Advances in Research

Aims: In this study a time series modeling was developed to predict the annual warming trend at coast Libya in the second decade of the 21^st century using ARIMA model, and performing an evaluation for the results significance.

Study Design: Utilizing Box-Jenkins method through, the stage of identification, parameter estimation and diagnosis, finally, a forecast of the annual surface temperature trend on Libya in the second decade of the 21^st century was assembled, together with an evaluation of the significance of the predicted warming trend.

Place and Duration of Study: Annual surface absolute temperature (ASAT) from 16 stations belonging to the coast of Libya during the period of (1892-2010) was used.

Results: The most optimum two prediction models obtained for the above data, are non-seasonal linear trend model ARIMA (3-1-2) and quadratic trend model ARIMA (3-2-3). We found that the forecasted values followed the upward trend present in the data and the pattern of results almost followed the pattern predicted with a correlation value of approximately 80% for both models. According to linear Trend model, an increase in temperature of 0.12°C/decade and according to quadratic model, an increase of 0.53°C/decade had been predicted until the year 2020. This increase in temperature is the same as what was predicted by the United Nations (from 1.3°C to 5.8°C between the year 1990 and 2100).

Conclusion: The two models, individually, produced the best overall performance in making short-term (∼10-year) predictions of annual surface absolute temperature in Libya. It can be used as a supplemental tool for environmental planning and decision making concerned with other environmental models.