Experiments In Automatic Cloud Tracking Using SMS-GOES Data

Wolf, Daniel E.; Hall, D.; Endlich, R. M.

doi:10.1175/1520-0450(1977)016<1219:eiactu>2.0.co;2

Cited by 29 publications

(8 citation statements)

References 12 publications

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“…Clustering has been applied to the location of track able clouds for wind-velocity estimation (Endlich et al 1971, Wolf et al 1977, Endlich and Wolf 1981. Results were found to be satisfactory.…”

Section: Segmentation Of Cloudsmentioning

confidence: 99%

Segmentation of clouds using cluster analysis

Seddon

Hunt

1985

International Journal of Remote Sensing

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The techniques of pattern recognition can provide unique information on cloud structures for cloud climatology programmes. We present a flexible automatic method for segmentation of meteorological satellite data using a multidimensional clustering procedure. The algorithm developed is described, together with its application to cloud data from the METEOSAT-I satellite. If the data are transformed prior to segmentation by use of the Principal Components Transformation, the results compare favourably with those of alternative methods.

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Section: Segmentation Of Cloudsmentioning

confidence: 99%

Segmentation of clouds using cluster analysis

Seddon

Hunt

1985

International Journal of Remote Sensing

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“…Several groups have developed computer-based techniques to derive motion 3,4 vectors from sequences of satellite images . The principal application of these techniques, however, has been to estimate upper-level winds in data-sparse regions.…”

Section: Motion Vectorsmentioning

confidence: 99%

Shortrange Forecasting of Cloudiness and Precipitation through Extrapolation of GOES Imagery.

Muench¹

1981

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“…In general, these ideas can be categorized into three main methods: timing analysis methods, overlapping methods, and cross-correlation methods. The timing analysis method concretely includes Fourier transform (Arking et al 1978), the singular value decomposition (SVD) method (K. , the schema matching method (Wolf et al 1977;Brad and Letia 2002), and others. This method is relatively sensitive to the presence of mixtures of motions, changes in cloud shape, and edge effects (Arking et al 1978), but their shortcoming is the large calculated amount.…”

Section: Introductionmentioning

confidence: 98%

Rainfall Retrieval and Nowcasting Based on Multispectral Satellite Images. Part II: Retrieval Study on Daytime Half-Hour Rain Rate

Zhuge

Zhang

2011

Journal of Hydrometeorology

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To implement continuous and reliable rainfall retrieval, based on the satellite retrieval algorithm of 10-min rain rate, this study proposes an immediate tracking and continuous accumulation technique (ITCAT) of halfhour rainfall retrieval by further combining the cross-correlation method. The ITCAT includes two steps. 1) The cross-correlation method is applied to track cloud-motion currents and establish 10-min-interval image sequences. 2) A continuous retrieval of 10-min rain rates is conducted with the image sequences, and finally a total half-hour rainfall is determined by accumulations. The satellite retrieval tests on the typical precipitation processes in the summer of 2008 show that, compared with the previous direct rainfall retrieval for half-hour to one-hour, this rainfall retrieval technique significantly improves the retrieval accuracy of rainfall scope and rainfall intensity ranging from slight rain to rainstorm for both real-time monitoring or nowcasting processes. This technique is more effective than the previous algorithm, and the fundamental reason lies in its consideration of the movement of cloud clusters. On this basis, coverage duration of rainfall clouds can be reliably estimated. It is of significance to the retrieval of deep convective cloud rainfall with rapid movement speed and drastic intensity variation. This technique also provides a feasible idea for improving the accuracy of rainfall nowcasting.

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Experiments In Automatic Cloud Tracking Using SMS-GOES Data

Cited by 29 publications

References 12 publications

Segmentation of clouds using cluster analysis

Segmentation of clouds using cluster analysis

Shortrange Forecasting of Cloudiness and Precipitation through Extrapolation of GOES Imagery.

Rainfall Retrieval and Nowcasting Based on Multispectral Satellite Images. Part II: Retrieval Study on Daytime Half-Hour Rain Rate

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