Climate change in the UAE: Modeling air temperature using ARIMA and STI across four bio-climatic zones

Abstract

Background: Standardizing climate-related indices and models across spatial and temporal scales presents a challenge. Especially when predicting climatic conditions in the era of climate change. The present work aims to assess the use of ARIMA (Auto Regressive Integrated Moving Average) modeling approach coupled with STI (Standardized Temperature Index) to predict temperature anomalies across four bio-climatic regions within the United Arab Emirates (UAE). Methods: We used monthly temperature data from NOAA Land-Based Station Data for Abu Dhabi, Al-Ain, Dubai and Sharjah. ARIMA modeling and STI assessment of climatic events were used to predict and study the dynamics of climate of the four zones. The use of such forecasting powers was intended for an ultimate aim to study the impact of climate change on land use and land cover changes. Results: Data were not auto-correlated as shown by the Box-Ljung test. Additionally, the box-plots showed that Abu Dhabi had the highest median temperature. The ARIMA forecasting suggested that Dubai is predicted to have increasing trend of average temperatures until 2030. "Extremely hot" events were highest for Al-Ain (i.e. 9), followed by Abu Dhabi, Dubai and Sharjah. Dubai had the highest occurrences of "Moderately hot" events, when compared to all other studied zones. Further, events classified as "very cold" were in the order of 20, 10, and 8, for Dubai, Sharjah, and for each of Abu Dhabi and Al-Ain, respectively. Conclusions: The temperature is predicted to increase in Dubai and Sharjah, with each representing a different bio-climatic zone. This was also reflected in the STI assessment of the historical temperature. "Moderately hot" and "very cold" events for Dubai were the highest as compared to the other studied zones in the UAE. It is therefore believed that ARIMA, coupled with STI, may be a valid approach to forecast temperature and analyse extreme events.