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Barry, R. G.

Publications and source records attributed to Barry, R. G..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Parameterization and scaling of arctic ice conditions in the context of ice-atmospheric processes

The goals of this project are to observe how the open water/thin ice fraction in a high-concentration ice pack responds to different short-period atmospheric forcings, and how this response is represented in different scales of observation. The objectives can be summarized as follows: determine the feasibility and accuracy of ice concentration and ice typing by ERS-1 SAR backscatter data, and whether SAR data might be used to calibrate concentration estimates from optical and massive-microwave sensors; investigate methods to integrate SAR data with other satellite data for turbulent heat flux parameterization at the ocean/atmosphere interface; determine how the development and evolution of open water/thin ice areas within the interior ice pack vary under different atmospheric synoptic regimes; compare how open-water/thin ice fractions estimated from large-area divergence measurements differ from fractions determined by summing localized openings in the pack; relate these questions of scale and process to methods of observation, modeling, and averaging over time and space.

Barry, R. G.↗
NASA NTRS1994

Parameterization and scaling of Arctic ice conditions in the context of ice-atmosphere processes

This report summarizes achievements during year three of our project to investigate the use of ERS-1 SAR data to study Arctic ice and ice/atmosphere processes. The project was granted a one year extension, and goals for the final year are outlined. The specific objects of the project are to determine how the development and evolution of open water/thin ice areas within the interior ice pack vary under different atmospheric synoptic regimes; compare how open water/thin ice fractions estimated from large-area divergence measurements differ from fractions determined by summing localized openings in the pack; relate these questions of scale and process to methods of observation, modeling, and averaging over time and space; determine whether SAR data might be used to calibrate ice concentration estimates from medium and low-rate bit sensors (AVHRR and DMSP-OLS) and the special sensor microwave imager (SSM/I); and investigate methods to integrate SAR data for turbulent heat flux parametrization at the atmosphere interface with other satellite data.

Barry, R. G.↗
NASA NTRS1994

Ice-atmosphere interactions in the central Arctic: Remotely-sensed and simulated ice concentration and motion

The response of the Beaufort Sea ice pack to the passage of strong low pressure systems is studied using SAR (synthetic aperture radar), AVHRR (advanced very high resolution radiometer), and SSM/I (special sensor microwave/imager) data combined with model simulations. The SAR, AVHRR, and modeled concentrations concur generally in showing a 1 to 5 percent decrease in ice fraction during the passage of the lows. SSM/I derived concentrations appear to underestimate overall concentration and overestimate the opening of the pack relative to the other data sets. Ice motion derived from SAR and AVHRR and model simulations using two ice rheologies agree reasonably well in direction and magnitude, although the cavitating fluid approximation tends to overestimate ice motion compared to a viscous plastic rheology. Ice motions from SAR, AVHRR, and buoy observations can be merged to yield uniform grids particularly well suited to synoptic scale studies and model validation.

Maslanik, J. A.↗
NASA NTRS1989

Cloud cover determination in polar regions from satellite imagery

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Barry, R. G.↗
NASA NTRS1989

Cloud classification from satellite data using a fuzzy sets algorithm - A polar example

Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

Key, J. R.↗
NASA NTRS1989

Merging AVHRR and SMMR data for remote sensing of ice and cloud in polar regions

Multispectral data from the Advanced Very High Resolution Radiometer (AVHRR) were digitally processed and merged with Scanning Multichannel Microwave Radiometer (SMMR) imagery. Five channels of AVHRR data, four channels of SMRR brightness temperatures and SMMR-derived ice concentration and ice type were co-registered to a polar stereographic grid. The merged data sets are currently being used in combination with meteorological information for integrated studies of clouds and sea ice.

Maslanik, J. A.↗
NASA NTRS1989

Lidar detection of leads in Arctic sea ice

REMOTE sensing using an airborne infrared lidar has shown an unexpected capability to detect open leads in Arctic sea ice and their associated meteorology in winter. It is shown here that vertical profiles of backscattered radiation demonstrate strong returns from hydrometeor plumes originating from leads having a surface water temperature near -1.8 C. Recently refrozen leads are also distinguishable by the lidar backscatter from adjacent thicker, older sea ice. Wide leads release enough energy to create buoyant plumes which penetrate the Arctic boundary layer inversion, transporting heat and moisture into the troposphere. These results show that the role of the Arctic as a global heat sink may need to be reevaluated, and that lead plumes have a significant effect on the radiation budget.

Schnell, R. C.↗
NASA NTRS1989

Adaptation of the ISCCP cloud detection algorithm to combined AVHRR and SMMR arctic data

The International Satellite Cloud Climatology Project (ISCCP) cloud detection algorithm is applied to artic data, and modifications are suggested. Both Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data are examined. Synthetic AVHRR and SMMR data are also generated. Modifications suggested include the use of snow and ice data sets for the estimation of surface parameters, additional AVHRR channels, and surface class characteristic values when clear sky values cannot be obtained. Greatest improvement in computed cloud fraction is realized over snow and ice surfaces; over other surfaces all versions perform similarly. Since the use of SMMR for surface analysis increases the computational burden, its use may be justified only over snow and ice-covered regions.

Key, J.↗
NASA NTRS1988

Cloud cover determination in polar regions from satellite imagery

The principal objectives of this project are: (1) to develop suitable validation data sets to evaluate the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; (2) to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers; and (3) to compare synoptic cloud data from a control run experiment of the GISS climate model II with typical observed synoptic cloud patterns.

Barry, R. G.↗
NASA NTRS1988

Cloud classification from satellite data using a fuzzy sets algorithm: A polar example

Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine likely areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

Key, J. R.↗
NASA NTRS1988

Cloud cover determination in polar regions from satellite imagery

The principal objectives of this project are: to develop suitable validation data sets to evaluate the effectiveness of the ISCCP operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers: and to compare synoptic cloud data from a control run experiment of the Goddard Institute for Space Studies (GISS) climate model 2 with typical observed synoptic cloud patterns. Current investigations underway are listed and the progress made to date is summarized.

Barry, R. G.↗
NASA NTRS1988

Intercomparison of satellite-derived cloud analyses for the Arctic Ocean in spring and summer

Several methods of deriving Arctic cloud information, primarily from satellite imagery, have been intercompared. The comparisons help in establishing what cloud information is most readily determined in polar regions from satellite data analysis. The analyses for spring-summer conditions show broad agreement, but subjective errors affecting some geographical areas and cloud types are apparent. The results suggest that visible and thermal infrared data may be insufficient for adequate cloud mapping over some Arctic surfaces.

Mcguffie, K.↗
NASA NTRS1987

Cloud cover determination in polar regions from satellite imagery

A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.

Barry, R. G.↗
NASA NTRS1986

Empirical and modeled synoptic cloud climatology of the Arctic Ocean

A set of cloud cover data were developed for the Arctic during the climatically important spring/early summer transition months. Parallel with the determination of mean monthly cloud conditions, data for different synoptic pressure patterns were also composited as a means of evaluating the role of synoptic variability on Arctic cloud regimes. In order to carry out this analysis, a synoptic classification scheme was developed for the Arctic using an objective typing procedure. A second major objective was to analyze model output of pressure fields and cloud parameters from a control run of the Goddard Institue for Space Studies climate model for the same area and to intercompare the synoptic climatatology of the model with that based on the observational data.

Barry, R. G.↗
NASA NTRS1985

Empirical and modeled synoptic cloud climatology of the Arctic Ocean

A daily climatology of the atmospheric circulation of the Arctic and the associated cloud conditions were determined. These are used for comparisons with the variability of general circulation model, generated circulation, and cloud cover for the same region.

Barry, R. G.↗
NASA NTRS1985

Characteristics of Arctic Ocean ice determined from SMMR data for 1979 - Case studies in the seasonal sea ice zone

Sea ice data derived from the Scanning Multichannel Microwave Radiometer are examined for sections of the Arctic Ocean during early summer 1979. The temporary appearance of spuriously high multiyear ice fractions in the seasonal ice zones of the Kara and Barents Seas is a result of surface melt phenomena and the relative responses of the different channels to these effects. These spurious signatures can provide early identification of melt onset and additional information on surface characteristics.

Anderson, M. R.↗
NASA NTRS1984

Pilot study and evaluation of a SMMR-derived sea ice data base

Data derived from the Nimbus 7 scanning multichannel microwave radiometer (SMMR) are discussed and the types of problems users have with satellite data are documented. The development of software for assessing the SMMR data is mentioned. Two case studies were conducted to verify the SMMR-derived sea ice concentrations and multi-year ice fractions. The results of a survey of potential users of SMMR data are presented, along with SMMR-derived sea ice concentration and multiyear ice fraction maps. The interaction of the Arctic atmosphere with the ice was studied using the Nimbus 7 SMMR. In addition, the characteristics of ice in the Arctic ocean were determined from SMMR data.

Barry, R. G.↗