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Feature - Gridding the aerosol problem

Feature - Gridding the aerosol problem

Image courtesy BEinGRID

It can be difficult to measure the number of aerosols - tiny particles suspended in the air - that are in our planet's atmosphere.

Such knowledge is important in a number of ways, as aerosols can have an effect upon everything from short-term air-quality forecasting to predicting the effects of aerosols on global warming. At least one climatologist says that on a long-term, global scale, aerosols will make India's monsoons more intense, and Australia's droughts hotter and longer. So, wet areas will be wetter, and dry areas drier. (See 7 January 2009 iSGTW, "Opinion - UK grid researchers aid efforts to understand climate change.")

Tracking where aerosols come from, where they tend to collect, and where they tend to "sink" on a planetary scale is a tricky business as well . Due to wind and weather patterns, sometimes the most pristine, remote areas accumulate the most aerosols.

To collect raw data, researchers rely upon information from Earth observation satellites. But how to deal with the huge stream of terabytes of data coming in - especially as some scientists want to do studies in real-time?

To solve this problem, BEinGRID developed a way to produce aerosol maps using the grid to speed up processing of satellite-generated data.

European Space Agency satellite data depicting a map of aerosols in the atmosphere. (Black represents no aerosols, purple is some aerosols, and red is the most aerosols.) Image courtesy GlobAerosol

Making maps

Called "GlobeAerosol," the project was led by GMV Aerospace and Defence, which had a strong background in Earth observation techniques, and strong ties to organizations such as the European Space Agency and public initiatives such as the Global Monitoring Environment and Security project. Terradue acted as technology provider, supporting distributed spatial data management and high performance computing applications, while the information management company ATOS Origin acted as business consultant and the Italian National Research Council (known as CNR) supported the evaluation of results.

Because the Earth observation data is acquired from different satellites with different acquisition modes, it created a challenge for data analysis. The complexity and time execution of the algorithms made for a particular challenge. In addition, storage and dissemination of the aerosol data was a problem, as the information must be available to end users for long periods.

But by working together, the GlobeAerosol team found that distributed computing allowed for a seamless allocation of required resources. By having computing resources operate in parallel, different algorithms could be run simultaneously, thereby removing processing bottlenecks.

In addition, a "gridded" GlobeAerosol allowed for high-quality maps to be created from the fusion of different sources, finished products could be turned around in a shorter time period, old aerosol maps could be reprocessed, and new resources added without stopping the service chain. In addition, by using the grid, researchers did not have to worry about over-reliance on a single node; with a distributed system, results could still be obtained even if there was a failure at any one point.

"Thanks to the grid-based solution and to the fusion of Earth observatory information, aerosol maps are now available for air quality forecasting and long-term pollution trends, and it is no longer a question of missing information," said Antonio Tabasco, head of division for GMV. "Now aerosol maps are promptly generated with the right quality and operational warranties."

-Dan Drollette, iSGTW. Portions reprinted from BEinGRID

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