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Herbert E. Hunter, Edward B. Rodgers, and William E. Shenk

Abstract

A statistical method has been developed using satellite, climatological, and persistence data to predict tropical cyclone position 12, 24, 48 and 72 h after initial observation. The satellite measurements were infrared window channel (11.0 μm) equivalent blackbody temperatures (TBB), which gave representations (through the cloud and surface temperature fields) of the structure of the cyclones and the circulation features surrounding them. There were 197 individual measurements of TBB for each cyclone observation. Algorithms have been prepared using digital data from a single satellite image, 14 climatological and persistence type variables, and a combination of these data sources. The algorithms were developed using a unique statistical procedure based on an eigenvector preprocessing and the use of independent tests for screening decisions.

Independent testing of these algorithms showed that the average error made by the algorithms developed from the single satellite observation were comparable to the 48 h Joint Typhoon Warning Center (JTWC) forecast and were approximately 10% better for 72 h forecasts. Forecasts using only the climatological and persistence variables were about 20% worse than JTWC for 24 h forecasts and 10% worse for 48 and 72 h forecasts. When both satellite and nonsatellite variables were included, the performance was comparable to JTWC's for the 24 and 48 h forecasts and approximately 25% better than JTWC's for the 72 h forecasts.

The performance of the objective algorithms for various partitions was analyzed. It is shown that both the satellite and nonsatellite variables make significant and unique contributions.

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Herbert E. Hunter, Edward B. Rodgers, and William E. Shenk

Abstract

An empirical analysis program, based on finding an optimal representation of the data, has been applied to 120 observations of twenty nine 1973 and 1974 North Pacific tropical cyclones. Each observation consists of a field of Nimbus-5 Electrically Scanning Microwave Radiometer (ESMR-5) radiation measurements at 267 grid points covering and surrounding the tropical cyclone plus nine other non-satellite derived descriptors. Forecast algorithms to estimate the maximum wind speed at 12, 24, 48 and 72 h after each observation were developed using three bases: the non-satellite-derived descriptors, the ESMR-5 radiation measurements, and the combination of the two data bases. Independent testing of these algorithms showed that the average error made by algorithms developed from all three bases was less than the average error made by the persistence 24, 48 and 72 h maximum wind speed forecast and less than the average errors made operationally by the Joint Typhoon Warning Center (JTWC) 48 and 72 h maximum wind speed forecasts. The algorithms developed from the ESMR-5 base alone outperformed the JTWC operational forecast for the 48 and 72 h maximum wind speed. Also, the ESMR-5 data base, when combined with the non-satellite base, produced algorithms that improved the 24 and 48 h maximum wind-speed forecast by as much as 10% and the 72 h maximum wind forecast by approximately 16% as compared to the forecast obtained from the algorithms developed from the non-satellite data base alone.

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Herbert E. Hunter, Rosemary M. Dyer, and Morton Glass

Abstract

Classification algorithms have been developed to distinguish six categories of cloud ice particles. These algorithms have been incorporated in schema which, when applied to shadowgraph images produced by the Precision Measurement System laser scanning device, have demonstrated the capability of classifying with more consistency than human classifiers, and with almost no sensitivity to particle orientation.

The data used to derive the algorithms consisted of observations obtained on four separate aircraft flights. Two human classifiers, interacting with a preliminary machine classification, defined the correct answers for this training data set. The algorithms were then tested against arbitrarily selected segments from two additional flights. The ADAPT Service Corporations eigenvector, or empirical orthogonal function (EOF) technique, defined the features objectively, and the ADAPT independent eigenscreening algorithm development program related these features to the particle type.

Analysis of the performance suggests that considerable variation is to be expected, based on the set-to-set variation of the distribution of particle types between real data sets. The classification schema have been developed to allow the user to change key parameters in order to compensate for this variation.

It was concluded that the machine classification was superior to manual classification for the identification of large numbers of particles in terms of speed and consistency.

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Rosemary M. Dyer, Morton Glass, and Herbert E. Hunter

Abstract

A major impediment to the development of computer algorithms for the automatic classification of ice particle types found in the atmosphere as measured by a Particle Measuring System two-dimensional probe is the difficulty of obtaining training data. This is especially true when, as is usually the case, the particle shapes do not correspond to any of the pure crystal types found in textbooks.

This paper presents the results of testing such a training set. Sources of bias among human observers include the effect of training and previous familiarity with the data, fatigue, and particle orientation, as well as subjective differences among observers. The deviation of individual human observers from the classifications arrived at by consensus indicates an upper bound to the accuracy possible in automated classification schemes.

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William E. Shenk, Herbert E. Hunter, Frederick V. Menkello, Robert Holub, and Vincent V. Salomonson

Abstract

An objective statistical procedure has been developed using satellite infrared window radiation measurements to estimate the central pressure (Pc), the deviation of the central pressure from the climatological normal (ΔP), the intensity (I = ∇2 P), and the deepening or filling rate (dP/dt) of extratropical cyclones. The independent variables for 40 cylones over the North Atlantic and Pacific Oceans were the Nimbus 2 High Resolution Infrared Radiometer (HRIR) measurements at 79 locations surrounding the center of each cyclone, the date, and the geographical location of the center. Optimum empirical orthogonal functions were used to reduce the dimensionality and establish the regression relationship between the cyclone parameters and the radiation measurements for 30 of the cyclones. The remaining 10 cyclones were used to test the accuracy of the regression relationship. When the test cyclones were well represented by the cyclones in the sample employed to establish the relationship, a standard error of estimate for Pc of 6 mb was achieved for the test cyclones with slightly lower percentage accuracies for ΔP and I. An a priori decision could be made for each test cyclone regarding the probable success of parameter estimation. This was dependent on how well the test cyclone was represented by the orthogonal functions derived by the cyclones used to establish the regression equation.

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