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Dust busters
Researchers look to understand damaging storms and howto better predict them 18 Oct 2024
The Arabian Peninsula is one of the world’s major sources of dust year round, contributing significantly to the amount of dust in the air in the Northern Hemisphere. Between 15 and 20 dust storms over the Arabian Peninsula per year impact all aspects of human life as well as marine ecosystems and the climate.
Sand and dust storms cause about U.S.$13 billion a year in damage to crops, livestock, infrastructure, human health and more in the Middle East and North Africa. The storms are also becoming more frequent, spanning longer periods of time and spreading to wider areas.
Having an early warning for dust storms would be invaluable, but the storms’ rapid development and spread make it difficult to predict when, where and how badly they will strike.
Hossein Hashemi, from Sweden’s Lund University, studies the causes and trends of dust storms and says with artificial intelligence and satellite data, we can define areas where we see that land is more susceptible to becoming new dust sources.
By combining remote sensing, advanced data modeling and machine-learning algorithms, Hashemi’s research team has mapped the entire Middle East, allowing it to study how dust sources vary over time.
“Previous studies have shown the destructive effects of dust storms on health and the economy in countries in the Middle East,” Hashemi writes in Atmospheric Pollution Research. “It is necessary to predict the region’s susceptibility to dust-storm sources considering spatiotemporal variability and provide insight into dust-generation mechanisms. Machine learning can be an effective technique, with experimental studies in northeastern Iran identifying dust sources with 91 percent accuracy.”
GETTING TO THE SOURCE
Hashemi’s team says the outcome can help policymakers identify susceptible areas and implement measures to reduce the likelihood of dust storms.
“It’s difficult to predict the sources of sand and dust storms,” says Jilili Abuduwaili of the Chinese Academy of Sciences. “Outbreaks depend not only on meteorological factors such as wind speed, precipitation and air temperature, but also on terrestrial factors such as vegetation cover and soil characteristics. However the integration of multiple remote-sensing and meteorological data with different spatial and temporal resolutions can help.”
Abuduwaili used four machine-learning methods to predict an area’s susceptibility as a dust-storm source. The research found that wind speed played the most important role in the model, followed by vegetation conditions and other land-surface characteristics.
An essential part of the dust cycle is the transportation of dust around the world. For this, the dust storm needs the atmospheric processes that determine all aspects of the storm — from its intensity to its duration. For the Arabian Peninsula, the shamal winds play a critical role. These northerly semi-permanent winds are thought to be the main meteorological driver for dust emissions year round, but Diana Francis, head of the Environmental and Geophysical Sciences lab at Khalifa University, is interested in why dust emissions over the southern parts of the Arabian Peninsula peak in the summer.
“This peak indicates the existence of a still-unknown but important mechanism for dust emissions,” she says. “Cyclogenesis, the formation of cyclones, has proven to be a major dust-emission mechanism over other arid regions, capable of generating dramatic dust storms. However, there’s been little attention given to dust activity associated with cyclogenesis over the Arabian Peninsula.”
A PRESSING NEED
Francis’ research found that most models fail to reproduce the key aspects of the dust cycle when compared with satellite and ground-based observations, and since these models are increasingly used for future climate simulations, there’s a pressing need to improve the overall representation of dust behavior.
“Global and regional weather and climate models are used to simulate the emission of dust and its interactions with the climate,” Francis tells KUST Review. “However, the large spatiotemporal heterogeneity of dust sources — from giant sand dunes to small ridges and furrows of an agricultural field, from short-lived dust devils to global dust transport — makes it extremely challenging to represent the dust cycle in climate models.”
Francis wants more in-situ measurements and remote-sensing observations from satellites to better understand the dust effect on climate, saying high-resolution simulations accounting for direct and indirect effects of dust could unravel the various physical mechanisms behind dust interactions with the climate.
“We urge the scientific community to pay attention to these details in global and regional climate models and make attempts to improve them so that all models can realistically represent the effects of dust on the climate in past, present or future simulations,” Francis tells KUST Review.
The Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) forecasts sand and dust storms in Europe, the Middle East and North Africa. Operated by the Meteorological State Agency of Spain, the Barcelona Supercomputing Center and the Barcelona Dust Regional Center, the website provides access to available dust forecasts and observations as well as relevant information on the advances of mineral dust research.
The SPRINTARS (Spectral Radiation Transport Model for Aerosol Species) model was developed at Japan’s Kyushu University to simulate the effects of atmospheric aerosols on the climate system at a global scale. It can be used to establish an effective monitoring and early warning system for sand and dust storms at regional and national levels.
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