Abstract: An initialization scheme for numerical models containing treatment of cloudiness is presented. The dynamic type of initialization scheme is based on the digital filtering technique, which requires integration of the model backward and forward about the analysis time. As the numerical model contains an advanced condensation-cloud parameterization, the initialization procedure renders initial cloud water and cloud cover fields, yet no cloud observations have been available. The initial cloud fields obtained are in a good agreement with the weather situations as they appear on satellite imagery and in synoptic analyses. The cloud water content is of the same order of magnitude as the one obtained from a 24-h forecast with the model. Improvements are observed in the spinup of the model cloud and of the precipitation rate.

Abstract: A one-dimensional kinematic model is used to investigate the effects of silver iodide seeding in the region of a Cb cloud between isotherms of −8°C and −12°C. The agent interaction with cloud atmosphere is simulated by an improved microphysical model version which includes phoretic processes. The behaviour of the different agent types is investigated using the maximum values of agent mixing ratios and corresponding agent particle masses and radii.

Abstract: A method is presented for determining the infrared optical depth of semitransparent clouds from satellite measurements. The technique employs cloud measurements at two infrared wavelengths and two angles. Using a simple but accurate model it is shown that the cloud optical depths at both wavelengths can be uniquely determined. Results of simulation studies are presented. The method will be used on data from the Along Track Scanning Radiometer on the first European remote-sensing satellite (ERS-1), which has the capability of providing multiangle multichannel measurements globally.

Abstract: To our knowledge, previous observations of cloud boundaries have been limited to studies of cloud bases with ceilometers, cloud tops with satellites, and intermittent reports by aircraft pilots. Comprehensive studies that simultaneously record information of cloud top and cloud base, especially in multiple layer cases, have been difficult, and require the use of active remote sensors with range-gated information. In this study, we examined a 4-week period during which the NOAA Wave Propagation Laboratory (WPL) 8-mm radar and the Pennsylvania State University (PSU) 3-mm radar operated quasi-continuously, side by side. By quasi-continuously, we mean that both radars operated during all periods when cloud was present, during both daytime and nighttime hours. Using this data, we develop a summary of cloud boundaries for the month of November for a single location in the mid-continental United States.

Abstract: : A new cloud analysis model to eventually replace the Real-Time Nephanalysis operating at the Air Force Global Weather Central is being prototyped. This new cloud analysis model will process multisource satellite data, geostationary and polar-orbiting, civilian and military. The output will be used primarily to initialize cloud forecast models but may be used also for climate research and other applications. This report will review the customer requirements for cloud analysis data, the existing and future cloud forecast algorithms, and how the new cloud analysis model can integrate the multisource satellite data into one coherent analysis useful to all users. The likely approach for this 'analysis integration' will be to blend optimum interpolation techniques, common in numerical weather analysis, with a knowledge base commonly used in artificial intelligence.

Abstract: Recently, an adaptive method to partition and interpret satellite images for cloud classification has been presented. In this application, texture measures are used as features and the segmentation and classification is based the self-organizing process. The cloud classification system has been in operational use since September 1991. In this paper, performance characteristics obtained so far are presented.

Abstract: Activities at the NASA Langley Research Center's distributed active archive centers (DAACs) intended to capitalize on existing centers of scientific expertise and to prevent a single point of failure are described. A Version 0 Langley DAAC, a prototype of an Earth Observing System Data and Information System, started archiving and distributing existing datasets on the earth's radiation budget, clouds, aerosols, and tropospheric chemistry in late 1992. The major goals of the LaRC Version 0 effort include to enhance scientific use of existing data; to develop institutional expertise in maintaining and distributing data; to encourage cooperative interagency and international involvement with datasets and research; and to use institutional capability for processing data from previous missions to prepare for processing the future EOS satellite data.

Abstract: To support the development of electro/optical sensor systems under the Smart Weapons Operability Enhancement (SWOE) Program. TASC has developed a four-dimensional (3 spatial and 1 temporal) cloud model for use in radiometric computations and scene simulation. The cloud scene simulation model employs a multi-step process to generate the density fields beginning with the rescale and add fractional Brownian motion algorithm to simulate the horizontal distribution of cloud elements within the user-defined cloud domain. Knowledge of structures of stratiform and cirriform cloud types is used to specify the vertical extent of individual clouds. Internal variability is then generated within each cloud using a three- dimensional version of the rescale and add model. A physics-based scheme that models clouds as the sum of a large number of individual Lagrangian 'parcels' is used to simulate cumulus cloud growth and convection based on environmental conditions. In this paper we present a description of the cloud scene simulation modeling process. In particular, we emphasize the cumulus model which marries fractal field generation and convection dynamics to result in a computationally efficient method to generate cloud fields that are both physically derived and visually realistic.

Abstract: The extent of penetration and/or perforation of a target layer by a debris cloud, whose particle mass distribution and velocities were calculated from a previous impact, was determined with two computational approaches. First, the size of single or paired particles required for target perforation was calculated and compared with the largest particle expected based on the fragment size distribution in the debris cloud. A second approach used a three-dimensional shock-wave code to calculate the explicit interaction of individual particles in the debris cloud with the target. The cloud was represented by randomly locating the particles within an envelope, maintaining the mass and size distribution of the particles. This interaction of the cloud of particles produced target surface craters and penetration comparable to recovered witness plates from impact experiments.

Abstract: In this paper we outline the Smart Weapons Operability Enhancement (SWOE) cloud modeling requirements. We present an overview of the cloud model logic, and provide more detailed descriptions of the fractal field generation process and the cumuliform convection model.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Abstract: The determinations of cloud presence, properties, and radiative influence are high priority requirements for both defense related operations and in the pursuit of research goals for the U.S. Global Change Research Program. A number of current programs address aspects of the remote sensing of clouds; this paper provides an overview of these programs, their objectives, requirements, and interrelationship. Requirements are divided into three categories: (1) impacts on defense operations and systems, (2) numerical weather prediction (NWP), and (3) climate study objectives, both prognostic and diagnostic. Additionally, current satellite sensor data resources and applicable cloud property retrieval algorithm approaches are described.

Abstract: : This report describes data sources, data processing activities, compression, prediction, and blending of the climatological databases chosen to represent realistic global cloud amount statistics within the C Cloud S program.

Abstract: Introduction The classification of clouds and the evaluation of liquid water content interest meteorology and climate modelling from space. Many methods have been developped using either optical measurements (1) or microwave radiometers (2). But the number of simultaneous use of both techniques remain poor partly due to the problem of coincidence in time and place of the two kinds of measurements (3). Using microwave radiometry it is quite difficult to establish and validate a liquid water retrieval algorithm due to the lack of in-situ measurements, so a comparison to liquid water content obtained by optical method is interesting. The optical approach takes into account the fact that the reflectance is a function of the albedo itself related to the optical depth. Moreover combining infrared and visible (or near-visible) channels enables a cloud classification which can help to develop microwave algorithm. This preliminary study takes benefit of the exactly coincident measurements in time and location of the micowave radiometer (ATSWMWR) and infrared instrument (ATSRAR) aboard ERS1, to compare the results of optical and microwave approaches on some images acquired in July 1992.

Abstract: An unresolved problem in current cloud retrieval algorithms concerns the analysis of scenes containing overlapping cloud layers. Cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget. Most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. One promising method uses fuzzy logic to determine whether mixed cloud and/or surface types exist within a group of pixels, such as cirrus, land, and water, or cirrus and stratus. When two or more class types are present, fuzzy logic uses membership values to assign the group of pixels partially to the different class types. The strength of fuzzy logic lies in its ability to work with patterns that may include more than one class, facilitating greater information extraction from satellite radiometric data. The development of the fuzzy logic rule-based expert system involves training the fuzzy classifier with spectral and textural features calculated from accurately labeled 32x32 regions of Advanced Very High Resolution Radiometer (AVHRR) 1.1-km data. The spectral data consists of AVHRR channels 1 (0.55-0.68 mu m), 2 (0.725-1.1 mu m), 3 (3.55-3.93 mu m), 4 (10.5-11.5 mu m), and 5 (11.5-12.5 mu m), which include visible, near-infrared, and infrared window regions. The textural features are based on the gray level difference vector (GLDV) method. A sophisticated new interactive visual image Classification System (IVICS) is used to label samples chosen from scenes collected during the FIRE IFO II. The training samples are chosen from predefined classes, chosen to be ocean, land, unbroken stratiform, broken stratiform, and cirrus. The November 28, 1991 NOAA overpasses contain complex multilevel cloud situations ideal for training and validating the fuzzy logic expert system.

Abstract: Meteorological satellite instrument pixel sizes are often much greater than the individual cloud elements in a given scene. Partially cloud-filled pixels can be misinterpreted in many analysis schemes because the techniques usually assume that all of the cloudy pixels are cloud filled. Coincident Landsat and Geostationary Operational Environmental Satellite (GOES) data and degraded-resolution Landsat data were used to study the effects of both sensor resolution and analysis techniques on satellite-derived cloud parameters. While extremely valuable for advancing the understanding of these effects, these previous studies were relatively limited in the number of cloud conditions that were observed and by the limited viewing and illumination conditions. During the First ISCCP Regional Experiment (FIRE) Phase 2 (13 Nov. - 7 Dec. 1991), the NASA ER-2 made several flights over a wide range of cloud fields and backgrounds with several high resolution sensors useful for a variety of purposes including serving as ground truth for satellite-based cloud retrievals. This paper takes a first look at utilizing the ER-2 for validating cloud parameters derived from GOES and NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data.

Abstract: A semi-portable flow-through cloud water monitoring system was developed for measurements of cloud water conductivity and pH in remote sites lacking AC line power. This system was tested from May to September on Camels Hump mountain, Vermont. High temporal resolution data from seven cloud events were collected during the 1991 growing season. Mean cloud water conductivity and pH for all events was 467 μmhos cm−1 and 3.2, respectively. The highest conductivity was 997 (μmhos cm−1 recorded on 19 September 1991 and the lowest pH of 2.9 was recorded during several events over the summer. Data from this system may be used to achieve a better understanding of the chemical environment in areas experiencing forest decline.

Abstract: A multi-year research and development program is underway to develop an automated cloud model known as TACNEPH for use by the Air Force at tactical sites. Significant features of this model include the ability to analyze real-time DMSP/OLS and NOAA/AVHRR data using only the limited resources of transportable tactical ground stations and to automatically adapt to changes in the available data mix. No supporting data from a center are available (e.g., upper air temperature and moisture fields, surface reports). To satisfy these requirements it was necessary to develop separate algorithms for each sensor platform. An infrared algorithm developed for DMSP data relies on an estimate of the clear scene radiative brightness temperature based on a dynamic correction to a surface temperature climatology. A separate NOAA IR algorithm is an adaptation of the multispectral approach of Saunders and Kriebel. Both algorithms are designed to improve cloud detection capabilities over the current Air Force operational RTNEPH model, with particular emphasis on low cloud. A major aspect of the TACNEPH development program is the validation of the cloud algorithms over globally varying conditions. Since there is no universally accepted source of ground truth data for cloud, it was necessary to develop a validation procedure based on available data sources. Algorithm validation is based on subjective man/computer analysis of the input satellite sensor data using any available additional data sources as guidance.

Abstract: In order to get a better understanding of the influence of clouds on the Earth's energy budget, one needs a cloud classification taking into account cloud height, thickness, and cloud cover. The radiometer ScaRaB (scanner for radiation balance), launched in 1993, has in addition to the two broad-band channels (0.2 - 4 micrometers and 0.2 - 50 micrometers ) necessary for earth radiation budget (ERB) measurements, two narrow-band channels (0.5 - 0.7 micrometers and 10.5 - 12.5 micrometers ) in order to improve cloud detection. Most automatic cloud classifications have been developed with measurements of very good spatial resolution (200 m to 5 km). Earth radiation budget experiments, on the other hand, work at a spatial resolution of about 40 km (at nadir), and therefore we investigated a cloud classification algorithm adapted on this scale. The algorithm is based on the dynamic clustering method and uses co-located AVHRR-ERBE data, simulating the ScaRaB measurements. This cloud field classification is compared on one hand to results obtained by a well tested threshold algorithm using AVHRR (advanced very high resolution radiometer) measurements at reduced spatial resolution of 4 km and on the other hand to cloud parameters extracted from HIRS (high resolution infrared sounder)/MSU (microwave sounding unit) data. We find that classification of cloud fields is still possible at a resolution of 40 km, and by combining AVHRR, ERBE, and HIRS/MSU measurements one can undertake interesting studies on the influence of different cloud fields on the Earth radiation budget.

Abstract: : Neural networks are appropriate for meteorological classification tasks for a number of reasons. First, their associative properties allow graceful degradation of performance under conditions of ambiguity and noise, thus avoiding the brittle behavior of many standard approaches. Second, they learn to perform tasks which cannot easily be specified analytically, such as non-linear discriminate functions. Finally, they can be executed in realtime on appropriate hardware. To exploit these properties, this research developed a general approach to meteorological classification based on neural network data fusion. The system was applied to cloud type identification from satellite imagery. The current experiment is one of the first to provide a large cloud database on which to train, and as such is one of the first true cross- validation experiments in this area. While the 27 days of data provides many pixel samples of the cloud types present at a particular hour, the question to be answered here was whether the samples collected on particular types of clouds sufficiently represent the variations of that cloud that can appear on a different day. The promising results point to the applicability of neural networks for automated generation of meteorological products in real time.

Abstract: Satellite remote sensing was first introduced to Sri Lanka in the late 1970s with the launch of the Landsat satellites. The author discusses the use of remote sensing for this country. Some of the topics discussed are: (a) in a well-mapped country is satellite imagery required? (b) cost of data (c) resolution of the data (d) timely availability of data (e) availability of cloud free data in the equator (f) digital equipment required and the maintenance of such equipment (g) the software required and the maintenance of it. >

Abstract: A number of problems of aerosol/cloud and radiation/cloud interactions, as well as cloud chemistry, related to climate change study, which could be addressed with 3-D cloud structure models which incorporate a detailed `inventory' of physical processes. Also, cloud remote sensing problems can be sensitive to the 3-D structure of clouds. Those problems motivate us to develop a 3-D Large Eddy Simulation model with explicit description of cloud microphysical processes. The model output contains fields of aerosol and drop size distributions, among other output parameters. Some results of recent model runs are presented. In order to study a 3-D radiance response of the system we derive a `two-stream' approximation of radiative transfer for a 3-D inhomogeneous medium based on a 3-D delta- Eddington method. The basic equations of the method are derived and the solution method is outlined. Relevance of the model to investigation of arctic stratus layers is discussed.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Abstract: The radiation field over a broken stratocumulus cloud deck is simulated by the Monte Carlo method. We conducted four experiments to investigate the main factor for the observed shortwave reflectively over the FIRE flight 2 leg 5, in which reflectivity decreases almost linearly from the cloud center to cloud edge while the cloud top height and the brightness temperature remain almost constant through out the clouds. From our results, the geometry effect, however, did not contribute significantly to what has been observed. We found that the variation of the volume extinction coefficient as a function of its relative position in the cloud affects the reflectivity efficiently. Additional check of the brightness temperature of each experiment also confirms this conclusion. The cloud microphysical data showed some interesting features. We found that the cloud droplet spectrum is nearly log-normal distributed when the clouds were solid. However, whether the shift of cloud droplet spectrum toward the larger end is not certain. The decrease of number density from cloud center to cloud edges seems to have more significant effects on the optical properties.

Abstract: In this article, we present the first maps of the global distribution of the cloud liquid and ice water contents of the atmosphere. It is shown that the cloud microphysics package produces realistic distributions of both moisture variables. We axe presently adapting the present model so that long-term simulations with the CSU GCM may be made. In the near future, we plan to couple the cloud liquid and ice water contents prognosed by the cloud microphysics package with the cloud fraction and cloud optical properties.

Abstract: Radio emission of cloud l a er on cm and mm waves contains f l u c t u a t i o n com onent whicl i s connected with inhomogeneity of t h e l a y e r an: reflects t h e turbulen t charac te r of moving i n l a y e r . As t h e o p t i c a l depth of clouds on microwaves less than unit t h e s e f l u c t u a t i o n s are determined by t h e whole s t r u c t u r e of t h e l a y e r as complete. Analysis of t h e s e f l u c t u a t i o n s g ives a p o s s i b i l i t y t o determine such characteristics of cloud l a y e r as thickness and displacement ve loc i ty .