Showing papers on "Cloud computing published in 1997"

Distributed and Parallel Database Systems.

Abstract: The maturation of database management system (DBMS) technology has coincided with significant developments in distributed computing and parallel processing technologies. The end result is the development of distributed database management systems and parallel database management systems that are now the dominant data management tools for highly data-intensive applications. With the emergence of cloud computing, distributed and parallel database systems have started to converge. In this chapter, we present an overview of the distributed DBMS and parallel DBMS technologies, highlight the unique characteristics of each, and indicate the similarities between them. We also discuss the new challenges and emerging solutions.

A Prognostic Cloud Scheme for Operational NWP Models

Abstract: An explicit cloud prediction model has been developed and incorporated into the Eta Model at the National Centers for Environmental Prediction. In this scheme, only one predictive variable, cloud mixing ratio, is added to the model’s prognostic equations to represent both cloud liquid water and cloud ice. Precipitation is diagnostically calculated from cloud mixing ratio. Extensive tests have been performed. The statistical results show a significant improvement in the model precipitation forecasts. Diagnostic studies suggest that the inclusion of cloud ice is important in transferring water vapor to precipitation and in the enhancement of latent heat release; the latter subsequently affects the vertical motion field significantly.

Method and apparatus for monitoring computer systems during manufacturing, testing and in the field

Abstract: A method and apparatus for monitoring a plurality of data processing systems from a monitoring system. The data processing systems may be coupled to the monitoring system via a network cloud. When one of the plurality of data processing systems experiences a failure, the failure is detected at the monitoring system based upon communications over the network. The data processing systems may each have a service processor directly coupled to the network cloud. The monitoring system can also be employed to monitor the status of the data processing systems, either in a manufacture/test environment or in the field. The monitored status can include an inventory of parts for the data processing systems. Each part can be provided with identification information that is readable by the data processing system when the part is installed, and the identification information can be used to automatically generate an inventory of parts for each of the data processing systems. The monitoring system can also be used to automatically download an updated a piece of software to the data processing systems. In one aspect of the invention, bidirectional communication is employed between the monitoring system and the data processing systems. When an event occurs on the data processing system, the system sends a service request to the monitoring system notifying it of the event. The monitoring system also sends periodic communications to the data processing systems to ensure that each is functioning properly.

Implementation of the Cloud Prediction Scheme in the Eta Model at NCEP

Abstract: An explicit cloud prediction scheme has been developed and incorporated into the Eta Model at the National Centers for Environmental Prediction (NCEP) to improve the cloud and precipitation forecasts. In this scheme, the cloud liquid water and cloud ice are explicitly predicted by adding only one prognostic equation of cloud mixing ratio to the model. Precipitation of rain and snow in this scheme is diagnostically calculated from the predicted cloud fields. The model-predicted clouds are also used in the model’s radiation calculations. Results from the parallel tests performed at NCEP show improvements in precipitation forecasts when prognostic cloud water is included. Compared with the diagnostic clouds, the model-predicted clouds are more accurate in both amount and position. Improvements in specific humidity forecasts have also been found, especially near the surface and above the freezing level.

Protocol architecture for universal personal computing

Abstract: This paper presents a new paradigm for network computing over the Internet called universal personal computing, where mobile users can access computing resources, network services, and personalized computing environments anywhere using any available terminals The user and system requirements are defined, and an agent-based protocol architecture required to manage different mobile objects, ie, users and terminals, in this computing environment is presented Modifications of connection setup procedures between user application programs to enable addressing based on a global user identity are considered The use of personal agents to facilitate interworking and management functions is proposed

Virtual circuit switching architecture

Abstract: A virtual architecture for enabling direct point-to-point communications between any processes on a network cloud utilizes a process record in which information relevant to the process is stored and propagated through a parent/child hierarchy of connection service processes and information service processes. Process records and information relating to processes are propagated throughout private clouds, public clouds and interconnecting global services to facilitate both activity based network routing and load based network routing without the use of predetermined network routing mechanisms.

Lagrangian approach for deriving cloud characteristics from satellite observations and its implications to cloud parameterization

Abstract: A Lagrangian view is adopted for establishing the spatiotemporal cloud statistics and the scale dependent radiative properties using satellite data. Individual clouds are identified using a newly developed scheme. We sort all clouds by cloud type, cloud area, and number of clouds in each area bin, as well as their radiative properties. For seven different cloud types our analyses provide radiative properties, such as albedo and cloud top temperature, as a function of the cloud spatial scale. All clouds are marked by local time, and large clouds are tracked over time. These analyses provide diurnal variability, lifetimes, and evolution of cloud systems as a function of their spatial scales. These scale dependent cloud properties can be objectively used in guiding the development and evaluation of cloud parameterization in global climate models (GCMs). Particularly, we show how our Lagrangian approach can be used to establish the relative importance of resolvable and fully parameterized clouds to the total cloudy area and to the total amount of reflected visible irradiance. Focus in this 1 month satellite study is on the convective-stratiform cloud systems over the western and central tropical Pacific Ocean, including the so-called warm pool. We adopt the hourly Japanese geostationary satellite (GMS) window channel radiances in the visible and IR window region for cloud classification and characterization. To study the radiative contributions of different clouds in the area, we computed the bidirectional model (BDM) for the Visible and Infrared Spin Scan Radiometer instrument aboard GMS, which we show to agree well with the BDM of the Earth Radiation Budget instrument aboard the Nimbus 7 satellite. An iterative two-stage cloud detection scheme was developed to identify individual clouds. Furthermore, a tracking algorithm was developed to study the time evolution of mesoscale convective systems (MCS). It operates on area and orientationally equivalent ellipsoidal representations of these MCS. We show that the temporal statistics of these convective anvil clouds show good agreement with those reported in the literature. Our data indicate that for the convective-stratiform systems in the tropical Pacific, 95% of the radiatively important clouds (containing a core with an effective brightness temperature <219 K) are of scales resolvable by a GCM of about 50 km × 50 km. On the other hand, a GCM of 250 km × 250 km will only be able to resolve 50% of the radiatively important clouds. This, however, does not mean that the processes responsible for the formation and maintenance of these systems are also resolvable. The low clouds that are unattached to convective-stratiform systems are mostly unresolvable by available GCMs.

Vertical stratification of tropical cloud properties as determined from satellite

Abstract: A new retrieval scheme is developed to infer tropical cloud properties and vertical structure, including liquid and ice water content, cloud top and base, and cloud layering. The retrieval scheme utilizes a cloud classification scheme that uses both International Satellite Cloud Climatology Project (ISCCP) cloud top temperature and a microwave index from the special sensor microwave/imager (SSM/I). Different cloud classes have different allowed numbers of cloud layers. The retrieval scheme also incorporates findings from observational studies. When multiple liquid layers are judged to be possible, a “cloudiness likelihood” parameter is used to determine the priority for the presence of liquid layer at each level, based on the European Centre for Medium-Range Weather Forecasts analyzed relative humidity field. Cloud liquid water path is determined using a microwave satellite retrieval. In case of multiple liquid layers, the liquid water path is partitioned and assigned to each liquid layer in proportion to the adiabatic liquid water path in each layer. Depending on the cloud class, ice water paths are determined using one of the following methods: (1) ISCCP ice optical depth; (2) a microwave ice retrieval that uses ice scattering signals at high SSM/I frequencies; and (3) a residual method that infers ice from the difference between a “virtual” liquid water path derived from ISCCP total optical depth and the true liquid water path determined from SSM/I. The retrieved cloud layering is indirectly validated using cloud cooccurrence climatology from surface observations. The cloud base retrieval is compared with lidar measurements obtained during the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment.

Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation

Abstract: Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

The NASA DC-8 airborne cloud radar: design and preliminary results

Abstract: The University of Massachusetts Microwave Remote Sensing Laboratory and NASA Jet Propulsion Laboratory have developed a 95 GHz airborne radar system for remote sensing of clouds. This instrument was recently operated aboard NASA's DC-8 Airborne Laboratory and participated in the Cloud Layer Experiment (CLEX) in the central U.S. and in the Southern Alps Experiment (SALPEX) in New Zealand. The development of this system was motivated by the need for a sensitive, well-calibrated millimeter-wave cloud radar that can probe clouds from above. This geometry avoids the attenuation suffered by ground based systems that look up through precipitation and also simulates the viewing geometry of a spaceborne sensor. This paper describes the design and operating characteristics of the instrument as well as preliminary results from the initial deployments. Engineering test flights were conducted during June 1996, concurrent with CLEX. The instrument also collected data during two flights from California to Hawaii and New Zealand and another flight near New Zealand. Data from the flights are used to demonstrate the instruments capabilities. The data from both experiments are classified into the four classes of cloud systems used by the GEWEX Cloud System Study (GCSS). Reflectivity statistics for each class of cloud system are presented.

Modeling and Characterization of Cloud Dynamics

Abstract: Cloud dynamics plays an important role in the climate system, weather forecast, geophysics, and so on. However this elementary process in meteorology is very much complicated because it consists of different time and space scales and the phase transition from condensed phase to gas is coupled with the motion of atmosphere. Even if the flow of the atmosphere were known with accuracy using the Navier-Stokes equation, we could not discuss the morphology of clouds. In order to investigate such a complex system, construction of a phenomenological model is essential. In this Letter, we introduce a model of cloud formation which reproduces the diversity of cloud patterns. Characterizations of four cloud phases are also given.

Application REQuested IP over ATM (AREQUIPA)

Abstract: This document specifies a method for allowing ATM-attached hosts that have direct ATM connectivity to set up end-to-end IP over ATM connections within the reachable ATM cloud, on request from applications, and for the exclusive use by the requesting applications. This allows the requesting applications to benefit in a straightforward way from ATM's inherent ability to guarantee the quality of service (QoS).

Water vapour profile retrievals from SSM/T-2 data constrained by infrared-based cloud parameters

Abstract: An algorithm has been developed for the retrieval of water vapour profiles from passive microwave observations near 183GHz. The algorithm treats clouds explicitly and can incorporate cloud information from other sources. As a test, the algorithm has been configured to use data from the SSM /T-2 on the DMSP polar orbiting satellite series. Cloud top temperature and phase information have been derived from the AVHRR on the NOAA polar orbiting satellite series. Obtaining suitable coincidences between the SSM /T-2 and the AVHRR is challenging but two reasonable cases have been found. In one case, a liquid cloud injected into the retrieval results in significant improvement in the accuracy and vertical resolution in the neighbourhood of the cloud top. A cloud base is a by-product of the algorithm, but its validity has yet to be established. In the other case, a cirrus cloud injected into the algorithm resulted in little change in the retrieval which indicates that the algorithm was performing well in the cloud...

Method and apparatus for implementing a remote mirroring data facility without employing a dedicated leased line to form the link between two remotely disposed storage devices

Abstract: A method and apparatus for implementing a remote mirroring data facility for a computer system comprising a central processing unit (CPU); a first storage system that is coupled to the CPU so that the CPU can store information in the first storage system; a second storage system coupled to the CPU via a communication link; and a mirroring controller to mirror at least some of the information stored in the first storage system in the second storage system by transferring the at least some of the information over the communication link. The communication link can be implemented via a network cloud, which may be the Internet or an intranet. Multiple pipes can be used to pass data through the network cloud in parallel. Alternatively, the communication link can be implemented using wireless technology.

Man–computer interactive method on cloud classification based on bispectral satellite imagery

Abstract: A bispectral cloud classification method based on man-computer interactive way, i.e. a unit feature space classification method (UFSCM), has been presented in this paper. Apart from land and water, six types of clouds including cumulonimbus, multilayer cloud system, thin / think cirrus, middle and low level clouds are recognized. The method has been tested by using more than two hundred samples, with total accuracy reaching 87.1 %.

Climatic variability of cloud radiative forcing

Abstract: Multiple-regression models have been developed relating interannual departures of the Earth Radiation Budget Satellite net, long-wave, and short-wave cloud radiative forcing primarily to variations in the International Satellite Cloud Climatology Project cloud amounts for low, middle and high clouds, and cloud water. These models are used to evaluate the effects on cloud radiative forcing of specified and observed changes in cloud properties. The calculated changes of cloud forcing due to 16.5% increases in low-, middleand high-cloud amounts and 25% increases in cloud water are compared with those of a radiative-transfer model. the two methods have results which agree with respect to the signs of the responses and the order of the significance of the independent variables for net cloud forcing. Overall, variations in cloud water have the largest effect on net cloud forcing; those in high cloud have the largest effect on long-wave cloud forcing; those in cloud water make the largest contributions to short-wave cloud forcing. Using the statistical models forced by one-standard-deviation variations in cloud properties, variations in high cloud are shown to have increased importance relative to the results for the 16.5 and 25% perturbations. In addition, variations in clear-sky planetary albedo and long-wave flux are also found to be important at higher latitudes. In a small sample of observed short-term climate-change scenarios, compensations amongst the effects of the variables alter the magnitude, and in two cases the sign, of the change in net cloud forcing relative to those resulting from uniform variations of the cloud properties.

Incorporation of a Cloud Simulation into a Flight Mission Rehearsal System: Prototype Demonstration.

Abstract: One environmental parameter that has a large impact on aircraft missions for the U.S. military is clouds. This article describes an initial attempt to incorporate physically consistent clouds into a flight mission rehearsal system. A cloud model is used to generate cloud information that is visually incorporated into the PowerScene mission rehearsal system. PowerScene incorporates off-the-shelf hardware to provide photo realism to a wide range of applications, including mission planning, previewing, rehearsing, debriefing, and training. Implementation of this approach would allow the user to train in both clear and cloudy conditions and to evaluate the impact of clouds on the mission. The cloud model is briefly described, as are the basic visualization approach, the prototype implementation, and the work remaining to fully integrate these features into PowerScene.

Sampling Errors and Bias in Satellite-Derived Fractional Cloud Cover Estimates from Exponential and Deterministic Cloud Fields as a Consequence of Instrument Pixel Size and Number

Abstract: The proposed European Space Agency’s cloud profiling radar Millimetre Active Cloud Structure Imaging Mission is a nadir-pointing radar with a 1-km footprint; it will need to integrate the received signal power for a reasonable amount of time (1.4–14 s) along track to detect a cloud. As a result, the radar will provide a set of long (10–100 km) narrow pixels that are registered either as cloudy or as clear, depending on how much cloud there is in each. These are thus likely to give a biased estimate of fractional cloud cover over a region because the radar will be unable to detect small clouds or gaps. For a nadir-pointing radar the clouds and gaps essentially form a 1D sequence that can be modeled by a general single-server queue. This model allows analytical expressions to be found for the bias and sampling error in specific cases. Such expressions are presented for the two extremes of the Erlang queuing model, that is, for an exponential and a deterministic queue. These are then compared to res...

Validation of automated cloud top phase algorithms: distinguishing between cirrus clouds and snow in a priori analyses of AVHRR imagery

Abstract: Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create these a priori analyses for the evaluation of cloud detection algorithms is relatively straightforward, although the task becomes more complicated when little spectral signature is evident between a cloud and its background, as appears to be the case in advanced very high resolution radiometer (AVHRR) imagery when thin cirrus is present over snow-covered surfaces. In addition, complex procedures are needed to help the analyst distinguish between water and ice cloud tops to construct the manual cloud top phase analyses and to ensure that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. Procedures are described that enhance the researcher’s ability to (1) distinguish between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery, (2) construct accurate a priori cloud top phase manual analyses, and (3) quantitatively validate the performance of both automated cloud detection and cloud top phase classification algorithms. The methodology uses all AVHRR spectral bands, including a band derived from the daytime 3.7-?m channel, which has proven most valuable for discriminating between thin cirrus clouds and snow. It is concluded that while the 1.6-?m band is needed to distinguish between snow and water clouds in daytime data, the 3.7-?m channel remains essential during the daytime to differentiate between thin ice clouds and snow. Unfortunately this capability that may be lost if the 3.7-?m data switches to a nighttimeonly transmission with the launch of future National Oceanographic and Atmospheric Administration (NOAA) satellites.

Data and image fusion for geometrical cloud characterization

Abstract: Clouds have a strong influence on the Earth`s climate and therefore on climate change. An important step in improving the accuracy of models that predict global climate change, general circulation models, is improving the parameterization of clouds and cloud-radiation interactions. Improvements in the next generation models will likely include the effect of cloud geometry on the cloud-radiation parameterizations. We have developed and report here methods for characterizing the geometrical features and three-dimensional properties of clouds that could be of significant value in developing these new parameterizations. We developed and report here a means of generating and imaging synthetic clouds which we used to test our characterization algorithms; a method for using Taylor`s hypotheses to infer spatial averages from temporal averages of cloud properties; a computer method for automatically classifying cloud types in an image; and a method for producing numerical three-dimensional renderings of cloud fields based on the fusion of ground-based and satellite images together with meteorological data.

Cloud Cover Predictions Diagnosed from Global Numerical Weather Prediction Model Forecasts.

Abstract: : We developed statistical relationships between fractional cloud cover and a collection of variables drawn from forecast fields from a global numerical weather prediction model. These relationships were then applied to later forecasts from the same weather prediction model to diagnose the cloud cover corresponding to the forecast states. The U.S. Air Force RTNEPH cloud analysis datasets in the Northern Hemisphere for January and July 1991 were used to represent cloud cover in separate winter and summer statistical relationship developments. Forecasts from the Phillips Laboratory Global Spectral Model at times corresponding to the cloud analyses were used to provide the weather model predictors. We used multiple linear regression and a hybrid regression estimation of event possibilities/multiple linear regression to develop the statistical relationships in the 5 percent cloud amount categories from 0 to 100 percent. We used multiple discriminant analysis with six cloud amount categories covering the range from 0 to 100 percent. Separate relationships were developed over 10-day periods for low, middle, and high cloud decks, and total cloud. The relationships developed were also distinct for different forecast durations. All relationships were applied to forecasts initialized on the day following the 10-day development period. Our results showed that multiple linear regression produced forecast diagnoses of cloud amount that were slightly better than the other methods in root-mean-square error. This method also modified the frequency distribution of cloud cover from that of the analysis. The hybrid method improved upon the frequency distribution of clear and overcast, but worsened the near-clear and near-overcast categories. Multiple discriminant analysis produced cloud cover diagnoses with the best combination of root-mean-square skill and preservation of the freque

Visualization of dense cloud radiation data in modeling and simulations

Abstract: Visualization technologies are improving our ability to assess the effectiveness of the warfighter on today's battlefield. Increasingly, our ability to predict the behavior and performance of competing systems is being facilitated by simulations. These predictions typically involve visual and sensor simulations, but they may also be used for mission performance generalizations. A key link in this analysis involves the assessment of real optics, ATR algorithms, and observers under the changing influence of the natural atmosphere. The effects of the atmosphere can be as diverse as target contrast degradation, dynamic range influences of light and shadows in the viewed field, cloud free lines of sight, and optical turbulence. However, in general, the modeling and simulation community has only treated limited versions of the full influences of the atmosphere. In some cases these influences have been modeled using cartoon-like emulations of reality, bereft of physical content. Physics-based solutions are usually bypassed in the drive for near-realtime results. In this paper, we discuss the need for three-dimensional (3-D) solutions to near-earth atmospheric representation, describe a set of physics-based programs designed to generate cloudy- hazy atmospheric scenarios, run a robust 3-D radiative transfer (RT) model, and present this representation for visualization by a perspective view generator of the resulting radiance fields. The cloud fields are generated with a stochastic model that uses cloud layer height information, cloud type, and vertical sounding profile data. The output from this model is coupled to standard vertical haze profiles to produce a 3-D field of atmospheric properties. The official Army Research Laboratory discrete ordinates method (DOM) RT code, contained in the WAVES modeling package, has difficulties with dense cloud conditions. Here, we discuss a recommended upgrade to WAVES in the form of a specially designed RT code that accesses these cloud/haze data and is insensitive to cloud density variations. This feature allows it to effectively simulate effects in and around natural clouds. Further processing compresses and interprets the outputs of the RT code for a given sensor spectral response. Point to point calculations can then be performed on the resulting database for path characterization, including path radiance and contrast transmission calculations. These can be used in assessing system performance for each color channel of a sensor, or in visualizing the cloud fields themselves.

Preprint of the Cloud Impacts on DoD Operations and Systems 1997 Conference (CIDOS-97), U.S. Naval War College - Sims Hall, Nolt Auditorium Newport, Rhode Island, 23-25 September 1997.

Abstract: : The Tri-Service Cloud Modeling Program was established by OUSDRE (2) Program Reviews; (3) Cloud MS (4) Cloud and Cloud Effects Modeling; (5) Cloud Prediction; (6) Measurement Systems and Sensors; (7) Cloud Datasets Summaries of these presentations are included in this report