Abstract:The goal of this study is to investigate the variability of poor visibility events occurring hourly in the UAE and their relationship to climate dynamics. Hourly visibility observation data spanning more than three decades from ten stations across the country were used. Four intervals of low visibility, between 0.10 km and 5.0 km, were considered. Poor visibility records were analyzed under wet and dry weather conditions. The Mann-Kendall test was used to assess the inferred trends of low visibility records. The relationships between poor visibility measurements and associated meteorological variables and climate oscillations were also investigated. Results show that Fujairah city has the highest average visibility values under wet weather conditions, while Abu Dhabi city has the lowest average visibility values under both wet and dry conditions. Wet weather conditions had a greater impact than dry weather conditions on visibility deterioration in seven out of the ten stations. Results confirm that fog and dust contribute significantly to the deterioration of visibility in the UAE and that Abu Dhabi has been more impacted by those events than Dubai. Furthermore, the numbers of fog and dust events show steep increasing trends for both cities. A change point in poor visibility records triggered by fog and dust events was detected around the year 1999 at Abu Dhabi and Dubai stations after the application of the cumulative sum method. Increasing shifts in the means and the variances were noticed in the total annual fog events when Student's t-test and Levene's test were applied. In Abu Dhabi, the mean annual number of dust events was approximately 112.5 before 1999, increasing to 337 dust events after 1999. In Dubai, the number of dust events increased from around 85.5 to 315.6 events. The inferred fog and dust trends were compared to four climate indices. Results showed a significant correlation (positive and negative) between four climate indices and the occurrence of fog and dust events in the UAE.

This research aims at assessing land suitability for large-scale agriculture using multiple spatial datasets which include climate conditions, water potential, soil capabilities, topography and land management. The study case is in the Emirate of Abu Dhabi, in the UAE. The aridity of climate in the region requires accounting for non-renewable sources like desalination and treated sewage effluent (TSE) for an accurate and realistic assessment of irrigated agriculture suitability. All datasets were systematically aggregated using an analytical hierarchical process (AHP) in a GIS model. A hierarchal structure is built and pairwise comparisons matrices are used to calculate weights of the criteria. All spatial processes were integrated to model land suitability and different types of crops are considered in the analysis. Results show that jojoba and sorghum show the best capabilities to survive under the current conditions, followed by date palm, fruits and forage. Vegetables and cereals proved to be the least preferable options. Introducing desalinated water and TSE enhanced land suitability for irrigated agriculture. These findings have positive implications for national planning, the decision-making process of land alteration for agricultural use and addressing sustainable land management and food security issues.