to 10 W/sq m higher than those obtained from the ScaRaB adapted ISCCP clear sky identifications. The latter are close to (about 1 W/sq m higher) fluxes corresponding to clear sky regions from original ISCCP data, whereas ScaRaB clear sky LW fluxes obtained with the original ISCCP identification lie about 1 to 2 W/sq m below. Especially in the tropics where water vapor abundance is high, the ERBE clear sky LW fluxes seem to be systematically overestimated by about 4 W/sq m, and SW fluxes are lower by about 5 to 10 W/sq m. However, the uncertainty in the analysis of monthly mean zonal cloud radiative effects is also produced by the low frequency of clear sky occurrence, illustrated when averaging over pixels or even over regions of 4deg longitude x 5deg latitude, corresponding to the spatial resolution of General Circulation Models. The systematic bias in the clear sky fluxes is not reflected in the zonal cloud radiative effects, because the clear sky regions selected by the different algorithms can occur in different geographic regions with different cloud properties.

Rossow, W. B.↗

A 3-Year Climatology of Cloud and Radiative Properties Derived from GOES-8 Data Over the Southern Great Plains

While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.

Khaiyer, M. M.↗

Implications of the Observed Mesoscale Variations of Clouds for Earth's Radiation Budget

The effect of small-spatial-scale cloud variations on radiative transfer in cloudy atmospheres currently receives a lot of research attention, but the available studies are not very clear about which spatial scales are important and report a very large range of estimates of the magnitude of the effects. Also, there have been no systematic investigations of how to measure and represent these cloud variations. We exploit the cloud climatology produced by the International Satellite Cloud Climatology Project (ISCCP) to: (1) define and test different methods of representing cloud variation statistics, (2) investigate the range of spatial scales that should be included, (3) characterize cloud variations over a range of space and time scales covering mesoscale (30 - 300 km, 3-12 hr) into part of the lower part of the synoptic scale (300 - 3000 km, 1-30 days), (4) obtain a climatology of the optical thickness, emissivity and cloud top temperature variability of clouds that can be used in weather and climate GCMS, together with the parameterization proposed by Cairns et al. (1999), to account for the effects of small-scale cloud variations on radiative fluxes, and (5) evaluate the effect of observed cloud variations on Earth's radiation budget. These results lead to the formulation of a revised conceptual model of clouds for use in radiative transfer calculations in GCMS. The complete variability climatology can be obtained from the ISCCP Web site at http://isccp.giss.nasa.gov.

Rossow, William B.↗

A New "Cloud Mode" for the AERONET

A key to predicting climate change is to observe an understand the global distribution of clouds and their physical properties such as optical thickness and droplet size. Since clouds change rapidly over short time and space intervals, they are difficult to simulate in computer models. But it is essential that global climate models predict realistic spatial and temporal distribution of cloud optical depth. The best way to verify these distributions is to infer optical depth from global coverage satellite data. However, satellite methods have many sources of uncertainty; thus, independent and reliable ground-based estimates are essential for validation. For aerosol, there is the AERONET - a ground based monitoring network that consists of identical multi-channel radiometers for assessing aerosol optical properties and validating their satellite retrievals. In addition to AEROSOL, we want the network monitoring CLOUD optical properties. It will use AERONET "time" (inappropriate for aerosol studies) to make basic new measurements related to cloud physics. In the presentation we will report on a new technique that retrieves cloud optical thickness for even broken clouds above green vegetation from surface measurements of zenith radiance in the visible (VIS) and near-IR (NIR) spectral regions. The idea of the method is simple: since green vegetation reflects 40-50% of incoming radiation in the NIR and only 5-10% in the VIS region, ground measurements under thin clouds have little spectral contrast between VIS and NIR, while thick clouds reflect much more of the surface-reflected radiation in the NIR than in VIS. Based on this idea, we use a combination of measurements (spectral indices) in VIS and NIR to estimate cloud optical thickness. By analogy with NDVI, the simplest index that can be defined is the Normalized Difference Cloud Index (NDCI) which is a ratio between the difference and the sum of two radiances measured for two narrow spectral bands in VIS and NIR.

Marshak, Alexander↗

Ice Cloud Formation and Dehydration in the Tropical Tropopause Layer

Stratospheric water vapor is important not only for its greenhouse forcing, but also because it plays a significant role in stratospheric chemistry. several recent studies have focused on the potential for dehydration due to ice cloud formation in air rising slowly through the tropical tropopause layer. Holton and Gettelman showed that temperature variations associated with horizontal transport of air in the tropopause layer can drive ice cloud formation and dehydration, and Gettelman et al. recently examined the cloud formation and dehydration along kinematic trajectories using simple assumptions about the cloud properties. In this study, we use a Lagrangian, one-dimensional cloud model to further investigate cloud formation and dehydration as air is transported horizontally and vertically through the tropical tropopause layer. Time-height curtains of temperature are extracted from meteorological analyses. The model tracks the growth and sedimentation of individual cloud particles. The regional distribution of clouds simulated in the model is comparable to the subvisible cirrus distribution indicated by SAGE II. The simulated cloud properties depend strongly on the assumed ice supersaturation threshold for ice nucleation. with effective nuclei present (low supersaturation threshold), ice number densities are high (0.1--10 cm(circumflex)-3), and ice crystals do not grow large enough to fall very far, resulting in limited dehydration. With higher supersaturation thresholds, ice number densities are much lower (less than 0.01 cm(circumflex)-3), and ice crystals grow large enough to fall substantially; however, supersaturated air often crosses the tropopause without cloud formation. The clouds typically do not dehydrate the air along trajectories down to the temperature minimum saturation mixing ratio. Rather the water vapor mixing ratio crossing the tropopause along trajectories is typically 10-50% larger than the saturation mixing ratio.

Jensen, Eric↗

Observations and Parameterizations of Particle Size Distributions in Deep Tropical Cirrus and Stratiform Precipitation Clouds: Results from In-Situ Observations in TRMM Field Campaigns

In this study, we report on the evolution of particle size distributions (PSDs) and habits as measured during slow, Lagrangian-type spiral descents through deep subtropical and tropical cloud layers in Florida, Brazil, and Kwajalein, Marshall Islands, most of which were precipitating. The objective of the flight patterns was to learn more about how the PSDs evolved in the vertical and to obtain information of the vertical structure of microphysical properties. New instrumentation yielding better information on the concentrations of particles in the size (D) range between 0.2 and 2 cm, as well as improved particle imagery, produced more comprehensive observations for tropical stratiform precipitation regions and anvils than have been available previously. Collocated radar observations provided additional information on the vertical structure of the cloud layers sampled. Most of the spirals began at cloud top, with temperatures (T) as low as -50 C, and ended at cloud base or below the melting layer (ML). The PSDs broadened from cloud top towards cloud base, with the largest particles increasing in size from several millimeters at cloud top to one centimeter or larger towards cloud base. Some continued growth was noted in the upper part of the ML. Concentrations of particles less than 1 mm in size decreased with decreasing height. The result was a consistent change in the PSDs in the vertical. Similarly, systematic changes in the size dependence of the particle cross-sectional area was noted with decreasing height. Aggregation-as ascertained from both the changes in the PSDs and evolution of particle habits as observed in high detail with the cloud particle imager (CPI) probe-was responsible for these trends. The PSDs were generally well-represented by gamma distributions of the form N = N0 gamma D microns e- lambda gamma D that were fitted to the PSDs over 1-km horizontal intervals throughout the spirals. The intercept (N0 gamma), slope (lambda gamma), and dispersion (microns) values were derived for each PSD. Exponential curves (N = N0e- lambdaD; micron = 0) were also fitted to the distributions. The lambda gamma values for given spirals varied systematically with temperature as did the values of lambda (exponential), and the data generally conformed to values found in previous studies involving exponential fits to size distributions in mid-latitude frontal and cirrus layers. Considerable variability often noted in the PSD properties during the loops of individual spirals was manifested primarily in large changes in N0 gamma and N0, but micron, lambda gamma and lambda remained fairly stable. Temperature is not found to be the sole factor controlling lambda gamma or lambda but is a primary one. Direct relationships were found between lambda gamma and N0 gamma or lambda gamma and micron for the gamma distributions and lambda and N0 for the exponential. The latter relationship was not found as distinctly in earlier studies; observed PSDs in this study had better fidelity with less scatter. The micron values changed monotonically with T over the range of temperatures and were directly related to N0 gamma or lambda gamma, thereby reducing the number of variables in the PSD functional equation to two. In the upper part of the ML, N0 and lambda continued to decrease, and in the lower part these values began to increase as the largest particles melted. We developed general expressions relating various bulk microphysical, radar, and radiative transfer-related variables to N0 gamma and lambda gamma, useful for both tropical and mid-latitude clouds. These relationships facilitate the specification of a number of bulk properties in cloud and climate models. The results presented in this paper apply best to temperatures between 0 and -40 C, for which the measured radar reflectivities fall in the range of 0 to 25 dBZe.

Heymsfield, Andrew J.↗

Cloud Thickness from Offbeam Returns - Thor Lidar

Physical thickness of a cloud layer, and sometimes multiple cloud layers, can be estimated from the time delay of off-beam returns from a pulsed laser source illuminating one side of the cloud layer. In particular, the time delay of light returning from the outer diffuse halo of light surrounding the beam entry point, relative to the time delay at beam center, determines the cloud physical thickness. The delay combined with the pulse stretch gives the optical thickness. The halo method works best for thick cloud layers, typically optical thickness exceeding 2, and thus compliments conventional lidar which cannot penetrate thick clouds. Cloud layer top and base have been measured independently over the ARM/SGP site using conventional laser ranging (lidar) and the top minus base thickness are compared with a cloud top halo estimate obtained from the NASA/Goddard THOR System (THOR = THickness from Offbeam Returns). THOR flies on the NASA P3, and measures the halo timings from several km above cloud top, at the same time providing conventional lidar cloud top height. The ARM/SGP micropulse lidar provides cloud base height for validation.

Cahalan, R.↗

Impact of MIE-Resonances on the Atmospheric Absorption of Water Clouds

Clouds strongly modulate radiative transfer processes in the Earth's atmosphere. Studies, which simulate bulk properties of clouds, such as absorption, require methods that accurately account for multiple scattering among individual cloud particles. Multiple scattering processes are well described by MIE-theory, if interacting particles have a spherical shape. This is a good assumption for water droplets. Thus, simulations for water clouds (especially for interactions with solar radiation) usually apply readily available MIE-codes. The presence of different drop-sizes, however, necessitates repetitive calculations for many sizes. The usual representation by a few sizes is likely to miss contributions from densely distributed, sharp resonances. Despite their usually narrow width, integrated over the entire size-spectrum of a cloud droplet distribution, the impact of missed resonances could add up. The consideration of these resonances tends to increase cloud extinction and cloud absorption. This mechanism for a larger (than by MIE-methods predicted) solar absorption has the potential to explain observational evidence of larger than predicted cloud absorption at solar wavelengths. The presentation will address the absorption impact of added resonances for typical properties of water clouds (e.g. drop size distributions, drop concentrations and cloud geometry). Special attention will be given to scenarios with observational evidence of law than simulated solar absorption; particularly if simultaneous measurements of cloud micro- and macrophysical properties are available.

Wiscombe, W.↗

Precipitation Processes developed during ARM (1997), TOGA COARE(1992), GATE(1 974), SCSMEX(1998) and KWAJEX(1999): Consistent 2D and 3D Cloud Resolving Model Simulations

Real clouds and clouds systems are inherently three dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud system with large horizontal domains at the National Center for Atmospheric Research. The results indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D simulations of these same cases. The reason for the strong similarity between the 2D and 3D CRM simulations is that the observed large-scale advective tendencies of potential temperature, water vapor mixing ratio, and horizontal momentum were used as the main forcing in both the 2D and 3D models. Interestingly, the 2D and 3D versions of the CRM used in CSU and U.K. Met Office showed significant differences in the rainfall and cloud statistics for three ARM cases. The major objectives of this project are to calculate and axamine: (1)the surface energy and water budgets, (2) the precipitation processes in the convective and stratiform regions, (3) the cloud upward and downward mass fluxes in the convective and stratiform regions; (4) cloud characteristics such as size, updraft intensity and lifetime, and (5) the entrainment and detrainment rates associated with clouds and cloud systems that developed in TOGA COARE, GATE, SCSMEX, ARM and KWAJEX. Of special note is that the analyzed (model generated) data sets are all produced by the same current version of the GCE model, i.e. consistent model physics and configurations. Trajectory analyse and inert tracer calculation will be conducted to identify the differences and similarities in the organization of convection between simulated 2D and 3D cloud systems.

Tao, W.-K.↗

Inferring Cloud Properties from Passive Solar Sensors

The most common approach for retrieving cloud optical depth from ground-based observations uses downwelling fluxes measured by pyranometers and Multi-Filter Rotating Shadowband Radiometers (MFRSR). The key element in both retrieval techniques is the one-to-one mapping of the "observed" fluxes into cloud optical depth through plane-parallel radiative transfer. Both methods are expected to work well only for completely overcast clouds giving an effective optical depth for the whole sky. To infer cloud optical depth locally one can assume to use a narrow-field-of view radiometer that measures radiances instead of fluxes. However, lack of one-to-one relationships between radiance and cloud optical depth, prevents the direct use of radiances either. Here we discuss a new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (NIR) spectral regions. In addition to an algebraic combinations of spectral radiances such as Normalized Difference Cloud Index (NDCI) that largely removes nonuniqueness and the radiative effects of cloud inhomogeneity but can result in poor retrievals due to its insensitivity to cloud fraction, both RED and NIR radiances as points on the "RED vs. NIR" plane are proposed to be used for retrieval. The proposed retrieval method is applied to a multi- channel sunphotometer (as a part of AERONET) measurements at the ARM site in Oklahoma. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and MFRSR. In addition to cloud optical depth, the new retrieval method also infers a "radiatively effective" cloud fraction.

Marshak, A.↗

Independent Pixel and Two Dimensional Estimates of LANDSAT-Derived Cloud Field Albedo

A theoretical study has been conducted on the effects of cloud horizontal inhomogeneity on cloud albedo bias. A two-dimensional (2D) version of the Spherical Harmonic Discrete Ordinate Method (SHDOM) is used to estimate the albedo bias of the plane parallel (PP-IPA) and independent pixel (IPA-2D) approximations for a wide range of 2D cloud fields obtained from LANDSAT. They include single layer trade cumulus, open and closed cell broken stratocumulus, and solid stratocumulus boundary layer cloud fields over ocean. Findings are presented on a variety of averaging scales and are summarized as a function of cloud fraction, mean cloud optical depth, cloud aspect ratio, standard deviation of optical depth, and the gamma function parameter Y (a measure of the width of the optical depth distribution). Biases are found to be small for small cloud fraction or mean optical depth, where the cloud fields under study behave linearly. They are large (up to 0.20 for PP-IPA bias, -0.12 for IPA-2D bias) for large v. On a scene average basis PP-IPA bias can reach 0.30, while IPA-2D bias reaches its largest magnitude at -0.07. Biases due to horizontal transport (IPA-2D) are much smaller than PP-IPA biases but account for 20% RMS of the bias overall. Limitations of this work include the particular cloud field set used, assumptions of conservative scattering, constant cloud droplet size, no gas absorption or surface reflectance, and restriction to 2D radiative transport. The LANDSAT data used may also be affected by radiative smoothing.

Chambers, L. H.↗