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R. F. Cahalan, D. A. Short, and G. R. North

Abstract

A space-time statistical analysis of total outgoing infrared radiation (derived from the 10.5–12.5 μm window measurements of the NOAA operational satellites) is used to determine the gross features of day-to-day cloudiness fluctuations over the Pacific Ocean in summer and winter. Infrared fluctuations arise from the passage of cloudiness systems through a grid box as well as the creation and destruction of cloudiness in the box. Which process dominates depends upon the size of the box relative to the size, speed and persistence time of a typical cloudiness system. In most regions the statistical analysis yields advection speeds characteristic of 700 mb mean flow with spatial dependence resembling the 300 mb mean flow. Spatial scales less than 2000 km predominate, smaller scales having less persistence. Characteristic time scales are on the order of one or two days, even for a grid box spanning the entire North Pacific storm track. This result is remarkable in view of the much longer time scales commonly associated with atmospheric disturbances. Apparently many cloudiness systems are created and destroyed during the lifetime of a single disturbance.

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Gerald R. North, Thomas L. Bell, Robert F. Cahalan, and Fanthune J. Moeng

Abstract

Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available. The geographical shape of an EOF shows large intersample variability when its associated eigenvalue is “close” to a neighboring one. A rule of thumb indicating when an EOF is likely to be subject to large sampling fluctuations is presented. An explicit example, based on the statistics of the 500 mb geopotential height field, displays large intersample variability in the EOF's for sample sizes of a few hundred independent realizations, a size seldom exceeded by meteorological data sets.

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Gerald R. North, Fanthune J. Moeng, Thomas L. Bell, and Robert F. Cahalan

Abstract

Zonally averaged meteorological fields can have large variances in polar regions due to purely geometrical effects, because fewer statistically independent areas contribute to zonal means near the poles than near the equator. A model of a stochastic field with homogeneous statistics on the sphere is presented as an idealized example of the phenomenon. We suggest a quantitative method for isolating the geometrical effect and use it in examining the variance of the zonally averaged 500 mb geopotential height field.

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