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Key, J.

Publications and source records attributed to Key, J..

24 records · Page 2

Cloud cover determination in polar regions from satellite imagery

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Barry, R. G.

Classification of merged AVHRR and SMMR Arctic data with neural networks

A forward-feed back-propagation neural network is used to classify merged AVHRR and SMMR summer Arctic data. Four surface and eight cloud classes are identified. Partial memberships of each pixel to each class are examined for spectral ambiguities. Classification results are compared to manual interpretations and to those determined by a supervised maximum likelihood procedure. Results indicate that a neural network approach offers advantages in ease of use, interpretability, and utility for indistinct and time-variant spectral classes.

Key, J.

Adaptation of the ISCCP cloud detection algorithm to combined AVHRR and SMMR arctic data

The International Satellite Cloud Climatology Project (ISCCP) cloud detection algorithm is applied to artic data, and modifications are suggested. Both Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data are examined. Synthetic AVHRR and SMMR data are also generated. Modifications suggested include the use of snow and ice data sets for the estimation of surface parameters, additional AVHRR channels, and surface class characteristic values when clear sky values cannot be obtained. Greatest improvement in computed cloud fraction is realized over snow and ice surfaces; over other surfaces all versions perform similarly. Since the use of SMMR for surface analysis increases the computational burden, its use may be justified only over snow and ice-covered regions.

Key, J.

Shell theory automated for rotational structures

Package of numerical integration programs static, buckling, vibration, and plastic analysis on thin sheels of revolution. Sheels may be subjected to distributed loads, concentrated line loads, and thermal strain. Outputs include stresses, displacement, plastic strains, and vibration and buckling results. Program aids design of aircraft bodies, spacecraft, submarines, and storage tanks. Written in FORTRAN IV for batch execution, program has been implemented on UNIVAC 1108.

Key, J.

Computer program for numerical analysis of stiffened shells of revolution

Programs, using Love-Reissner first-order shell theory, can analyze orthotropic thin shells of revolution subjected to unsymmetric distributed loading or concentrated line loads and thermal strains. They can perform stability or vibration analysis of thin shells of revolution subjected to axisymmetric distributed loading or concentrated line loads and thermal strains.

Key, J.

Static, stability, and dynamic analysis of shells of revolution by numerical integration - A comparison

Recent innovations in digital computer technology have enabled engineers to analyze shell structures of complex configurations without unduly restrictive approximations. An attempt is made to compare the various programs now generally available from the point of view of the advantages of the relative technique utilized, as well as the programmed state of the art. Many of the comparisons are based on the sample problems solved by the STARS-2 system of programs. These examples indicate both the structural detail which can be analyzed by, and the analytical capabilities available in, the numerical shell-of-revolution programs. All advantages and differences are demonstrated by use of solutions for realistic shell problems in the areas of statics, stability, vibrations, and dynamic response of shells subjected to time-dependent loadings.

Svalbonas, V.