Showing papers on "Cloud computing published in 1983"

The International Satellite Cloud Climatology Project (ISCCP): The First Project of the World Climate Research Programme

Abstract: The first project of the World Climate Research Program is the International Satellite Cloud Climatology Project, (ISCCP) whose objective is the collection and analysis of satellite radiance data in order to infer the global distribution of cloud radiative properties and improve the modeling of cloud effects on climate. The operational component of ISCCP takes advantage of the global coverage provided by the current and planned international array of geostationary and polar-orbiting meteorological satellites in the 1980s. It will produce a five-year global radiance and cloud data set. The research component of ISCCP will coordinate studies to validate climatology, improve cloud analysis algorithms, improve cloud effects modelling, and investigate the role of clouds in the atmospheric radiation budget and hydrologic cycle.

Improved Cloud Motion Wind Vector and Altitude Assignment Using VAS.

Abstract: A CO2 cloud tracking technique to determine simultaneous heights and velocities of cloud motion winds is presented. Using animated CO2 channel imagery from VAS, multi-level cloud situations are separated into high, middle and low level cloud motion wind vectors by the CO2 slicing method. The VAS CO2 channel radiometric values are used in the CO2 absorption method to assign quantitative heights to the cloud vectors; cloud top pressures are determined from the ratio of the deviations in cloud produced radiances and the corresponding clear air values for three CO2 channels in a radiative transfer equation formulation. Two case studies are presented that show CO2 cloud-motion wind vectors to be in good agreement with radiosonde wind observations and CO2 cloud heights to be within a 50 mb rms deviation of radiosonde, bispectral and stereo height determinations.

The Effect of Spatial and Temporal Averaging on Sampling Strategies for Cloud Amount Data

Abstract: Sampling and averaging strategies are as significant an influence upon the resulting cloud climatologies as the resolution of the original cloud archives. An investigation of total cloud amount data, as represented by the U.S. Air Force 3-dimensional nephanalysis, illustrates the effects of temporal and spatial processing. Analysis of mean cloud amount as a function of the standard deviation provides a quantitative method for determining cloud size and assessing regional time series of variability. Careful definition of spatially and temporally homogeneous cloud climatology regions facilitates stratified sampling and could obviate the need for averaged data.

Synoptic cloud variations in a low resolution spectral atmospheric model

Abstract: A spectral model of low resolution (two vertical levels and rhomboidal wave number truncation 15) has been used in simulations of January and July climatologies. The model has self-generated cloud cover, and it is this aspect that is detailed in this report. The emphasis on cloud production has been chosen partly because of a noticeable lack of detailed information on cloud production from the few other models with self-generated cloud. The cloud covers produced by each simulation are intercompared by use of global mean values, zonal values, through to instantaneous cloud production. It is found that the two simulations have rather different spatial and temporal characteristics. The global mean cloud cover shows much less variability between seasons than the hemispheric means, implying some stability in global cloud cover.

Application of microwave remote sensing to studies of sea ice

Abstract: Monitoring of snow and ice is of importance for meteorological and climate research and applications, for hydrological purposes and for navigation and offshore activity in polar regions. For some of these applications long-term monitoring on a mesoscale and a synoptic scale is sufficient, whereas other applications require short-term observation on a mesoscale. This applies especially to forecasting of sea ice conditions, for instance. In the latter cases microwave remote sensing is the only technique that may deliver reliable and timely data irrespective of light, weather and cloud conditions. In the polar regions, this feature is of utmost importance. All known microwave remote-sensing techniques have demonstrated their applicability in polar regions, in particular in connection with observations of sea ice. It has also been shown that a combination of simultaneously acquired data from different sensors may be of advantage in parameter retrieval. This paper reviews the monitoring requirements and the microwave techniques available for this purpose with a view to snow and sea ice research and applications.

Model of solar radiation using total cloud cover and percentage sunshine measurements

Abstract: The solar radiation model developed by Sherry and Justus and similar models developed by others (e.g., Suckling and Hay, 1976, 1977) use climatological data as input such as those reported by U.S. National Weather Service. These input data include the observed cloud type and the amount of cloud cover for each type at up to four different layers in the sky, as seen by an observer on the ground. The model described uses as input all the climatological data incorporated by the model of Sherry and Justus, with the exception of the reported cloud type and the corresponding cloud cover for the various layers. It uses instead only the total cloud cover without differentiation according to type of height. There are situations where total cloud cover may be the only useful cloud parameter available for modelling. These include cases in which cloud parameters are based on two-dimensional photographs like those available from satellites and from all-sky cameras. In addition, past or present reports at some stations may include only total cloud cover without detailing the amount of cover for each type of cloud.

Cloud fraction and cloud size distributions derived using Landsat Multispectral Scanner data

Abstract: Initial results are presented on the spatial structure of cumulus cloud fields derived using Landsat digital data. Techniques to determine clear, overcast, and cloud edge pixels are discussed and used to analyze four Landsat scenes. Cloud number densities, cloud cover, cloud aspect ratio, and the ratio of interior to cloud edge pixels are obtained for the four scenes and are discussed. This new application of Landsat digital data should prove useful in developing and testing models of the radiative and dynamical properties of cumulus cloud fields on GCM spatial scales.

Satellite observed cloud distribution over the Indian Ocean during the southwest monsoon season

Abstract: The cloud distribution over the Indian Ocean has been studied for the two consecutive southwest monsoon seasons of the years 1973 and 1974 with the help of cloud imagery received from NOAA-2 spacecraft in the visible and thermal infrared channels. The cloud distribution shows an interesting mean pattern and demarcates the position of Southern Hemispheric Equatorial Trough (SHET). Weak tropical disturbances which appear as amorphous convective cloud clusters are predominant in the near equatorial regions of the Indian Ocean in this season. The study reveals a negative association between the southwest monsoon activity over India and the intensity of SHET. During weak monsoon conditions over India there is intense convective activity over the Indian Ocean between equator and Lat. to Sin association with active SHET.

Cloud observations with Nimbus-7 satellite data

Abstract: A Nimbus-7 Cloud Data Processing Team was established in 1982 in order to implement cloud-related studies for as long as the spacecraft's Temperature Humidity IR radiometer and Total Ozone Mapping Spectrometer continue to operate It will soon be possible to correlate the Nimbus-7 cloud cover information with International Satellite Cloud Climatology results The production of validated Nimbus-7 cloud products was scheduled to begin in November, 1983; each year of Nimbus-7 cloud data should take about four months to produce

Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

Abstract: The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

Analysis of cloud characteristics derived from archived satellite data

Abstract: The present investigation is concerned with the differing scientific user community requirements for cloud data and the nature of archived satellite data. It is concluded that information on cloud characteristics and cloud cover is of the utmost importance for at least three scientific research areas, viz. numerical weather forecasting, environmental remote sensing, and climatic monitoring and modelling. However, these three user groups require information at different levels of temporal and spatial resolution, and the nature of the comparison between surface and satellite assessment of cloud cover differs among the three groups. Taking into account the diverse requirements of the scientific community and difficulty of a mutually agreed definition of the cloud parameters, a number of recommendations are made. It is suggested that radiance data, not cloud data, should be archived directly from satellite observations, and that the highest spatial and temporal resolutions available should be retained in the archive.