Arctic and Subarctic Atmospheres, 0 to 90 Km

Arctic and Subarctic Atmospheres, 0 to 90 Km PDF

Author: Allen E. Cole

Publisher:

Published: 1977

Total Pages: 52

ISBN-13:

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Sets of mean monthly reference atmospheres that describe seasonal changes in the vertical distributions of temperature, density, and pressure at altitudes up to 90 km are presented for latitudes 60 deg N and 75 deg N. Also provided are specialized atmospheric models that reflect longitudinal differences in the vertical structure of temperature and density at these latitudes. Estimates of the seasonal, day-to-day, diurnal, and spatial variations are given with special emphasis placed on density. (Author).

Monthly Midlatitude Atmospheres, Surface to 90 Km

Monthly Midlatitude Atmospheres, Surface to 90 Km PDF

Author: Arthur J. Kantor

Publisher:

Published: 1976

Total Pages: 36

ISBN-13:

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Sets of mean monthly Reference Atmospheres that reflect the seasonal changes in the vertical distributions of temperature, pressure, and density at altitudes up to 90 km are presented for latitudes 30 deg N and 45 deg N. Estimates of the magnitude of the diurnal, day-to-day, and spatial variability of temperature and density are included for altitudes above 20 km. Special attention is given to the distribution of atmospheric density since density is the atmospheric property of most concern to aerospace designers and engineers. This report is part of a comprehensive effort to develop sets of mean monthly atmospheric models, surface to 90 km, for 15 deg intervals of latitude from pole to equator. The research is being performed to help satisfy the many requests that have been received from Air Force engineers and designers for information on the time and space variability of atmospheric density and temperature at altitude up to 90 km. (Author).

Variability of Atmospheric Density in the Middle Atmosphere

Variability of Atmospheric Density in the Middle Atmosphere PDF

Author: Arthur J. Kantor

Publisher:

Published: 1983

Total Pages: 28

ISBN-13:

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An analysis of the time and space variability of density in the middle atmosphere has been developed in this report, affording a means to determine density changes that occur over distances out to 200 nmi and time periods of 1 to 72 hr. Spatial variations - The rms differences between densities at locations 50, 100, and 200 nmi apart are provided in Tables 4, 8 and 11 for low- and middle- latitude stations at altitudes from 20 through 60 km. These rms values are estimates of the day-to-day variability around the mean density gradients given in Table 5 for low latitudes and Tables 9 and 12 for middle latitudes. Time variations - The rms variability of density for time periods from 1 to 12 hr in tropical regions is given in Table 13 for altitudes up to 60 km. Estimates were derived using autocorrelation theory and an analysis of the diurnal variation of density, which is the dominant periodic cycle at low latitudes. Analyses of available density observations at several midlatitude locations for altitudes between 30 and 60 km provide reasonable estimates of the magnitude (and changes with season and latitude) of the variability of density with time for periods up to 72 hr. Variations of density at these latitudes are relatively small during summer and do not increase significantly with time. Rms variations remain between 1-1/2 and 4 percent for all periods up to 72 hr.

Areal Coverage Estimates by Stochastic Modelling

Areal Coverage Estimates by Stochastic Modelling PDF

Author: Irving I. Gringorten

Publisher:

Published: 1976

Total Pages: 60

ISBN-13:

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The purpose of this paper is to relate the single-point probability of a meteorological event to the probability of its occurrence along a line or in an area of given size or fraction of the area. To make the problem tractable it was limited to modelling the probability estimates of the minimum or maximum condition along a line or in an area, or of the maximized minimum in a fraction of the area. In the absence of an analytical solution a Monte Carlo technique, applied to a Gaussian variable, was used to obtain answers that are presented graphically. Two models are described, one shown to be effective with macroscale events; the other, and more interesting model, is shown to be effective with the mesoscale phenomena of quantitative precipitation in areas ranging from a few hundred square kilometers to more than 50,000 sq. km. (Author).