Analysis of sand and dust storm events over Saudi Arabia in relation with meteorological parameters and ENSO

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Abdulhaleem H. Labban ◽  
Mohsin Jamil Butt
2021 ◽  
Author(s):  
Essam Mohammed Alghamdi ◽  
Mazen Ebraheem Assiri ◽  
Mohsin Jamil Butt

Abstract Sand and dust storm events are frequent natural hazards in the Kingdom of Saudi Arabia. Sand and dust storm monitoring is therefore essential to mitigate their environmental-related issues. Satellite remote sensing has been successfully used for sand and dust storm monitoring in various parts of the world. In the current endeavor, we are applying the Global Dust Detection Index (GDDI) on Moderate Resolution Imaging Spectroradiometer (MODIS) data onboard Terra satellite to monitor sand and dust storm activities over the Kingdom of Saudi Arabia. In the current study, fourteen sand and dust storm events are analyzed between the years 2000 to 2017. The GDDI based results are validated by using MODIS combined Dark Target (DT) and Deep Blue (DB) Aerosol Optical Depth (AOD) product, Meteosat satellite images, ground-based meteorological stations data, and AOD data from AERONET (Aerosol Robotic Network) stations in the study area. Also, GDDI based results are analyzed by determining algorithm accuracy, Probability Of Correct positive Detection (POCD), and Probability Of False positive Detection (POFD). Results of the study show that GDDI can successfully identify sand and dust storm events with various threshold values over the Kingdom of Saudi Arabia. It is envisaged that the outcome of this study would be very beneficial to understand sand and dust storm characteristics in the study region.


2019 ◽  
Vol 16 (3) ◽  
pp. 191-208
Author(s):  
Amos Kalua ◽  
Soo Jeong Jo ◽  
Seyedreza Fateminasab ◽  
Sana’a Al-Rqaibat ◽  
Christoph Opitz

Geosciences ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 162 ◽  
Author(s):  
Sarah Albugami ◽  
Steven Palmer ◽  
Jonathan Cinnamon ◽  
Jeroen Meersmans

Monthly meteorological data from 27 observation stations provided by the Presidency of Meteorology and Environment (PME) of Saudi Arabia were used to analyze the spatial and temporal distribution of atmospheric dust in Saudi Arabia between 2000 and 2016. These data were used to analyze the effects of environmental forcing on the occurrence of dust storms across Saudi Arabia by considering the relationships between dust storm frequency and temperature, precipitation, and wind variables. We reveal a clear seasonality in the reported incidence of dust storms, with the highest frequency of events during the spring. Our results show significant positive relationships (p < 0.005) between dust storm occurrence and wind speed, wind direction, and precipitation. However, we did not detect a significant relationship with temperature. Our results reveal important spatial patterns, as well as seasonal and inter-annual variations, in the occurrence of dust storms in Saudi Arabia. For instance, the eastern part of the study area experienced an increase in dust storm events over time, especially in the region near Al-Ahsa. Similarly, an increasing trend in dust storms was also observed in the west of the study area near Jeddah. However, the occurrence of dust storm events is decreasing over time in the north, in areas such as Hail and Qaisumah. Overall, the eastern part of Saudi Arabia experiences the highest number of dust storms per year (i.e., 10 to 60 events), followed by the northern region, with the south and the west having fewer dust storm events (i.e., five to 15 events per year). In addition, our results showed that the wind speeds during a dust storm are 15–20 m/s and above, while, on a non-dust day, the wind speeds are approximately 10–15 m/s or lower. Findings of this study provide insight into the relationship between environmental conditions and dust storm occurrence across Saudi Arabia, and a basis for future research into the drivers behind these observed spatio-temporal trends.


2013 ◽  
Vol 05 (10) ◽  
pp. 1084-1094 ◽  
Author(s):  
Varoujan K. Sissakian ◽  
Nadhir Al-Ansari ◽  
Sven Knutsson

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