Abdul-Wahab S. Mashat

Synoptic features associated with dust transition processes from North Africa to Asia

Aerosol index data from the total ozone mapping spectrometer satellite and reanalysis data from the National Center for Environmental Prediction and the National Center for Atmospheric Research are useful in the study of synoptic properties of the dust storms that carry dust from North Africa to Asia during the spring season for the period 1979 to 2006. In this study, we analyzed the synoptic properties of dust cases that pass through the transition zone between North Africa and Asia. We identified the dust cases to study by looking, inside transition zone, at events with an aerosol index greater than 2. We then divided the identified cases, depending on the spread and strength of the dust inside the transition zone, into seven categories ranging from weak events to moderate events to violent events. We found the common synoptic characteristics in all these categories as follows: The high pressure belt located over northern Africa allows the low pressure belt located over the South African Sahara to move northward; a pressure gradient between these two atmospheric systems directs from south to north; an increase in the pressure gradient leads to increased in both of the event’s dust and the amount of dust moves to North Africa from the Sahara; an additional pressure gradient between the western Azores high pressure system and the low pressure system located over the Arabian Peninsula directs from west to east; the stronger the pressure gradient, the greater the amount of dust in the event and moving a large amount of dust from Northeast Africa to Asia. To verify that these characteristics capture the essence of dust events from North Africa to Asia, we checked if they were also common to two additional extremes categories and two extremes events. The results confirmed the continued existence of these common characteristics.

Saudi-KAU Coupled Global Climate Model: Description and Performance

BackgroundA new coupled global climate model (CGCM) has been developed at the Center of Excellence for Climate Change Research (CECCR), King Abdulaziz University (KAU), known as Saudi-KAU CGCM.PurposeThe main aim of the model development is to generate seasonal to subseasonal forecasting and long-term climate simulations.MethodsThe Saudi-KAU CGCM currently includes two atmospheric dynamical cores, two land components, three ocean components, and multiple physical parameterization options. The component modules and parameterization schemes have been adopted from different sources, and some have undergone modifications at CECCR. The model is characterized by its versatility, ease of use, and the physical fidelity of its climate simulations, in both idealized and realistic configurations. A description of the model, its component packages, and parameterizations is provided.ResultsResults from selected configurations demonstrate the model’s ability to reasonably simulate the climate on different time scales. The coupled model simulates El Niño-Southern Oscillation (ENSO) variability, which is fundamental for seasonal forecasting. It also simulates Madden-Julian Oscillation (MJO)-like disturbances with features similar to observations, although slightly weaker.ConclusionsThe Saudi-KAU CGCM ability to simulate the ENSO and the MJO suggests that it is capable of making useful predictions on subseasonal to seasonal timescales.

Climatology of the autumn Red Sea trough

In this study, the Sudan low and the associated Red Sea trough (RST) are objectively identified using the mean sea level pressure (SLP) data from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis dataset covering the period 1955–2015. The Sudan low was detected in approximately 60.6% of the autumn periods, and approximately 83% of the detected low-pressure systems extended into RSTs, with most generated at night and during cold months. The distribution of the RSTs demonstrated that Sudan, South Sudan and Red Sea are the primary development areas of the RSTs, generating 97% of the RSTs in the study period. In addition, the outermost areas affected by RSTs, which include the southern, central and northern Red Sea areas, received approximately 91% of the RSTs originating from the primary generation areas. The synoptic features indicated that a Sudan low developed into an RST when the Sudan low deepened in the atmosphere, while the low pressures over the southern Arabian Peninsula are shallow and the anticyclonic systems are weakened over the northern Red Sea. Moreover, stabile areas over Africa and Arabian Peninsula form a high stability gradient around the Red Sea and the upper maximum winds weaken. The results of the case studies indicate that RSTs extend northward when the upper cyclonic and anticyclonic systems form a high geopotential gradient over Arabian Peninsula. Furthermore, the RST is oriented from the west to the east when the Azores high extends eastward and the Siberian high shrinks eastward or shifts northward.

MODIS satellite data evaluation for sand and dust storm monitoring in Saudi Arabia

ABSTRACT The impacts of wind-blown desert sand and dust are a major concern of environmental and climate study due to their global extent. This article investigates the sand and dust storms detection in Saudi Arabia using Moderate Resolution Imaging Spectroradiometer (MODIS) data, both from Terra and Aqua satellite systems for the years 2002–2011. Normalized Difference Dust Index (NDDI) is applied for the detection of sand and dust storms whilst MODIS band 31 is applied to discriminate atmospheric sand and dust from that present on the ground. In addition, the data from Meteosat satellite, AERONET station, and meteorological stations are used to validate NDDI-based sand and dust storm events. The results of the study show that NDDI can successfully identify and differentiate sand and dust storms from clouds whilst MODIS band 31 can discriminate aerial and surface sand and dust over Saudi Arabia. The results also show that the multi-source data, that is MODIS, Meteosat, AERONET, and meteorological stations, can be very valuable for tracking sand and dust storm events. As no such attempt in the past has been made in Saudi Arabia, it is envisaged that the results of this study will be helpful in planning remote-sensing data for the climate change study in the region.