Climatology at any point: A neural network solution

Abstract

Advance knowledge of information on climatology of meteorological parameters like temperature, maximum temperature, minimum temperature, atmospheric pressure, rainfall etc are of great demands from all the users, planners, disaster managements personals, tourism etc. The information is required at the place concerned but this cannot be fulfilled by the meteorological community due to absent of observatory at that place and also some time absent of past data of long period. The present paper has described a comparatively new application of the neural network in the field of spatial interpolation. Neural network interpolation models are developed for both maximum and minimum temperatures for all the twelve months. The model utilizes geographical information like latitude, longitude and elevation as inputs to generate normal maximum and minimum temperatures at a place. The performances of the models are compared with the other commonly used method for spatial interpolation.