Detection of aridity trends using statistical models and time series remote sensing datasets: A case of Mediterranean Region

Mediterranean region is one of the major hotspots based on global climate change. Understanding the complex relationship between aridity and spatiotemporal climate variables is crucial for effective ecosystem management. Previous studies showed that all aridity indicators have certain limitations, either conceptual, operational, or both, resulting in proxies for aridity estimations. There is an urgent need to accurately assess the aridity index in the context of regional climate change challenges. This study utilized several geospatial techniques and remote sensing datasets to analyze and map spatiotemporal aridity dynamics. Here, using 42 years (1981-2022) of climate data from 20 meteorological stations across Mediterranean basin countries, we applied the MK test and Sen’s slope to examine climate parameters. To provide accurate future aridity expansion 14 Global Climate Models (GCMs) were used. The test performed at a 95% (α = 0.05) confidence interval indicated that the detected trends in maximum temperature were not significant few countries (e.g., France, Libya, Greece, Tunisia, Syria, Portugal, and Morocco). Therefore, the statistics of the MK test showed a significant increase in mean temperatures, and a decrease in total precipitation was recorded at 73.33% of the weather stations, implying a rapid expansion of arid zones in the study area. The sensitivity coefficient proved that total precipitation contributed the most to aridity index changes, as a 10% increase in maximum temperature resulted in an increase in aridity index almost throughout the basin. Hyper-arid zone will increase by 0.4% whereas humid zone will decline by approximately 2.1%. The Pearson correlation coefficient between aridity and major climatic factors is relatively low and is not statistically significant (p< 0.05). Notably, these results shed light on the understanding of the influence of climate factors on aridity. More in-depth studies are required to analyze the uncertainty in historical and future climate data. This will help to address one of the key challenges faced in Mediterranean countries and enhance sustainable resource management.