PREDICTING DIFFERENCES IN TEMPERATURE DATA BY MODELING AND SIMULATION

Temperature is defined as the degree of hotness or coldness of a body or environment (corresponding to its molecular activity). Therefore, the importance of temperature to man, agriculture, and aquatic life cannot be overemphasized. It is in this regard that we attempted to model two consecutive years minimum and maximum temperature differences of randomly selected locations in Niger state (case study) whose observations were available so that we could gain understanding of their effects on the environment and use this information for prediction purposes. This was achieved by setting up the model using regression analysis, graphs, gathered data, and simulation approach using C++ programming language. Having put into consideration all the necessary conditions that can affect variation in temperature data and the effect of such variation, we are sure that the temperatures differences model through the graph representations has successfully ease temperature prediction purposes, provided the data collected is accurately analyzed with the explanatory variables accurately applied. Though, this paper was able to fulfill its objectives, but due to some limitations that were certainly errors associated with the used data set among which are instrumental errors that can be systematic or random, we cannot totally guarantee accuracy.