A Model for the Sequence of Positive and Negative Maximum Air temperature Anomaly in Port Harcourt, Nigeria

Abstract

This work employ the Markov Chain model in modeling the sequence of positive and negative maximum air temperature anomaly in order to provide information for weather or climate assessment of the city of Port Harcourt, Nigeria. This was achieved by determining; the order of the Markov Chain model that fits the maximum air temperature data, the transition probability matrix for the sequence of positive and negative maximum air temperature anomaly, the steady state probabilities of a positive and negative maximum air temperature anomaly and the mean recurrence time (in days) of a positive and negative maximum air temperature anomaly. These were determined for each month of the year (January – December). The Results from the study showed that the first order Markov Chain model is found suitable for analyzing the positive and negative maximum air temperature anomaly in Port Harcourt, Nigeria for each month of the year, the positive - positive (+ +) and negative - negative (- -) anomaly sequences have equal chance of 0.8, 0.8, 0.7, 0.8, 0.9 and 0.8 in the months of January, February, July, October, November and December respectively, while the positive - negative (+ -) and negative - positive (- +) anomaly sequences also have equal chance of 0.2, 0.2, 0.3, 0.2, 0.1 and 0.2 in the same months. Furthermore, the results revealed that, in the long run, the positive and negative maximum air temperature anomalies have equal chance of 0.5 in the months of January, February, July, October, November and December and equal mean recurrence time of 2.00 days in the same months. The study recommends that the first order Markov Chain model be used in analyzing the sequence of positive and negative maximum air temperature anomaly in Port Harcourt, Nigeria and that the results of the study be made available to stakeholders for use wherever they deem fit.