Temporal and spatial characteristics of Saudi Arabian dust storms, with focus on associated air parcel trajectories, are investigated using station and gridded weather observations and remotely‐sensed aerosol optical depth (AOD). For 13 focal stations, an extensive pool of 84‐h backward trajectories is developed for dust storm days, and the trajectories are grouped into 3–5 representative clusters based on the K‐means technique and Silhouette Coefficients. Saudi Arabian dust storms are most prominent during February–June, with a mid‐winter peak along the southern coast of the Red Sea, spring peak across northern Saudi Arabia around the An Nafud Desert, and early summer peak in eastern Saudi Arabia around the Ad Dahna Desert. Based on backward trajectories, the primary local dust source is the Rub Al Khali Desert and the primary remote sources are the Saharan Desert, for western Saudi Arabia, and Iraqi Deserts, for northern and eastern Saudi Arabia. During February–April, the Mediterranean storm track is active, with passing cyclones and associated cold fronts carrying Saharan dust to Saudi Arabian stations along the northern coast of the Red Sea. Across Saudi Arabia, the highest AOD is achieved during dust storms that originate from the Rub Al Khali and Iraqi Deserts. Most stations are dominated by local dust sources (primarily Rub Al Khali), are characterized by three dominant trajectory paths, and achieve AOD values exceeding 1. In contrast, for stations receiving predominantly remote dust (particularly Saharan), 3–5 trajectory paths emerge and AOD values only reach approximately 0.6 as dust is lost during transport.

The observed climatic controls on springtime and summertime Saudi Arabian dust activities during 1975-2012 are analyzed, leading to development of a seasonal dust prediction model. According to empirical orthogonal function analysis, dust storm frequency exhibits a dominantly homogeneous pattern across Saudi Arabia, with distinct interannual and decadal variability. The previously identified positive trend in remotely sensed aerosol optical depth since 2000 is shown to be a segment of the decadal oscillation in dust activity, according to long-duration station record. Regression and correlation analyses reveal that the interannual variability in Saudi Arabian dust storm frequency is regulated by springtime rainfall across the Arabian Peninsula and summertime Shamal wind intensity. The key drivers of Saudi Arabian dust storm variability are identified. Winter-to-spring La Niña enhances subsequent spring dust activity by decreasing rainfall across the country's primary dust source region, the Rub' al Khali Desert. A relatively cool tropical Indian Ocean favors frequent summer dust storms by producing an anomalously anticyclonic circulation over the central Arabian Peninsula, which enhances the Shamal wind. Decadal variability in Saudi Arabian dust storm frequency is associated with North African rainfall and Sahel vegetation, which regulate African dust emissions and transport to Saudi Arabia. Mediterranean sea surface temperatures (SSTs) also regulate decadal dust variability, likely through their influence on Sahel rainfall and Shamal intensity. Using antecedent-accumulated rainfall over the Arabian Peninsula and North Africa, and Mediterranean SSTs, as low-frequency predictors, and tropical eastern Pacific and tropical Indian Ocean SSTs as high-frequency predictors, Saudi Arabia's seasonal dust activity is well predicted.

[1] Temporal and spatial variations in atmospheric dust over Saudi Arabia are studied for 2000-2010 using satellite and ground-based aerosol optical depth (AOD) and station dust storm observations. These data sets show a consistent seasonal cycle in dust activity, which peaks in spring-summer in northern-central Saudi Arabia and in early spring and summer across southern-western Saudi Arabia, associated with strong winds and westerly transport, respectively. Over the desert regions, anomalies in dust activity from satellite and station observations are highly correlated on the monthly timescale and statistically consistent on the daily timescale. However, the coastal and mountainous regions exhibit limited consistency between these data sets, likely associated with the coarse spatial resolution and short sampling time in the satellite data, as well as non-aeolian aerosol contamination. We conclude that satellite AOD is a reliable index for dust activity over desert regions but not over low dust, coastal, and topographically complex regions in Saudi Arabia.Citation: Yu, Y., M. Notaro, Z. Liu, O. Kalashnikova, F. Alkolibi, E. Fadda, and F. Bakhrjy (2013), Assessing temporal and spatial variations in atmospheric dust over Saudi Arabia through satellite, radiometric, and station data, J. Geophys.

Riyadh, the capital of the Kingdom of Saudi Arabia, has experienced unusual levels of urbanization in the past few decades, making it one of the fastest growing cities in the world. This paper examines flood hazards in the rapidly urbanizing catchment of Al-Aysen in Riyadh. Remote sensing and geographic information system techniques were employed to obtain and prepare input data for hydrologic and hydraulic models, with the former based on the very popular curve number approach. Due to the limited nature of the rainfall data, observations from two rain gauges in the vicinity of the catchment were used to estimate design storms. The hydrologic model was run in a semi-distributed mode by dividing the catchment into many sub-catchments. The impact of urbanization on run-off volume and peak discharge resulting from different storms was investigated, with various urbanization scenarios simulated. Flood hazard zones and affected streets were also identified through hydrologic/hydraulic model simulation. The mismatch between administrative and catchment boundaries can create problems in flood risk management for similar cities since hydrologic processes and flood hazards are based on the hydrologic connectivity. Since flooding events impact the road network and create driving hazards, governmental decision-makers must take the necessary precautions to protect drivers in these situations.

Due to the importance of database systems, integration between two Geomatics sciences, GIS and Remote Sensing has been made in order to support and serve various sectors in Jordan. GIS has been used to create layers that can show decision makers in a simple, easy and flexible manner. Remote Sensing will be used in creating images of how Jordan is seen from space, which will give the users more information and an overview about the study area. Satellite images could be converted into digital image maps, using digitizing procedures. The features viewed in the original scene could be studied by using different remotely sensed techniques. Landsat-7 (ETM+) and SPOT images were implemented, in order to extract the information needed for the topography of the region, land cover areas, boundaries, drainage patterns, road networks, man-used areas, vegetated areas and many other features in Al-Salt areas. The validity and the appropriateness of GIS and Remote Sensing techniques, particularly data fusion of images were evaluated in relation to visualization.