Clouds
Responsible researcher: Sylvio Luiz Mantelli Neto
Last updated: 2008-11-13
Sunlight interaction with atmospheric components result in distinct patterns in the sky.
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| Sunlight interaction with atmospheric components result in distinct patterns in the sky. |
Clouds play a major role on atmospheric behavior. They are present in a great variety of shape, altitude, density, distribution, etc., according to their composition and current weather conditions. Its presence and diurnal variation modulates the amount of solar energy that reaches the Earth surface by absorbing and scattering it. Energy balance usually takes into account their effects of cooling and warming on the atmosphere with a great impact on everyday life of human living.
Clouds are also, the major factor of uncertainty on physical models when they are present. Clouds observation and quantification still remain a challenge. From satellite its determination is subject to geometric distortion, overlaying multiple blocking layers, atmospheric composition variability and Earth surface seasonal background changes. From surface its monitoring is done using criteria established by World Meteorological Organization (WMO) adopted by synoptic observers, but this method is marked by subjective uncertainty and biases of operator evaluation.
The replacement of surface observers in highly desirable to reduce the subjectiveness of analysis, classification and improvement of amount evaluation. Synoptic observations performed by surface operators are subject to shifts and other uncertainties related to variation of subjective scene analysis. Camera systems are being used to replace operators, but current used methods are still based on trivial image analysis.
Replace any human activity by one artifact, must take into account issues related to a new group of sciences in Cognitive, Artificial Intelligence and Knowledge Engineering areas. This artifact is known on these related areas as an Intelligent Agent [1]. To find new techniques to identify, evaluate and classify patterns present in the atmospheric is one of the objectives of the present research in the Computer Vision area. Current investigations is intended not to be conclusive but collaborative to solve uncertainties human replacement activities.
The following images illustrates some aspects of current research. The left image shwos a typical cloud assessment along one day. Besides it, two images and their analysis developed in the current research.
Researchers
- Sylvio Luiz Mantelli Neto : main clouds researcher.
- Eros Comunello : research colaborator.
- Aldo von Wangenheim: group coordinator.
- Dr. Enio Bueno Pereira: research colaborator.
Publications
- Mantelli Neto, Sylvio Luiz, Aldo von Wangenheim, Enio Bueno Pereira, Eros Comunello, 2010: The Use of Euclidean Geometric Distance on RGB Color Space for the Classification of Sky and Cloud Patterns. J. Atmos. Oceanic Technol., 27, 1504–1517. doi: 10.1175/2010JTECHA1353.1
- MANTELLI NETO, S. L. ; WANGENHEIN, A. V. ; PEREIRA, Enio Bueno ; E. Comunello . (accepted) Methodology for Automatic Observation of Sky Patterns. In: XXIX Congresso da Sociedade Brasileira de Computação- Colóquio em Informática: Brasil / INRIA Cooperações Avanços e Desafioos, 2009, Bento Gonçalves RS. Proccedings do XXIX Congresso da Sociedade Brasileira de Computação- Colóquio em Informática: Brasil / INRIA Cooperações Avanços e Desafioos, 2009.
- MANTELLI NETO, S. L. ; WANGENHEIN, Aldo Von ; PEREIRA, Enio Bueno . Modelo preliminar de estimativa de cobertura de nuvens, no espaço de cores RGB obtidas a partir de imageador automático.. In: XII Simpósio Brasileiro de Sensoriamento Remoto, 2005, Goiânia. Anais XII Simpósio Brasileiro de Sensoriamento Remoto, 2005. p. 4123-4131.
- MANTELLI NETO, S. L. ; WANGENHEIN, Aldo Von ; PEREIRA, Ê. B. . Nova Metodologia para a Estimativa da Cobertura de Nuvens. . Revista Pesquisa Naval, v. 15.
- MANTELLI NETO, S. L. ; WANGENHEIN, A. V. ; PEREIRA, Enio Bueno . Desenvolvimento de uma Nova Metodologia para a Estimativa da Cobertura de Nuvens. In: XII Congresso Brasileiro de Meteorologia, 2002, Foz do Iguaçu, 2002.
References
Russel S., Norvig P. Artificial Intelligence 2nd ed. 2003 book Elsevier .
Johnson R. A. and Wichern D. W. Applied Multivariate Statistical Analysis. 6th. ed. 2007 book Pearson Int. Ed.
Duda R. O., Hart P. E., Stork D. G. Pattern Classification 2nd ed. 2000 Wiley-Interscience.
Gonzales R. C., Woods R. E. Digital Image Processing, 2nd ed. 2002 Prentice-Hall
