Accession Number : ADA289058

Title :   Synthetic 3-D Atmospheric Temperature Structure: A Model for Known Geophysical Power Spectra Using a Hybrid Autoregression and Fourier Technique.

Descriptive Note : Interim rept. 1 Oct 92-31 May 94,

Corporate Author : PHILLIPS LAB HANSCOM AFB MA

PDF Url : ADA289058

Report Date : 25 MAY 1994

Pagination or Media Count : 53

Abstract : Geophysical phenomena are often characterized by smooth continuous power spectra having a domain of negative slope power law dependence. Frequently. Fourier transform analysis has been employed to synthesize scenes from pseudorandom arrays by passing the random samples through a Fourier filter having a desired correlation structure and power spectral dependency. This report approaches synthesis of three-dimensional synthetic structure by invoking autoregression analysis in conjunction with the Fourier method. Since computations that apply multidimensional fast Fourier transforms to large data arrays consume enormous resources, the goal of this study is to seek an alternative method to reduce the computational burden. Future releases of the Phillips Laboratory Strategic High Altitude Atmospheric Radiance Code (SHARC) will feature an ability to calculate structured radiance. The methods explored here provide a process that can complement or sometimes supplement methods presently being used. The three-dimensional temperature structure realizations generated by these methods were used to produce two-dimensional integrated temperature structure scenes that showed compliance with the input specifications.

Descriptors :   *COMPUTERIZED SIMULATION, *REGRESSION ANALYSIS, *ATMOSPHERE MODELS, *FOURIER ANALYSIS, COMPUTER PROGRAMS, DATA BASES, FOURIER TRANSFORMATION, IMAGE PROCESSING, DATA PROCESSING, COMPUTATIONS, STOCHASTIC PROCESSES, ATMOSPHERIC TEMPERATURE, POWER SPECTRA, PROBABILITY DENSITY FUNCTIONS, THREE DIMENSIONAL, CORRELATION, RADIANCE, WIND VELOCITY, GEOPHYSICS, ATMOSPHERIC DENSITY, CONTINUOUS SPECTRA, PSEUDO RANDOM SYSTEMS.

Subject Categories : Meteorology
      Computer Programming and Software
      Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE