Predicting daily total ozone over Kolkata, India: skill assessment of different neural network modelsThis article was published online on 7 October 2008. An error was subsequently identified. This notice is included in the online and print versions to indicate that both have been corrected, 20 January 2009.

This paper explores the observation made by the Earth Probe Total Ozone Mapping Spectrometer EPTOMS to analyse the predictability of daily total ozone concentration over Kolkata, India. Latitude, longitude, aerosol index, reflectivity, sulphur dioxide index and total ozone concentration of a given day have been used as independent variables to predict total ozone concentration of the next day. Artificial neural network in the forms of a multilayer perceptron, generalized feed forward neural network, a radial basis function network and a modular neural network have been trained to generate predictive models. Performances of the models in the test cases have been judged with the help of four statistical parameters. Finally the models have been compared with multiple linear regression and the potential of generalized feed forward neural network has been established over the other proposed models. Copyright © 2008 Royal Meteorological Society [ABSTRACT FROM AUTHOR]