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Nowcasting visibility during wintertime fog over the airport of a metropolis of India: decision tree algorithm and artificial neural network approach

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  • Debashree Dutta
  • Sutapa Chaudhuri

Abstract

The endeavor of the present research is to nowcast the spatial visibility during fog over the airport of Kolkata (22.6°N; 88.4°E), India, with artificial neural network (ANN) model. The identification of dominant parameters influencing the visibility during wintertime (November–February) fog over the region is made using the decision tree algorithm. The decision tree is constructed by computing the entropy of the parameters collected during the period from 2001 to 2011. The parameters having minimum entropy are selected as the most useful parameters because it has maximum certainty in influencing the visibility. The result reveals that the moderate range of NO 2 (67–134 µg/m 3 ) is the most dominant parameter compared with other parameters that influence the visibility during wintertime fog over Kolkata and is selected as the first node of the tree. The decision tree approach led to select five such parameters having minimum entropy for affecting maximum the visibility during fog over Kolkata airport. The selected parameters are NO 2 , wind speed, relative humidity, CO and temperature. ANN model is developed with the selected parameters as the input in the form of multilayer perceptron with back propagation learning technique for forecasting the 3 hourly visibility during wintertime fog over Kolkata airport. The result reveals that the forecast of visibility of different categories is possible with ANN model. However, the best forecast is obtained for very dense visibility within the 50 m horizontal distance. The result is validated with observation, and the forecast error is estimated. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Debashree Dutta & Sutapa Chaudhuri, 2015. "Nowcasting visibility during wintertime fog over the airport of a metropolis of India: decision tree algorithm and artificial neural network approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(2), pages 1349-1368, January.
    • Handle: RePEc:spr:nathaz:v:75:y:2015:i:2:p:1349-1368
    DOI: 10.1007/s11069-014-1388-9
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    References listed on IDEAS

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    1. ., 2007. "The 1930s," Chapters, in: Henry W. de Jong & William G. Shepherd (ed.), Pioneers of Industrial Organization, chapter 11, Edward Elgar Publishing.
    2. ., 2007. "To the 1930s," Chapters, in: Henry W. de Jong & William G. Shepherd (ed.), Pioneers of Industrial Organization, chapter 10, Edward Elgar Publishing.
    3. Sutapa Chaudhuri & Debashree Dutta & Sayantika Goswami & Anirban Middey, 2013. "Intensity forecast of tropical cyclones over North Indian Ocean using multilayer perceptron model: skill and performance verification," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 97-113, January.
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    Cited by:

    1. Ortega, Luz C. & Otero, Luis Daniel & Solomon, Mitchell & Otero, Carlos E. & Fabregas, Aldo, 2023. "Deep learning models for visibility forecasting using climatological data," International Journal of Forecasting, Elsevier, vol. 39(2), pages 992-1004.
    2. Sebastian J. Dietz & Philipp Kneringer & Georg J. Mayr & Achim Zeileis, 2017. "Forecasting Low-Visibility Procedure States with Tree-Based Statistical Methods," Working Papers 2017-22, Faculty of Economics and Statistics, Universität Innsbruck.
    3. Philipp Kneringer & Sebastian J. Dietz & Georg J. Mayr & Achim Zeileis, 2017. "Probabilistic Nowcasting of Low-Visibility Procedure States at Vienna International Airport During Cold Season," Working Papers 2017-21, Faculty of Economics and Statistics, Universität Innsbruck.
    4. Sutapa Chaudhuri & Arumita Roy Chowdhury, 2018. "Air quality index assessment prelude to mitigate environmental hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(1), pages 1-17, March.

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