Using autoregressive neural network with external input for calculation of expected carbon dioxide surface concentration for different time intervals

The results of the prediction of a model based on an artificial neural network were compared to predict the concentration of carbon dioxide (CO2) in the surface layer of the atmosphere for different time intervals. Measurements were taken on the Arctic island of Belyy, Russia. For comparison, three time intervals were used, which differed in the dependence of carbon dioxide concentration on the time of day. A non-linear autoregressive neural network with external input (NARX) was used. The model based on NARX successfully coped with the prediction. The smallest error was for the time intervals with a strong dependence of CO2 concentration on the time of day.