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Microphysical schemes based on the scaling normalization of the particle size distribution (PSD) are cast into a variational data assimilation method to assess their ability to retrieve the precipitation structure and humidity from moments of the PSD that can be derived from radar- and ground-based disdrometer measurements. The sedimentation and evaporation, which are the main processes below the cloud base, are examined. Various identical twin experiments are presented in the context of a column time-dependent model used to simulate the passage of precipitating cells over a short period of time. The relative humidity profile is assumed constant. The feedback of the microphysical processes on the thermodynamic fields is ignored. Observations are generated from a three-moment scheme having the zeroth, third, and sixth moments of the PSD as prognostic variables. The model is discretized in terms of the logarithms of the predictive moments, which render the adjustment of the model variables easier to the observations. An upper bound for the characteristic diameter for the sixth moment is however necessary to prevent numerical instabilities from developing during the data assimilation process. The tangent linear model of the three-moment scheme reproduces well the difference between two nonlinear integrations over the assimilation window (8 min), which validates the use of its adjoint in the minimization of the cost function that measures the misfit between observations and corresponding model variables. A weak smoothness penalty function should be added to the cost function when noisy observations are assimilated. When all the predicted moments are observed and assimilated, the minimization converges very well, even with 40% observation error. In this case, the reflectivity factor, which is related to the sixth moment, can be retrieved with 0.2-dB accuracy. When only the sixth moment is observed, the total number of concentration (related to the zeroth moment) cannot be recovered. However, the constant relative humidity can be obtained with 1% accuracy. When simpler one-moment and two-moment schemes are used to retrieve the precipitation structure from the observed sixth moment, the model error strongly projects on the nonobserved moments of the PSD.

This study examines the development of bulk single-scattering properties of ice clouds, including single-scattering albedo, asymmetry factor, and phase function, for a set of 1117 particle size distributions obtained from analysis of the First International Satellite Cloud Climatology Project Regional Experiment (FIRE)-I, FIRE-II, Atmospheric Radiation Measurement Program intensive observation period, Tropical Rainfall Measuring Mission Kwajalein Experiment (KWAJEX), and the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) data. The primary focus is to develop band-averaged models appropriate for use by the Moderate Resolution Imaging Spectroradiometer (MODIS) imager on the Earth Observing System Terra and Aqua platforms, specifically for bands located at wavelengths of 0.65, 1.64, 2.13, and 3.75 [micro]m. The results indicate that there are substantial differences in the bulk scattering properties of ice clouds formed in areas of deep convection and those that exist in areas of much lower updraft velocities. Band-averaged bulk scattering property results obtained from a particle-size-dependent mixture of ice crystal habits are compared with those obtained assuming only solid hexagonal columns. The single-scattering albedo is lower for hexagonal columns than for a habit mixture for the 1.64-, 2.13-, and 3.75-[micro]m bands, with the differences increasing with wavelength. In contrast, the asymmetry factors obtained from the habit mixture and only the solid hexagonal column are most different at 0.65 [micro]m, with the differences decreasing as wavelength increases. At 3.75 [micro]m, the asymmetry factor results from the two habit assumptions are almost indistinguishable. The asymmetry factor, single-scattering albedo, and scattering phase functions are also compared with the MODIS version-1 (V1) models. Differences between the current and V1 models can be traced to the microphysical models and specifically to the number of both the smallest and the largest particles assumed in the size distributions.

The spectral-difference algorithm of Barker and Marshak for inferring optical depth [tau] of broken clouds has been shown numerically to be potentially useful. Their method estimates cloud-base reflectance and [tau] using spectral radiometric measurements made at the surface at two judiciously chosen wavelengths. Here it is subject to sensitivity tests that address the impacts of two ubiquitous sources of potential error: instrument noise and presence of aerosol. Experiments are conducted using a Monte Carlo photon transport model, cloud-resolving model data, and surface albedo data from satellite observations. The objective is to analyze the consistency between inherent and retrieved values of v. Increasing instrument noise, especially if uncorrelated at both wavelengths, decreases retrieved cloud fraction and increases retrieved mean [tau]. As with all methods that seek to infer [tau] using passive radiometry, the presence of aerosol requires that threshold values be set in order to discriminate between cloudy and cloud-free columns. A technique for estimating thresholds for cloudy columns is discussed and demonstrated. Finally, it was found that surface type and mean inherent [tau] play major roles in defining retrieval accuracy.

A new approach to retrieve microphysical properties from mixed-phase Arctic clouds is presented. This mixed-phase cloud property retrieval algorithm (MIXCRA) retrieves cloud optical depth, ice fraction, and the effective radius of the water and ice particles from ground-based, high-resolution infrared radiance and lidar cloud boundary observations. The theoretical basis for this technique is that the absorption coefficient of ice is greater than that of liquid water from 10 to 13 [micro]m, whereas liquid water is more absorbing than ice from 16 to 25 txm. MIXCRA retrievals are only valid for optically thin ([[tau].sub.visible]

This paper is devoted to the application of the Semi-Analytical Cloud Retrieval Algorithm (SACURA) to the cloud-top height determination using data from the Global Ozone Measurement Experiment (GOME) instrument onboard Earth Remote Sensing satellite (ERS-2). In particular, measurements of the top-of-atmosphere reflectance in the oxygen absorption A-band are used. The technique is based on the asymptotic radiative transfer theory as applied to studies of the oxygen absorption bands in reflected light. Our approach is valid for optically thick clouds with cloud optical thickness larger than approximately 5. The accuracy of the algorithm is checked against independent retrieval techniques for completely cloudy pixels. In particular, the close coincidence with data obtained from the Along Track Scanning Radiometer (ATSR-2) onboard ERS-2 is found. Some results of retrievals using these different instruments disagree (up to 2 km). This is explained by the strong horizontal inhomogeneity of clouds under investigation, which is not accounted by the SACURA or, possibly, by well-known problems of infrared techniques as applied to low-level clouds. The effective cloud geometrical thickness l is also retrieved. This parameter is defined as the geometrical thickness of a vertically homogeneous cloud, which allows for the minimization of differences between observed and calculated top-of-atmosphere reflectance spectra. For inhomogeneous clouds, the value of l differs from a real cloud geometrical thickness, but it gives us an indication of the possible existence of the multilayered cloud system in the field of view of the optical instrument. Index Terms--Clouds, radiative transfer, remote sensing, spectroscopy.

Here, previous work using photon diffusion theory to describe radiative transfer through dense plane-parallel clouds at nonabsorbing wavelengths is extended. The focus is on the scaling of space- and time-domain moments for transmitted light with respect to cloud thickness H and optical depth [tau]; and the new results are as follows: accurate prefactors for asymptotic scaling, preasymptotic correction terms in closed form, 3D effects for internal variability in [tau], and the rms transit time or pathlength. Mean pathlength is [alpha]H for dimensional reasons and, from random-walk theory, we already know that it is also [alpha](1 - g)[tau] for large enough [tau] (g being the asymmetry factor). Here, it is shown that the prefactor is precisely 1/2 and that corrections are significant for (1 - g)[tau] < 10, which includes most actual boundary layer clouds. It is also shown that rms pathlength is not much larger than the mean for transmittance (its prefactor is [square root of 7/20] [approximately equal to 0.59]); this proves that, in sharp contrast with reflection, pathlength distributions are quite narrow in transmission. If the light originates from a steady point source on a cloud boundary, a fuzzy spot is observed on the opposite boundary. This problem is formally mapped to the pulsed source problem, and it is shown that the rms radius of this spot slowly approaches [square root of 2/3H] as [tau] increases; it is also shown that the transmitted spot shape has a flat top and an exponential tail. Because all preasymptotic corrections are computed here, the diffusion results are accurate when compared to Monte Carlo counterparts for [tau] [greater than or equal to] 5, whereas the classic scaling relations apply only for [tau] [greater than or equal to] 70, assuming g = 0.85. The temporal quantities shed light on observed absorption properties and optical lightning waveforms. The spatial quantity controls the three-dimensional radiative smoothing process in transmission, which was recently observed in spectral analyses of time series of zenith radiance at 725 nm. Opportunities in ground-based cloud remote sensing using the new developments are described and illustrated with simulations of 3D solar radiative transfer in realistic models of stratocumulus. Finally, since this analytical diffusion study applies only to weakly variable stratus layers, extensions to more complex cloud systems using anomalous diffusion theory are discussed.

Significant enhancements in humidity around cumulus clouds, that is, the 'cloud halos' observed in many aircraft penetrations, are simulated using a three-dimensional dynamic model. Five case studies show that humidity halos occur mainly near lateral cloud boundaries and also occur at cloud top and base when the cloud dissipates. The humidity halo broadens as the cloud ages and is also broader in the presence of wind shear than in its absence, especially on the downshear side of the cloud. The broadband calculation over the solar spectrum (0.2-4.0 [micro]m) shows that the shortwave (SW) heating rate in the halo is about 11%-18% larger than the ambient environmental heating rate. The strongest halo-induced surface SW radiative forcing for all cases studied is about -0.2 W [m.sup.-2], which is approximately a 0.02% change from the forcing without a halo.

Satellite and corresponding near-surface in situ observations have been made of single- and dual-band cloud events [dubbed anomalous cloud lines (ACLs)] associated with the Chesapeake and Delaware Bays. A previous study developed the basis for two hypotheses concerning the mechanism responsible for ACLs. One explanation is that ACLs are forced in the same manner as Great Lakes lake-effect midlake cloud lines. An alternate explanation is that at least some ACLs are a special type of ship track that forms in statically unstable marine boundary layers. The time period examined in the current research is January 1997-December 2000. National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer imagery served as the satellite dataset, and NOAA buoy 44009 and Coastal-Marine Automated Network station CHLV2 provided the in situ data. The findings from the satellite portion of this research show that ACLs associated with both the Chesapeake and Delaware Bays were observed on roughly 3% of the days examined and were more frequent during the onset of the cold season. The data also show that single-band ACLs were, in general, more frequent than dual-band ACLs. For the near-surface in situ portion of this research, the average ACL for both bays was associated with a negative air--sea temperature difference and a larger downbay wind component than cross-bay wind component. On a month-by-month basis, ACLs for both bays tended to be associated with abnormally large downbay wind speeds and negative air--sea temperature differences in comparison with the corresponding weighted monthly norms.

The lidar-radar algorithm described in Part I of this set of papers is applied to ~1000 h of Raman lidar and millimeter wave cloud radar (MMCR) data collected at the Atmospheric Radiation Measurement program Southern Great Plains Clouds and Radiation Testbed site in Oklahoma during the period from November 1996 to November 2000. The resulting statistics of cirrus microphysical and radiative properties show that most cirrus clouds are optically thin (mean optical depth of 0.58 with a standard deviation of 0.67) with low ice water path (mean 12.19 g [m.sup.-2] with a standard deviation of 19.0). The seasonal changes of cirrus properties are relatively small except for the general effective radius ([D.sub.ge]). Strong temperature dependencies of ice water content, [D.sub.ge], and extinction coefficients are found in the dataset, which are well described by second-order polynomial functions. The temperature and thickness dependencies of the cirrus properties are studied in detail, providing information useful in the validation and improvement of cirrus parameterizations in general circulation models. The limitations of the MMCR for cirrus detection are also considered through comparisons with results from the Raman lidar, which show that the MMCR fails to detect most thin cirrus with [tau] [less than or equal to] 0.1 and consistently underestimates physical cloud thickness. Comparisons with available data describing cirrus microphysical and radiative properties are made, and an improved cirrus particle extinction coefficient parameterization based on the combined lidar-radar approach is offered.

Cloud remote sensing techniques are conventionally based on the independent pixel approximation (IPA). Here, three-dimensional (3D) radiative effects on IPA-based retrieved optical thickness from a visible-wavelength moderate-resolution (about 1 km) sensor are investigated. A Monte Carlo 3D radiative transfer model and a lognormal spectral cloud model are used to simulate monochromatic radiance reflected from overcast boundary layer cloud. A characterization of statistical properties of the optical thickness by the mean (M) and variance ([S.sup.2]) of the logarithm of the optical thickness is proposed, where S represents a degree of cloud inhomogeneity. Biases in retrieved values of the two parameters with the IPA are defined as [DELTA]M and [DELTA][S.sup.2] and attributed to neglect of net horizontal radiative transport in the IPA. Sensitivities of [DELTA]M and [DELTA][S.sup.2] are tested with respect to geometrical roughness, M, S, mean geometrical thickness, spectral exponent of optical thickness fluctuation, ground surface reflectance, and bidirectional angles. The 3D radiative effects are sensitive to the geometrical roughness of cloud top rather than internal inhomogeneity of the extinction coefficient. The bias [DELTA]M is negative in forward scattering viewing geometry due to cloud-side shadowing, while positive in backscattering viewing geometry due to side illumination. It is found that [DELTA]M is proportional to [S.sup.2] and large for a dense cloud. On the other hand, [DELTA][S.sup.2] largely depends on the solar zenith angle; smoothing is exhibited for high solar elevation and roughening for low solar elevation. The smoothing and roughening phenomena are found to be almost independent of the inhomogeneity parameter. An optically thick cloud exhibits more roughening, while for a geometrically thick cloud both smoothing and roughening are enhanced. It is suggested that for the bias removal some empirical assumptions are required in geometrical and microphysical properties of cloud, which should be studied with in situ observation data.

Output signal electrons from photomultiplier tubes (PMTs) have neither a Gaussian nor a Poisson distribution because of changes induced by multiplication when the number of input signal photons and dark electrons is fewer than ~100. Therefore the assumption of a Gaussian distribution of signal electrons cannot be used in simulations for space lidar observations with PMTs, for which the number of return signal photons is normally small. A theory is introduced for analog detection with PMTs that have Poisson-distributed secondary-electron emission at each dynode stage. The theory is validated by straightforward numerical simulations. It is shown that the multiplication in PMTs is a multiply stochastic Poisson process and that the distribution of output signal electrons can be interpreted basically as Neyman type A. Analysis by the threshold method of cloud detection with a space lidar shows considerable difference between a Gaussian approximation and the exact distribution. The result indicates that the threshold level must be optimized for the exact distribution. Return signals were simulated for a proposed space lidar, and cloud detection with the threshold method was demonstrated. OCIS codes: 040.5250, 280.3640.

The sensitivity of a new algorithm for cloud detection over a sea surface has been assessed on the basis of extensive simulations of clear and cloudy radiance spectra, including water and ice and low- and high-altitude clouds. The new algorithm makes use of autocorrelation and cross correlation between an observed spectrum and either a synthetic or a laboratory spectrum and can be used to determine quantitatively the degree of homogeneity of two spectra in the 800-900-[cm.sup.-1] region (11.11-12.5 [micro]m). The scheme is intended for high-spectral-resolution observations and could form the basis for an operational stand-alone cloud-detection algorithm for next-generation sounding spectrometers. Application of the scheme to real observations is presented and discussed. OCIS codes: 010.0010, 010.3920, 280.0280.

Byline: Hua Li (1), Hidekatsu Yamazaki (1) Keywords: Kelvin-Helmholtz billow; shear instability; length scale Abstract: We identified a Kelvin-Helmholtz billow from vertical turbulence velocity and instantaneous heat flux signals obtained from airfoil shear probes and thermistors mounted on a research submarine. The vertical turbulence velocity indicates that the horizontal scale of the billow was about 3.5 m. The spectral slope of the vertical turbulence velocity component is close to -2, revealing the flow is two-dimensional. We show a remarkable agreement between the length scales of the observed billow and those computed from direct numerical simulations based on similar conditions. Author Affiliation: (1) Department of Ocean Sciences, Tokyo University of Fisheries, Tokyo, 108-8477, Japan Article History: Registration Date: 08/10/2004

The Clouds and the Earth's Radiant Energy System (CERES) is part of NASA's Earth Observing System (EOS). CERES objectives include the following. 1) For climate change analysis, provide a continuation of the Earth Radiation Budget Experiment (ERBE) record of radiative fluxes at the top-of-the-atmosphere (TOA), analyzed using the same techniques as the existing ERBE data. 2) Double the accuracy of estimates of radiative fluxes at TOA and the earth's surface; 3) Provide the first long-term global estimates of the radiative fluxes within the earth's atmosphere. 4) Provide cloud property estimates collocated in space and time that are consistent with the radiative fluxes from surface to TOA. In order to accomplish these goals, CERES uses data from a combination of spaceborne instruments: CERES scanners, which are an improved version of the ERBE broadband radiometers, and collocated cloud spectral imager data on the same spacecraft. The CERES cloud and radiative flux data products should prove extremely useful in advancing the understanding of cloud-radiation interactions, particularly cloud feedback effects on the earth's radiation balance. For this reason, the CERES data should be fundamental to our ability to understand, detect, and predict global climate change. CERES results should also be very useful for studying regional climate changes associated with deforestation, desertification, anthropogenic aerosols, and El Nino/Southern Oscillation events. This overview summarizes the Release 2 version of the planned CERES data products and data analysis algorithms. These algorithms are a prototype for the system that will produce the scientific data required for studying the role of clouds and radiation in the earth's climate system. This release will produce a data processing system designed to analyze the first CERES data, planned for launch on Tropical Rainfall Measuring Mission (TRMM) in November 1997, followed by the EOS morning (EOS-AM1) platform in 1998. Index Terms - Algorithms, clouds, meteorology, radiation monitoring.

Simultaneous field measurements of aerosol and cloud droplet concentrations and droplet diameter were performed at a maritime site on the coast of Washington State. The aerosol and droplet spectra were compared for estimating cloud condensation nucleus concentration ([N.sub.ccn]) as the number of particles with diameters greater than 80 nm, that is, [N.sub.ccn] = N([D.sub.p] > 80 nm). Several analytical approaches were developed and applied to the data, including a stratification of the observations into periods of high and low liquid water content (LWC) based on a threshold value of 0.25 g [m.sup.-3]. The aerosol data were corrected for inertial losses of cloud droplets at the inlet using wind speed and droplet size; this correction improved the measured relationships between [N.sub.ccn], and droplet number concentration ([N.sub.d]). These measurements, when coupled with the range of possible aerosol chemical compositions, imply a cloud supersaturation of 0.24%-0.31% at the Cheeka Peak sampling site during periods of high LWC. The observations of droplet and aerosol spectra supported Twomey's cloud brightening hypothesis in that [N.sub.ccn] was highly correlated ([r.sup.2] = 0.8) with [N.sub.d] in apparent 1:1 proportions. For the investigated range (50 [cm.sup.-3] < [N.sub.d] < 600 [cm.sup.-3]) droplet effective diameter ([D.sub.eff]) was very sensitive to variation in [N.sub.ccn] for 50 [cm.sup.-3] < [N.sub.ccn] < 200 [cm.sup.-3], somewhat sensitive for 200 [cm.sup.-3] < [N.sub.ccn] < 400 [cm.sup.-3], but not very sensitive to variation in aerosol number for [N.sub.ccn] > 400 [cm.sup.-3]. A model was applied to the aerosol and droplet data to predict droplet size, as [D.sub.eff], from [Mathematical Expression Omitted] and LWC. Predicted values for [D.sub.eff] agreed ([r.sup.2] = 0.8) with [D.sub.eff] determined directly from the cloud droplet spectra, suggesting that this approach should be useful in climate modeling for predicting cloud droplet size from knowledge of [N.sub.ccn] and LWC.

An air parcel model including homogeneous freezing nucleation of ice crystals has been used to study the formation and development of cirrus clouds. In situ measurements taken during March 1994 over southern Germany were used for comparison with model predictions. Typical experimental data were chosen for a base-case model run. Using measured aerosol properties as input values, the model predicts the measured ice crystal size distribution. In particular, both measurements and model results show the presence of numerous small ice crystals (diameter between 1 and 20 [[micro]meter]). Both measurements and model results also show that small aerosol particles (below 0.1 [[micro]meter] diameter) are active in forming cirrus cloud particles. The modeled microphysical properties including ice crystal size distribution, number concentration, and the residual particle size distribution are in good agreement with the experimental data. based on the measured parameter values, a model sensitivity study considering air parcel updraft velocity, initial temperature, relative humidity, aerosol size distribution, number concentration, and air parcel vertical displacement is presented.

This article describes a parameterization of the visible extinction coefficient of cirrus and frontal ice cloud in terms of the ice/water content. The parameterization is based on the discovery that the ice cloud particle size spectra from a particular dataset tended to fall into three separate well-defined regions. These regions were a Marshall-Palmer distribution covering particles with dimensions larger than between 100 and 1400 [[micro]meter], depending on the cloud temperature; a Heymsfield-Platt type power-law distribution for the smaller particles (dimensions from 20 [[micro]meter] to somewhere between 100 and 800 [[micro]meter]); and a different spectrum of the smallest particles of sizes less than 20 [[micro]meter]. The dataset chosen had been obtained from aircraft in situ observations of cloud particle size spectra in ice clouds and covered the entire spectral range from 2 to 3000 [[micro]meter], thus allowing a study of every important spectral region. Part of this dataset was used originally in a previous study by Heymsfield and Platt. The data used in the present study covered cirrus clouds overlying deep frontal clouds, together with a reanalysis of the Heymsfield-Platt set for 'dry' cirrus clouds. In the present study, the visible extinction coefficient [Sigma] was parameterized in terms of the ice/water content W. A model of cylindrical ice particles was used. It was found that the dependence of [Sigma] on W followed a power law of the form, [Sigma] = j[W.sup.k], where k had a value that depended on the temperature range. The size spectra, although measured in certain cirrus and frontal ice clouds, were also used as surrogate spectra to estimate similar [Sigma]-W relations for water clouds. The [Sigma]-W relations for cirrus ice clouds were found to agree reasonably with those obtained recently by other workers. The relations also indicated, conversely, that the cloud ice/water content of cirrus could be retrieved from a measure of the cloud volume extinction coefficient to within an uncertainty of about 30%.

Photographs of a 120 [degrees] parhelion and a 22 [degrees] parhelion within persistent contrails are presented. These phenomena result from hexagonal plate-shaped ice crystals oriented horizontally with diameters between 300 [[micro]meter] and 2 mm. From our observations and reinvestigation of previous reports, we conclude that a subset of the population in persistent contrails can consist of highly regular, oriented, hexagonal plates or columns comparable to the most regular crystals in natural cirrus clouds. This is explained by measured ambient humidities below the formation conditions of natural cirrus. The resulting strong azimuthal variability of the scattering phase function impacts the radiative transfer through persistent contrails. Key words: Aircraft, contrail, climatic impact, crystal growth, halo phenomena, ice crystals, optical properties, relative humidity, remote sensing, scattering phase function.

The macroscopic behavior of cumulus convection and its mesoscale organization during Phase III of the Global Atmospheric Research Program's (GARP) Atlantic Tropical Experiment (GATE) is simulated with a two-dimensional (2D) cloud ensemble model. The model includes a three-phase bulk microphysics parameterization, a third-moment turbulence closure and an interactive, radiative transfer parameterization. The observed large-scale, horizontal advective effects and large-scale vertical velocity are imposed on the model's thermodynamic equations uniformly in the horizontal. The simulated, domain-averaged horizontal wind components are nudged toward the observed winds. A detailed comparison with available observations is made in this study. The observed time variations of the surface precipitation rate, surface evaporation rate, outgoing longwave radiation flux, and the vertical distributions of temperature, water vapor mixing ratio, and relative humidity are successfully reproduced by the model, as well as the vertical structure and time evolution of major convective systems. The most significant result is that the model is able to reproduce the negative correlation between the intensity of convection and the convective available potential energy. The simulated total cloud amount compares favorably with the whole-sky camera observations of Holle et al., but the low-level cloud amount is significantly underestimated. In spite of its success, sensitivity tests suggest that the 2D model has stronger inhibiting effects on convection and is more efficient in vertical transports than is observed when the vertical wind shear is strong. The CEM also produces smaller amplitudes of the daily fluctuations in cloud amount and precipitable water than observed, due possibly to the shortcomings of the microphysics parameterization.

W-band (3.2-mm) radars are seeing increasing utilization as a result of improving microwave technologies and the increased research emphasis being given to nonprecipitating clouds. This niche is exemplified by the study of the radiatively important stratus and cirrus clouds, which essentially require the application of Rayleigh and nonspherical scattering solutions, respectively. To increase the utility of such studies, the authors provide the following relations derived from empirical and model-derived particle size distributions that rely on a combination of Rayleigh and conjugate gradient-fast Fourier transform scattering theory approaches to relate (equivalent) radar reflectivity factors ([Z.sub.e]) Z ([mm.sup.6] [m.sup.-3]) to liquid water content (LWC, g [m.sup.-3]) and ice water content (IWC, mg [m.sup.-3]): Z = (3.6/[N.sub.d])[LWC.sup.1.8] for stratus clouds, where [N.sub.d] ([cm.sup.-3]) is the droplet concentration, and [Mathematical Expression Omitted] for cirrus clouds using the dielectric constant appropriate for ice, which is valid over a IWC range of 3-100 mg [m.sup.-3]. Sources of 95-GHz attenuation are also discussed. In addition, radar estimates of the lidar volume extinction coefficient [[Sigma].sub.l] ([m.sup.-1]) are derived using the exponential ice particle size distributions, yielding [Mathematical Expression Omitted] for solid ice particles, or [Mathematical Expression Omitted] if an ice density of 0.5 g [cm.sup.-3] is used to approximate the effects of hollow ice crystals in cirrus clouds.

Twelve months of Southern Hemisphere (maritime) midlatitudes Advanced Very High Resolution Radiometer local area coverage data at full radiometric and spatial resolution have been collocated with rain-rate data from three Doppler weather radars. Using an interactive computing environment, large independent samples of cloudy - altocumulus, cumulonimbus, cirrostratus, cumulus, nimbostratus, stratocumulus, stratus - and cloud-free scenes have been identified (labeled) in the collocated data. Accurate labeling was ensured by providing a supervising-analyst access to appropriate diagnostics, including difference and ratio channels, 3.7-[[micro]meter] reflected and emissive components. spectral histograms, Coakley-Bretherton spatial coherence plots, mean, standard deviation, and gray-level difference (GLD) statistics. This analysis yielded 4323 cloud and no-cloud samples at a spatial resolution of 8 x 8 instantaneous fields of view (IFOV), from 257 NOAA-11 and NOAA-12 orbits. Bayesian cloud discriminant functions calculated from the labeled samples and utilizing feature vectors including radiometric and GLD spatial characteristics successfully classified scenes into one of the seven cloud and no-cloud classes with significant skill (Kuipers' performance index 0.63). Utilizing the posterior probability of the classified samples enabled some clouds that were classified erroneously to be identified (and discarded), improving the skill of the discriminant functions by an additional 10% or so. Removing the GLD statistics from the feature vector reduced the skill of the cloud discrimination by about 20% (relative to the nondiscarding discriminant function), while increasing the misclassification of midlevel clouds. However, some cloud classes can only be discriminated from their multispectral signatures. Day and night discriminant functions show similar skill. Within raining cloud classes, rain rate has been related to the spatial and radiometric characteristics of the cloud. The skill of the rain-rate estimates is dependent on the cloud type. For nimbostratus and altocumulus classes 20%-25% of the rain-rate variation can be explained by predictors that measure the temperature, spatial texture, and degree of isotropy in the sampled clouds. Raining and nonraining samples of altocumulus, cumulus, cirrostratus, and nimbostratus can be delineated with at least 60% accuracy. This approach, whereby cloud classes are identified then rain rates estimated as a function of cloud type, would seem to resolve some of the usual problems associated with rain-rate analyses from midlatitudes infrared and visible satellite data. It also extends rain-rate diagnosis to nonconvective (frontal) cloud systems.

The authors measured aerosol and droplet size distributions in the range from 0.1 to 50 [mu], concentrations and sizes of precipitation particles, concentrations of condensation nuclei, and state parameters in and in the vicinity of a towering summer cumulus cloud. The measurements show that the liquid water content, droplet concentration, and vertical velocity all peaked in the upper half of the cloud, but the droplet mean diameter increased with altitude. A large fraction of the aerosols (0.1-3.0 [mu]) remains in the haze state. The vertical profiles of aerosols and condensation nuclei showed peaks between 5.0 and 7.0 km. The normalized aerosol size distribution shows a shift toward large aerosols. The peaks and the shift in the distribution were explained by chemical conversion of [SO.sub.2] to sulfate in-cloud droplets.

An analysis of the spatial and temporal scales of cloud variability and their coupling provided by the results from existing cloud observing systems allows us to reach the following conclusions about the necessary attributes of a cloud monitoring system. (1) Complete global coverage with uniform density is necessary to obtain an unbiased estimate of cloud change and an estimate of the reliability with which that change can be determined. (2) A spatial sampling interval of less than 50 km is required so that cloud cover distributions will generally be homogeneous, or statistically homogeneous, within a sample. (3) A sampling frequency of at least six times a day ensures not only that the diurnal and semi-diurnal cycles are not aliased into long term mean values, but also that changes in them can be monitored. (4) Since estimated climate changes are only evident on a decadal time-scale, unless cloud monitoring is continuous with a record length greater than 10 years and has very high precision ([approximately equal to] 1%) instrument calibration with overlapping observations between each pair of instruments, it will not be possible either to detect or to diagnose the effects of cloud changes on the climate.

The purpose of this paper is to assess the potential of a spaceborne 94-GHz radar for providing useful measurements of the vertical distribution and water content of ice clouds on a global scale. Calculations of longwave (LW) fluxes for a number of model ice clouds are performed. These are used to determine the minimum cloud optical depth that will cause changes in the outgoing longwave radiation or flux divergence within a cloud layer greater than 10 W [M.sup.-2], and in surface downward LW flux greater than 5 W [m.sup.-2], compared to the clear-sky value. These optical depth values are used as the definition of a 'radiatively significant' cloud. Different 'thresholds of radiative significance' are calculated for each of the three radiation parameters and also for tropical and midlatitude cirrus clouds. Extensive observational datasets of ice crystal size spectra from midlatitude and tropical cirrus are then used to assess the capability of a radar to meet these measurement requirements. A radar with a threshold of -30 dBZ should detect 99% (92%) of 'radiatively significant' clouds in the midlatitudes (Tropics). This detection efficiency may be reduced significantly for tropical clouds at very low temperatures (-80[degrees]C). The LW flux calculations are also used to establish the required accuracy within which the optical depth should be known in order to estimate LW fluxes or flux divergence to within specified limits of accuracy. Accuracy requirements are also expressed in terms of ice water content (IWC) because of the need to validate cloud parameterization schemes in general circulation models (GCMs). Estimates of IWC derived using radar alone and also using additional information to define the mean crystal size are considered. With crystal size information available, the IWC for samples with a horizontal scale of 1-2 km may be obtained with a bias of less than 8%. For IWC larger than 0.01 g [m.sup.-3], the random error is in the range +50% to -35%, whereas for a value of 0.001 g [m.sup.-3], the random error increases to between +80% and -45%. This level of accuracy also represents the best that may be achieved for estimates of the cloud optical depth and meets the requirements derived from LW flux calculations. In the absence of independent particle size information, the random effort is within the range +85% to -55% for IWC greater than 0.01 g [m.sup.-3]. For the same IWC range, the estimated bias is less than [+ or -] 15%. This accuracy is sufficient to provide useful constraints on GCM cloud parameterization

This paper presents the statistical properties of lidar-derived values of cloud extinction coefficients [sigma] and optical depths [tau]. The data were collected at Toronto during two measurement phases (phase 1: September-October 1989; phase 2: June-July 1991) of the Experimental Cloud Lidar Pilot Study. Although the small dataset limits general application of the statistical trends observed, the measurements demonstrate the valuable potential of lidar data for improving cloud parameterization in general circulation models. The measurements show the frequent occurrence of optically thin clouds ([sigma] [less than or equal to] 0.2 [km.sup.-1] and [tau] [less than or equal] to 0.2), demonstrating the ability of lidars to detect these dilute clouds and the importance of including them in radiative transfer models.

Use of radar with upper frequency of 13.8 GHz along with a lower frequency gives good estimation of attenuation due to clouds (Ac) and cloud water content (Wc). Statistical data on cloud attenuation is obtained using the measurements of Ac and Wc. This data could be used in developing ways to make corrections in the radar measured values, which are affected by cloud attenuation. The use of a radar, working at two frequencies, in calculating attenuation and water content of clouds is described.

The spatial and temporal variability of precipitating stratocumulus layers is examined using aircraft observations, satellite retrievals of cloud optical depth, and one-dimensional models that include coalescence and a simple representation of layer turbulence. The aircraft observations show large horizontal variations in cloud thickness and precipitation, with local rain rates 4-5 times larger than the replacement moisture flux, and evidence for precipitation scavenging of small cloud droplets. The satellite observations show that, despite this local water loss, the distribution of cloud optical thickness remains nearly constant over the course of a day, indicating that on larger scales precipitation removal and cloud-top entrainment are in approximate balance with the vapor flux. The authors apply analytic and numerical models of steady-state precipitation to the observed microphysical conditions, and find that the models can match the drop size distributions observed during both heavy and light stratocumulus rainfall, but are especially sensitive to the processes governing the growth rate of the smallest drizzle drops.

Improved ray-optics theory and Mie theory for single scattering and an adding-doubling method for multiple scattering have been used to study the interaction of radiation in NASA's Visible and Infrared Spin-Scan Radiometer Atmospheric Sounder Satellite (VAS) IR channels and the microphysics of inhomogeneous cirrus clouds. The simulation study shows that crystal shape has remarkable effects on scattering and on the radiative-transfer properties of cirrus clouds in IR spectra. The sensitivity of the brightness temperature, as observed with VAS-IR channels, to the hexagonal columns and plates in cirrus clouds is noticeable. A method that permits one to infer the optical thickness, crystal shape, ice-water content, and emittance of cirrus clouds by using a multi-IR window channel with a scanning observation technique is developed. Detailed error analyses are carried out, and the characteristics of VAS-IR window channels are investigated through the examination of the effects of sea-surface reflection and variations in the temperature and water-vapor profiles on the VAS measurements. It is shown that these effects are large and need to be considered. Some uncertainties that have risen from the theoretical model are studied; they demonstrate that the Mie-scattering theory should not be used to retrieve the microphysical and optical properties of cirrus clouds. A suitable cloud-microphysics model and a suitable scattering model are needed instead.

The Thermal Infrared Multispectral Scanner (TIMS) and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) were operated simultaneously from the ER2 aircraft during a March 1990 test over the Rio Bravo region, Belize. The two instruments have different scan rates and instantaneous fields of view. In addition, the undulation of the TIMS platform (i.e., the ER2 wing) induced relative motion between the normal viewing directions of the two instruments. Their scan directions also were slightly divergent. Coregistration of the imagery obtained by these two instruments is necessary to utilize the data effectively. However, coregistration is not a straightforward process, and traditional techniques based on ground control points are ineffective in this case. A technique for registering the TIMS imagery to AVIRIS imagery is presented. It takes advantage of the morphology of the fair weather cumulus (FWC) clouds present in the imagery for estimating inter-sensor distortions. It relies on an iterative process in which skew, nearest neighbor sampling, and cross-correlation (1D and 2D) are applied. Comparison between the AVIRIS three-band ratio (3BR) imagery and the coregistered TIMS imagery shows that TIMS is superior in detecting thin cloud and cloud edge pixels, especially over shadowed background. Although the seven scenes analyzed in this study were obtained within the same one-hour time period and over the same geographical region, the optimum temperature threshold for cloud detection, with respect to the background temperature, varies significantly from 2.1 to 3.3 [degrees] C. These values agree with the AVIRIS 3BR cloud fraction equivalent temperature thresholds to within 0.5 [degree] C. When applying a cloud shadow mask from the AVIRIS near infrared imagery to the coregistered TIMS background imagery, a 1 [degree] C temperature differential is found between the shadowed and nonshadowed background. This significant radiative cooling by Fair Weather Cumulus cloud shadows could introduce errors in surface emissivity retrievals by other Earth Observing System (EOS) investigators.

Seen from space, Earth can look dressed up or downright dowdy, depending on the location. In some spots, swathes of cloud cloak the dark ocean, offering a stunning contrast of [...]

The Experimental Cloud Lidar Pilot Study (ECLIPS) was initiated to obtain statistics on cloud-base height, extinction, optical depth, cloud brokenness, and surface fluxes. Two observational phases have taken place, in October-December 1989 and April-July 1991, with intensive 30-day periods being selected within the two time intervals. Data are being archived at NASA Langley Research Center and, once there, are readily available to the international scientific community. This article describes the scale of the study in terms of its international involvement and in the range of data being recorded. Lidar observations of cloud height and backscatter coefficient have been taken from a number of ground-based stations spread around the globe. Solar shortwave and infrared longwave fluxes and infra-red beam radiance have been measured at the surface wherever possible. The observations have been tailored to occur around the overpass times of the NOAA weather satellites. This article describes in some detail the various retrieval methods used to obtain results on cloud-base height, extinction coefficient, and infrared emittance, paying particular attention to the uncertainties involved. The above methods are then illustrated by both model simulations and by selected results from various laboratories. The ECLIPS data are shown to represent a valuable resource for cloud parameterizations in models and for model validations.

If the Sun can be seen at all through thin clouds it usually has a sharp edge, although occasionally it appears fuzzy, especially through altostratus, but rarely, if ever, through fog. Experiments with suspensions of polystyrene spheres of different sizes and optical thicknesses suggest that the range of cloud optical thicknesses over which a fuzzy Sun is seen increases with particle size. Nonsphericity, turbulence, and cloud horizontal inhomogeneity are not necessary for fuzziness. A possible explanation for what is observed is that, for a given optical thickness, the modulation contrast function of a cloud decreases more rapidly with increasing frequency the greater the particle size. Consequently the transition from optical thicknesses for which contrast is above the contrast threshold at all spatial frequencies to optical thicknesses for which contrast is below the threshold at high frequencies is sufficiently gradual to permit fuzziness of the Sun to be observed through clouds of constantly changing optical thickness.

Spectrally resolved visible and infrared images of marine stratus clouds were acquired from the NASA ER-2 high-altitude aircraft during the 1987 First International Cloud Climatology Program Regional Experiment. The images were obtained by cross-track scanning radiometers. Data images at near-infrared wavelengths show frequent and readily apparent brightness features that are due to glory single scattering. The observations and subsequent analysis by radiative transfer calculations show that the glory is a significant feature of near-infrared solar reflectance from water clouds. Glory observations and calculations based on in-cloud microphysics measurements agree well. The most dramatic difference from the visible glory is that the scattering angles are significantly larger in the near infrared. The glory is also apparently more distinct in the near infrared than in the visible, as scattering size parameters are in a range that effectively produces a glory feature, and also there is less obscuration by multiple-scattering reflectance because of absorption of radiation by droplets in the near infrared. For both the visible and the near infrared, the principal factors that wash out the glory are dispersion and, to a lesser degree, the effective radius of the cloud droplet-size distribution. The obscuration by multiple scattering in optically thick clouds is secondary. Rather than being a novelty, glory observations would be an accurate and unambiguous technique to sense the droplet size of water clouds remotely.

In the longwave part of the spectrum, clouds are generally modeled in GCMs as flat black plates. The true effective cloud cover for transmittance of infrared radiation may be larger or smaller than the fractional cloud cover normal to the surface because of emittance of radiation from the sides of clouds into the clear sky and because the sides may have a finite cross section normal to the view and a vertical thermal gradient. The authors have derived the effective cloud cover as a function of zenith angle in terms of the cloud cover normal to the surface for several models of cumulus clouds with measured spatial and size distributions as a function of aspect ratio (height to radius or half-width) and shape. The effective cloud cover is shown as a function of cloud shape and aspect ratio as well as spatial distribution. The effective cloud cover is also sensitive to the thermal gradient between the cloud top and its base.