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Weger, R. C.

Publications and source records attributed to Weger, R. C..

Aerosol Retrieval Using Synthetic Polder Multi-Angular Data

The POLarizations and Directionality of the Earth's Reflectances (POLDER) instrument onboard the Japanese ADEOS satellite offers unique possibilities for the retrieval of aerosol parameters with its polarization and multi-angular capability. In this study we examine a technique that simultaneously retrieve multiple aerosol parameters, namely asymmetry factor, single scattering albedo, surface albedo, and optical thickness. using simulated POLDER reflectances. It is found that. over dark or bright surfaces, simultaneous retrieval of multiple parameters is indeed possible, but not over surfaces with intermediate reflectivity. Among the four parameters, the single-scattering albedo is retrieved with the best accuracy and is the least vulnerable when the reflectance value is subjected to a 0.1% white noise.

Kuo, K. S.

Simultaneous Retrieval of Multiple Aerosol Parameters Using a Multi-Angular Approach

Atmospheric aerosol particles, both natural and anthropogenic, are important to the earth's radiative balance through their direct and indirect effects. They scatter the incoming solar radiation (direct effect) and modify the shortwave reflective properties of clouds by acting as cloud condensation nuclei (indirect effect). Although it has been suggested that aerosols exert a net cooling influence on climate, this effect has received less attention than the radiative forcing due to clouds and greenhouse gases. In order to understand the role that aerosols play in a changing climate, detailed and accurate observations are a prerequisite. The retrieval of aerosol optical properties by satellite remote sensing has proven to be a difficult task. The difficulty results mainly from the tenuous nature and variable composition of aerosols. To date, with single-angle satellite observations, we can only retrieve reliably against dark backgrounds, such as over oceans and dense vegetation. Even then, assumptions must be made concerning the chemical composition of aerosols. The best hope we have for aerosol retrievals over bright backgrounds are observations from multiple angles, such as those provided by the MISR and POLDER instruments. In this investigation we examine the feasibility of simultaneous retrieval of multiple aerosol optical parameters using reflectances from a typical set of twelve angles observed by the French POLDER instrument. The retrieved aerosol optical parameters consist of asymmetry factor, single scattering albedo, surface albedo, and optical thickness.

Kuo, K. S.

Simultaneous Retrieval of Multiple Aerosol Parameters Using a Multi-Angular Approach

Atmospheric aerosol particles, both natural and anthropogenic, are important to the earth's radiative balance through their direct and indirect effects. They scatter the incoming solar radiation (direct effect) and modify the shortwave reflective properties of clouds by acting as cloud condensation nuclei (indirect effect). Although it has been suggested that aerosols exert a net cooling influence on climate, this effect has received less attention than the radiative forcing due to clouds and greenhouse gases. In order to understand the role that aerosols play in a changing climate, detailed and accurate observations are a prerequisite. The retrieval of aerosol optical properties by satellite remote sensing has proven to be a difficult task. The difficulty results mainly from the tenuous nature and variable composition of aerosols. To date, with single-angle satellite observations, we can only retrieve reliably against dark backgrounds, such as over oceans and dense vegetation. Even then, assumptions must be made concerning the chemical composition of aerosols. In this investigation we examine the feasibility of simultaneous retrieval of multiple aerosol optical parameters using reflectances from a typical set of twelve angles observed by the French POLDER instrument. The retrieved aerosol optical parameters consist of asymmetry factor, single scattering albedo, surface albedo, and optical thickness.

Kuo, K.-S.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Lee, J.

An intercomparison of artificial intelligence approaches for polar scene identification

The following six different artificial-intelligence (AI) approaches to polar scene identification are examined: (1) a feed forward back propagation neural network, (2) a probabilistic neural network, (3) a hybrid neural network, (4) a 'don't care' feed forward perception model, (5) a 'don't care' feed forward back propagation neural network, and (6) a fuzzy logic based expert system. The ten classes into which six AVHRR local-coverage arctic scenes were classified were: water, solid sea ice, broken sea ice, snow-covered mountains, land, stratus over ice, stratus over water, cirrus over water, cumulus over water, and multilayer cloudiness. It was found that 'don't care' back propagation neural network produced the highest accuracies. This approach has also low CPU requirement.

Tovinkere, V. R.

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

Weger, R. C.

Cloud classification in polar regions using AVHRR textural and spectral signatures

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

Welch, R. M.