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  • Author or Editor: Robert F. Cahalan x
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Robert F. Cahalan
and
Joachim H. Joseph

Abstract

Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) data, with 80 and 30 m spatial resolution, respectively, have been employed to study the spatial structure of boundary-layer and intertropical convergence zone (ITCZ) clouds. The probability distributions of cloud area and cloud perimeters are found to approximately follow a power-law, with a different power (i.e., fractal dimension) for each cloud type. They are better approximated by a double power-law behavior, indicating a change in the fractal dimension at a characteristic size which depends upon cloud type. The fractal dimension also changes with threshold. The more intense cloud areas are found to have a higher perimeter fractal dimension, perhaps indicative of the increased turbulence at cloud top. A detailed picture of the inhomogeneous spatial structure of various cloud types will contribute to a better understanding of basic cloud processes, and also has implications for the remote sensing of clouds, for their effects on remote sensing of other parameters, and for the parameterization of clouds in general circulation models, all of which rely upon plane-parallel radiative transfer algorithms.

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David A. Short
and
Robert F. Cahalan

Abstract

The interannual variability (IAV) in monthly averaged outgoing infrared radiation (IR, from the NOAA polar orbiting satellites) is observed to be larger during summer than during winter over the north Pacific Ocean. A statistical analysis of the daily observations shows the daily variance to be similar during both seasons while the autocorrelation function is quite different. This leads to a seasonal difference in estimates of the climatic noise level, i.e., the variances expected in summer and winter monthly averages due to the number of effectively independent samples in each average. Because of a less vigorous tropospheric circulation, monthly means of IR during summer are affected by the passage of fewer synoptic-scale disturbances and their attendant cloudiness. Fewer independent samples imply a larger variance in the time averages. While the observed IAV is less in winter, the ratio of the observed IAV to the climatic noise level is larger, suggesting that signals of climatic variability in outgoing IR may be more readily diagnosed during winter in this region. The climatic noise level in monthly averaged IR and cloudiness is also estimated for two other climatic regimes—the quiescent subtropical north Pacific and the ITCZ in the western Pacific.

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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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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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