Showing papers on "Cloud computing published in 1998"

Discriminating clear sky from clouds with MODIS

Abstract: The MODIS cloud mask uses several cloud detection tests to indicate a level of confidence that the MEDIS is observing clear skies. It will be produced globally at single-pixel resolution; the algorithm uses as many as 14 of the MEDIS 36 spectral bands to maximize reliable cloud detection and to mitigate past difficulties experienced by sensors with coarser spatial resolution or fewer spectral bands. The MEDIS cloud mask is ancillary input to MEDIS land, ocean, and atmosphere science algorithms to suggest processing options. The MEDIS cloud mask algorithm will operate in near real time in a limited computer processing and storage facility with simple easy-to-follow algorithm paths. The MEDIS cloud mask algorithm identifies several conceptual domains according to surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. Once a pixel has been assigned to a particular domain (defining an algorithm path), a series of threshold tests attempts to detect the presence of clouds in the instrument field of view. Each cloud detection test returns a confidence level that the pixel is clear ranging in value from 1 (high) to zero (low). There are several types of tests, where detection of different cloud conditions relies on different tests. Tests capable of detecting similar cloud conditions are grouped together. While these groups are arranged so that independence between them is maximized, few, if any, spectral tests are completely independent. The minimum confidence from all tests within a group is taken to be representative of that group. These confidences indicate absence of particular cloud types. The product of all the group confidences is used to determine the confidence of finding clear-sky conditions. This paper outlines the MEDIS cloud masking algorithm. While no present sensor has all of the spectral bands necessary for testing the complete MEDIS cloud mask, initial validation of some of the individual cloud tests is presented using existing remote sensing data sets.

A Comparison of the CCM3 Model Climate Using Diagnosed and Predicted Condensate Parameterizations

Abstract: A parameterization is introduced for the prediction of cloud water in the National Center for Atmospheric Research Community Climate Model version 3 (CCM3). The new parameterization makes a much closer connection between the meteorological processes that determine condensate formation and the condensate amount. The parameterization removes some constraints from the simulation by allowing a substantially wider range of variation in condensate amount than in the standard CCM3 and tying the condensate amount to local physical processes. The parameterization also allows cloud drops to form prior to the onset of grid-box saturation and can require a significant length of time to convert condensate to a precipitable form, or to remove the condensate. The free parameters of the scheme were adjusted to provide reasonable agreement with top of atmosphere and surface fluxes of energy. The parameterization was evaluated by a comparison with satellite and in situ measures of liquid and ice cloud amounts. The...

Data-intensive computing

Abstract: Computational grids provide access to distributed compute resources and distributed data resources, creating unique opportunities for improved access to information. When data repositories are accessible from any platform, applications can be developed that support nontraditional uses of computing resources. Environments thus enabled include knowledge networks, in which researchers collaborate on common problems by publishing results in digital libraries, and digital government, in which policy decisions are based on knowledge gleaned from teams of experts accessing distributed data repositories. In both cases, users access data that has been turned into information through the addition of metadata that describes its origin and quality. Information-based computing within computational grids will enable collective advances in knowledge [396]. In this view of the applications that will dominate in the future, application development will be driven by the need to process and analyze information , rather than the need to simulate a physical process. In addition to accessing specific data sets, applications will need to use information discovery interfaces [138] and dynamically determine which data sets to process. In Section 5.1, we discuss how these applications will evolve, and we illustrate their new capabilities by presenting projects now under way that use some concepts implicit within grid environments. Data-intensive applications that will require the manipulation of terabytes of data aggregated across hundreds of files range from comparisons of numerical simulation output, to analyses of satellite observation data streams, to searches for homologous structures

A cloud monitoring system for remote sites

Abstract: A cloud monitor has been developed for use with cosmic ray air shower fluorescence detectors, the High Resolution Fly's Eye and the Pierre Auger Observatory. This is based on an infrared thermopile device which, unlike previous such monitors, requires no moving chopper and is suitable for unattended operation over long periods of time.

Mining Association Rules with Linguistic Cloud Models

Abstract: Mining asociation rules is an important issue in KDD applications. Since it was introduced by Agrawal et al., various algorithms have been proposed and developed. But studies on knowledge representation and uncertainty handling in mining of association rules are seldom reported. In this paper, we describe the linguistic cloud model and extend it to two and multi-dimensional ones and explore the application of cloud models in minig association rules at any concept level or at multiple concept levels by combining with Apriori algorithm.

Midlatitude cyclonic cloud systems and their features affecting large scales and climate

Abstract: Midlatitude cyclonic cloud systems are common occurrences that significantly impact our climate. In this review, attention is paid to those physical characteristics of these cloud systems with large-scale impacts that must be accounted for in climate simulations. Such attributes include atmospheric forcing, internal structure, surface influences, cloud layering, microphysics, precipitation, water cycling, and radiation. Because of their present limitations associated with, for example, grid sizes and simplified parameterizations, climate models cannot account for all the crucial impacts of these cloud systems. Future advances in the representation of these systems within climate models will need to rely in part on rigorous assessments of model capabilities in a variety of conditions.

Distributed virtual machines: a system architecture for network computing

Abstract: Modern virtual machines, such as Java and Inferno, are emerging as network computing platforms. While today’s virtual machines provide higher-level abstractions and more sophisticated services than their predecessors, and while they have migrated from dedicated mainframes to heterogeneous networked computers, their architecture has essentially remained intact. State of the art virtual machines are still monolithic, that is, all system components reside on the same host and are replicated among all clients in an organization. This crude replication of services among clients creates problems of security, manageability, performance and scalability. We propose a distributed architecture for virtual machines based on distributed service components. In our proposed system, services that control security, resource management, and code optimization are factored out of clients and reside in enterprisewide network servers. The services produce self-certifying, self-regulating, selfoptimizing programs via binary rewriting. We are currently building a Java virtual machine based on this architecture. We argue that distributed virtual machine architectures enable higher integrity, manageability, performance and scalability than monolithic virtual machines where all components reside on all clients.

Significant changes between the ISCCP C and D cloud climatologies

Abstract: We analyse one year of cloud data from the ISCCP C and D datasets. The two datasets differ by their retrieval algorithms and their definitions of the cloud types defined from the cloud top pressure and cloud optical depth. The differences between the two datasets are first described in terms of the total cloud cover, as well as its repartition in low, middle, and high level cloudiness. We also project the ISCCP C cloud classes into the ISCCP D cloud types to circumvent the problem of different cloud type definitions in the two datasets. The differences between the two datasets are then also investigated in terms of the most frequent cloud type.

Cloud-Top Heights from GOES-8 and GOES-9 Stereoscopic Imagery

Abstract: Operational satellite data from GOES-8 and GOES-9 were used to make stereoscopic measurements of cloud heights during the National Aeronautics and Space Administration’s Subsonic Aircraft: Contrail and Cloud Effects Special Study program. The stereoscopic data were used to differentiate between boundary layer wave clouds and cirrus in the mid- and upper troposphere. This separation was difficult to evaluate from radiometric data alone. Stereographic cloud height analysis provided a definitive result. The technique used for calculating cloud heights is described. GOES-8 and -9 data were better suited for stereoscopic measurements than data from previous satellites.

Remotely sensing cloud properties from microwave radiometric observations by using a modeled cloud database

Abstract: As a first step for remote sensing cloud properties, a database of cloud genera has been established. This is derived from a microphysical model, and it considers the statistical profiles of four hydrometeor species for each cloud genus. From this database the corresponding radiative database is obtained making use of a radiative transfer model, so for each cloud genus the simulated microwave response at the special sensor microwave imager channels is found. The cloud and radiative databases allow the retrieval of the genera of the cloud and other relevant properties from satellite observations. An automatic cloud genus classifier has also been implemented. Several tests have been carried out, and the results are presented.

DISCWorld: A Distributed High Performance Computing Environment

Abstract: An increasing number of science and engineering applications require distributed and parallel computing resources to satisfy user response-time requirements. Distributed science and engineering applications require a high performance “middleware” which will both allow the embedding of legacy applications as well as enable new distributed programs, and which allows the best use of existing and specialised (parallel) computing resources. We are developing a distributed information systems control environment which will meet the needs of a middleware for scientific applications. We describe our DISCWorld system and some of its key attributes. A critical attribute is architecture scalability. We discuss DISCWorld in the context of some existing middleware systems such as CORBA and other distributed computing research systems such as Legion and Globus. Our approach is to embed applications in the middleware as services, which can be chained together. User interfaces are provided in the form of Java Applets downloadable across the World Wide Web. These form a gateway for user-requests to be transmitted into a semi-opaque “cloud” of high-performance resources for distributed execution.

On the application of the classic Kessler and Berry schemes in Large Eddy Simulation models with a particular emphasis on cloud autoconversion, the onset time of precipitation and droplet evaporation

Abstract: Many Large Eddy Simulation (LES) models use the classic Kessler parameterisation either as it is or in a modified form to model the process of cloud water autoconversion into precipitation. The Kessler scheme, being linear, is particularly useful and is computationally straightforward to implement. However, a major limitation with this scheme lies in its inability to predict different autoconversion rates for maritime and continental clouds. In contrast, the Berry formulation overcomes this difficulty, although it is cubic. Due to their different forms, it is difficult to match the two solutions to each other. In this paper we single out the processes of cloud conversion and accretion operating in a deep model cloud and neglect the advection terms for simplicity. This facilitates exact analytical integration and we are able to derive new expressions for the time of onset of precipitation using both the Kessler and Berry formulations. We then discuss the conditions when the two schemes are equivalent. Finally, we also critically examine the process of droplet evaporation within the framework of the classic Kessler scheme. We improve the existing parameterisation with an accurate estimation of the diffusional mass transport of water vapour. We then demonstrate the overall robustness of our calculations by comparing our results with the experimental observations of Beard and Pruppacher, and find excellent agreement.

Multiple satellites diversity characteristics in snowing climate and system application for 14/12 GHz band

Abstract: This paper deals with multiple satellite diversity (Sat. D) characteristics using six different orbital position satellites in a snowing climate. Six down-link signals are measured by a spectrum analyzer and diversity gains are obtained by a Sat. D simulation program. Diversity gains for all satellite combinations are examined and it can be clarified that there are two kinds of diversity characteristics, i.e., a good diversity characteristics case and a poor diversity characteristics case. These results are caused by the difference in satellite transponder characteristics, differences in snow cloud movement, topographical conditions near the Earth-station and wind-direction etc. Furthermore, satellite transponder utilization strategies for the Sat. D system are considered. By using the advantage of long distance site-diversity characteristics, transponder sharing between a large number of Earth-stations in the system can be achieved. In this case, only a small number of the Sat. D transponders (almost 10:1) is sufficient for the Sat. D system.

Help design challenges in network computing

Abstract: This paper tells what network computing is, why it is important to Help developers, and what the implications are for online Help design.

Cloud movement detection for satellite images

Abstract: The ever-increasing amount of information available to meteorologists has led to a better understanding of weather forecasting. The ability to automatically detect and estimate cloud segment speed and direction in a weather satellite would be very useful in forecasts of future weather events. The objective of this research is to extract a particular cloud segment from a sequence of infrared satellite images, and detect cloud movement and calculate its speed and direction. The difference centroid algorithm is employed to detect the movement of the cloud segment. Cloud speed and direction are then calculated by finding centroid displacement between cloud segments.

Cloud Distribution Statistics from LITE

Abstract: The Lidar In-Space Technology Experiment (LITE) mission has demonstrated the utility of spaceborne lidar in observing multilayer clouds and has provided a dataset showing the distribution of tropospheric clouds and aerosols. These unambiguous observations of the vertical distribution of clouds will allow improved verification of current cloud climatologies and GCM cloud parameterizations. Although there is now great interest in cloud profiling radar, operating in the mm-wave region, for the spacebased observation of cloud heights the results of the LITE mission have shown that satellite lidars can also make significant contributions in this area.

Simulation of satellite lidar and radiometer retrievals of a general circulation model three‐dimensional cloud data set

Abstract: The inclusion of a backscatter lidar on a space platform for a radiation mission, as proposed by various space agencies, aims to bring new information on three-dimensional cloud distribution, with a special emphasis on optically thin cirrus clouds, which are presently poorly detected by passive sensors. Key issues for such cloud observational studies are the detection of multilayered cloud systems, thin cirrus, and fractional cloud cover, knowledge that would improve our understanding of the global radiation budget. To assess the impact of such lidar measurements on cloud climatology, a 1 month cloud data set has been simulated with a general circulation model (GCM). The cloud detection capability of a spaceborne scanning backscatter lidar is assessed with the use of two detection schemes, one based on limitations in the detected cloud optical depth and the other based on lidar signal-to-noise ratio. The cloud information retrieved from passive radiometric measurements using a procedure like that used in the International Satellite Cloud Climatology Project is also simulated from the same GCM cloud data set. It is shown that a spaceborne backscatter lidar can improve significantly the retrieval of thin cirrus clouds as well as underlying cloud layers. High-level cloud retrieval from a spaceborne lidar therefore appears as a powerful complement to radiometric measurements for improving our knowledge of actual cloud climatology.

Application of evolutionary techniques to temporal classification of cloud systems using satellite imagery

Abstract: The objective of this research is to automate the classification of the temporal behavior of storm cloud systems based on measurements derived from consecutive satellite images The motivation behind this study is to develop improved descriptions of cloud dynamics which can be used in general circulation models for prediction of global climate change Analysis was applied to the International Satellite Cloud Climatology Project (ISCCP) low resolution cloud top pressure database for the first six days in April 1989 A total of 296 midlatitude storm cloud components were tracked between consecutive 3-hour time frames For each pair of components, temporal correspondence events were classified as either (1) direct, (2) merge, (3) split, or (4) reject The reject class, which was used primarily to categorize pairs of unrelated systems, included storm cloud system dissipation and creation as well Statistical, neural network, and evolutionary techniques were developed for finding solutions to the storm cloud correspondence problem Evolutionary techniques applied to the problem consisted of (1) a constraint-handling hybrid evolutionary technique and (2) a genetic local search algorithm The results demonstrate the potential of evolutionary techniques to yield meteorologically feasible solutions, given appropriate constraints, to the two- frame storm tracking problem

A Study of Extinction and Star Formation in the Chamaeleon I Cloud with DENIS

Abstract: I present the first massive star count in the J band (1.25 μm) provided by DENIS in the Chamaeleon I dark cloud. These data are used to derive a high resolution map (2’) of an area of 1.5° x 3° around the centre of the cloud using an original processing which involves an adaptive grid for counting and a wavelet decomposition for noise filtering of the extinction map. The maximum extinction in this cloud is found to be 10 Av, using a normal law. Preliminary results on the study of the star formation improve our knowledge about the stellar population of the cloud. In particular, the K s luminosity function allows the estimation of the age of the stellar population of the cloud.

Estimation of cloud motion using cross—correlation

Abstract: This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.

Forecasting Applications of High-Resolution Satellite Cloud Composite Climatologies

Abstract: In this paper, the authors describe experimental forecasting tools developed from high-resolution satellite cloud composites. The satellite data were extracted from the new 5-km, hourly, global satellite database called Climatological and Historical Analysis of Clouds for Environmental Simulations (CHANCES). Analysis was focused on a region over the former Yugoslavia and Adriatic Sea during summer 1994. Cloud composite images were constructed using digital infrared data for each hour of the day. The value at each pixel in the cloud composites was the fractional coverage of cloud at that location for the season and represented its systematic variation. Composite images were also constructed for conditional probabilities of cloud 1–12 h past each hour of the day. The values at any particular pixel in the composites represented the conditional probability of cloud given an initial condition of cloudy or clear in that pixel. Data from both types of composite images were combined to produce a climatol...

Numerical modeling of altocumulus cloud layers

Abstract: Altocumulus (Ac) clouds are predominately water clouds and typically less than several hundred meters thick. Ac cloud heights are mid-level, from 2 to 8 km. Ac clouds cover large portions of the Earth and play an important role in the Earth’s energy budget through their effects on solar and infrared radiation. A two-dimensional cloud resolving model (CRM) and a one-dimensional turbulent closure model (TCM) are used to study Ac clouds with idealized initial conditions. An elevated mixed layer model (MLM) is developed and the results for the MLM are compared with results for CRM. The impacts of large-scale vertical motion, and solar and IR radiation, the utility of the TCM, the mixed layer characteristics and circulation of Ac layers, the turbulent kinetic energy (TKE) budget, and effects of relative humidify (RH) above the cloud are studied with a series of numerical simulations using the CRM and TCM. The results show that weak large-scale vertical motion may allow for a long lifetime of Ac clouds. In the nocturnal case, feedbacks between the liquid water path (LWP), IR radiation, and entrainment lead to an Ac layer with a nearly steady structure and circulation. The solar radiation in the diurnal case leads to decreases in the LWP, circulation intensity, and entrainment rate during the day. The comparison of TCM and CRM simulations suggests that TCM simulations can portray the basic characteristics of Ac clouds. The Ac convective layer includes mainly the cloud region and a shallow subcloud layer. In the Ac convective layers, the updrafts are wide and weak, whereas the downdrafts are narrow and strong. The updrafts are associated with regions of large cloud water mixing ratio, and the downdrafts with the regions of small cloud water mixing ratio. In Ac layers, the TKE is as large as in stratocumulus-topped-boundary-layer (STBL). The TKE is produced by buoyancy in the cloud region, dissipated by viscous dissipation, and redistributed upward and downward through turbulent transport. The Ac clouds become deeper when the RH above the cloud is high and can be maintained even if the RH above cloud is very low. The results and observations suggest that Ac layers are approximately wellmixed and similar to STBL. Therefore, an elevated MLM has been developed and tested for Ac layers. The Ac MLM uses a method for determining the entrainment rate at the mixed layer top that is used in many MLMs of the STBL. At the mixed layer base, the Ac mixed-layer model detrains at a rate that keeps the ratio of buoyant consumption of TKE in the subcloud layer to buoyant production in the cloud layer less than or equal to a critical value. The MLM results were good compared to the CRM results for cloud thickness, and fair for the LWP. The mixed layer magnitudes of conservative variables and flux profiles for the MLM agree reasonably to the results for the CRM.

Method for generating and using design shell for integrated circuit design

Abstract: PROBLEM TO BE SOLVED: To hold important information from the function block of IC design by analyzing a second block connected to the first block of integrated circuit design in accordance with a defined design rule through the use of circuit information in a first shell. SOLUTION: The block 300 comprises a storage element 304 (flip flop) connected to a cloud 306 and the cloud 306 gives an output path converted into the input path of the cloud 308 in the block 302 and the cloud 308 is connected to a storage element 310. The first block which is internally associated with not less than one block that is internally associated in accordance with the defined design rule is analyzed. The first shell which contains only circuit information required for the analysis of the other block in connection to the first block and shows the first lock is generated. Then, the second block connected to the first block of integrated circuit design is analyzed in accordance with the defined design rule by using circuit information in the first shell.