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Munteanu, M. J.

Publications and source records attributed to Munteanu, M. J..

Applications of Fuzzy Clustering Techniques to Stratified by Tropopause MSU Temperature Retrievals

The fuzzy partitioned clustering method was applied to predict tropopause height only using microwave information with an eye towards using it on real data under cloudy conditions. In the second stage stratified by tropopause regression temperature retrievals included using only the three or four microwave channels for each 40 mb range. The first step in the experiment is the fuzzy partitioned clustering of the microwave brightness temperatures. This method is a combination of standard hard clustering and discriminant analysis. The fuzzy partitioned clustering uses all the generated probabilities of membership of each pattern vector in any of the given clusters. These probabilities are generated by discriminant analysis to locate the correct cluster. The ultimate goal of standard discriminant analysis is to provide the unique (correct) cluster to which the pattern vector belongs. It was only the maximum of all the generated probabilities. The method uses all the probabilities and weight the regressions generated within each cluster. These regression formulas predict the tropopause height from the microwave brightness temperatures. In the second step the microwave regression temperature retrievals are stratified by tropopause height every 40 mb. The control experiment is defined, the data are stratified by land/ocean, summer/winter, and latitude bands.

Munteanu, M. J.↗

Applications of Fuzzy Set Theory to Satellite Soundings

The introduction of an appropriate fuzzy setting for satellite soundings and its application to clustering methods via unimodal fuzzy sets in the future is proposed. Methods of hard clustering analysis and fuzzy partitioned clustering were applied on simulated data with very encouraging results. The proposed clustering technique is discussed. The notion of a unimodal fuzzy set was chosen to represent the partition of a data set for two reasons: (1) it detects all the locations in the vector space where highly concentrated clusters of points exist; and (2) the notion is general enough to represent clusters that exhibit quite general distributions of points. The technique detects all of the existing unimodal fuzzy sets and realizes the maximum separation among them. It is economical in memory space and computational time requirements and also detects groups that are fairly generally distributed in the feature space.

Munteanu, M. J.↗

Applications of Some Artificial Intelligence Methods to Satellite Soundings

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Munteanu, M. J.↗

Applications of TOMS Ozone Data and Clustering Techniques in Satellite Soundings

Two primary areas are being pursued: (1) Applications of TOMS total ozone data to estimate the tropopause height and consequently to improve the temperature retrievals from satellite measurements; and (2) Applications of cluster analysis to satellite soundings. The strategy is to either use regression retrievals stratified by tropopause or to use the tropopause information as a constraint on the solution to the physical retrieval method.

Munteanu, M. J.↗

Regional correlation between TOMS total ozone from NIMBUS-7 satellite and geopotential height from the GLAS analysis

In order to study the relation between zone and the atmospheric circulation on a global scale the global correlation has been computed between TOMS total ozone measurements from NIMBUS-7 satellite and collocated geopotential heights analysis at all mandatory pressure levels between 1000-50 mb. The heights are obtained from the 4 deg x 5 deg GLAS analysis that uses both conventional (rawinsonde) and the operational TIROS-N satellite soundings but no ozone data. Zonal averages have been substracted to eliminate the correlation due merely to latitudinal dependence, and emphasize the correlation associated with synoptic features. Tables are presented with correlation coefficients for the four synoptic times covering the Pacific Ocean, Asia, Europe and the Atlantic Ocean, and United States regions. These coverages are approximate since NIMBUS-7 does not observe exactly the same region each day.

Munteanu, M. J.↗

Improved HIRS2/MSU soundings using tropopause information

In the GLAS physical retrieval scheme, all temperature profiles are expressed as an expansion about a global mean using empirical orthogonal functions derived from a sample of radiosondes. Total ozone burden, a parameter highly correlated with tropopause height, should be useful in improving sounding accuracy. The ability to estimate tropopause information from layer mean temperatures suggests incorporating the layer mean temperatures estimated from the sounding itself to give estimates of tropopause pressure and temperature. While information completely independent of sounding and first guess data is preferable, additional information is in fact added to the system by the statistical relationships between tropopause temperature and pressure and layer mean temperature profiles. This should not be confused with use of statistical relationships between temperature profiles and satellite observations, which form the basis of a statistical retrieval system but is in no way used in the physical retrieval scheme.

Susskind, J.↗

The prediction of tropopause height from clusters of brightness temperatures and its application in the stratified regression temperature retrievals using microwave and infrared satellite measurements

A total of 1575 radiosondes and the corresponding simulated brightness temperatures were used in an effort to derive a temperature retrieval based on the clusters of brightness temperatures. The 8 simulated channels, namely, 3 MSU and 5 IR of the TIROS-N satellite are used by the GLAS temperature retrieval method. The 3 MSU and 5 IR brightness temperatures were clustered into 17 cluster groups and a regression for the prediction of the tropopause height in mb was generated. The overall r.m.s. for the tropopause prediction is excellent, namely, around 16 mb for the summer and 23 mb for the winter. The correct cluster of brightness temperatures can be identified 98% of the time by the method of discriminatory classification if it is approximately a normal distribution or, in general, by the method of the nearest neighbor.

Munteanu, M. J.↗

Applications of cluster analysis to satellite soundings

The advantages of the use of cluster analysis in the improvement of satellite temperature retrievals were evaluated since the use of natural clusters, which are associated with atmospheric temperature soundings characteristic of different types of air masses, has the potential for improving stratified regression schemes in comparison with currently used methods which stratify soundings based on latitude, season, and land/ocean. The method of discriminatory analysis was used. The correct cluster of temperature profiles from satellite measurements was located in 85% of the cases. Considerable improvement was observed at all mandatory levels using regression retrievals derived in the clusters of temperature (weighted and nonweighted) in comparison with the control experiment and with the regression retrievals derived in the clusters of brightness temperatures of 3 MSU and 5 IR channels.

Munteanu, M. J.↗

Multivariate approximation methods and applications to geophysics and geodesy

The first report in a series is presented which is intended to be written by the author with the purpose of treating a class of approximation methods of functions in one and several variables and ways of applying them to geophysics and geodesy. The first report is divided in three parts and is devoted to the presentation of the mathematical theory and formulas. Various optimal ways of representing functions in one and several variables and the associated error when information is had about the function such as satellite data of different kinds are discussed. The framework chosen is Hilbert spaces. Experiments were performed on satellite altimeter data and on satellite to satellite tracking data.

Munteanu, M. J.↗

Geophysical approaches to inverse problems: A methodological comparison. Part 1: A Posteriori approach

The relationships of a variety of general computational methods (and variances) for treating illposed problems such as geophysical inverse problems are considered. Differences in approach and interpretation based on varying assumptions as to, e.g., the nature of measurement uncertainties are discussed along with the factors to be considered in selecting an approach. The reliability of the results of such computation is addressed.

Seidman, T. I.↗