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Virtual contact lenses for radar satellites

Algorithm improves sea level measurements

Date:
April 16, 2018
Source:
Technical University of Munich (TUM)
Summary:
Radar satellites supply the data used to map sea level and ocean currents. However, up until now the radar's 'eyes' have been blind where the oceans are covered by ice. Researchers have now developed a new analysis method to solve this problem.
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Radar satellites supply the data used to map sea level and ocean currents. However, up until now the radar's "eyes" have been blind where the oceans are covered by ice. Researchers at the Technical University of Munich (TUM) have now developed a new analysis method to solve this problem.

The melting of the polar ice cap would have a drastic effect: Sea level would rise by several meters around the world, impacting hundreds of millions of people who live close to coasts. "This means one of the most important questions of our time is how climate change is affecting the polar regions," explains Dr. Marcello Passaro of the TUM German Geodetic Research Institute.

The blind spot of the radar "eye"

But changes in sea level and ocean currents in the ice-covered regions of the Arctic and Antarctic in particular are very difficult to detect. The reason: The radar signals of the altimeter satellites that have been surveying the surfaces of the earth and oceans for more than two decades are reflected by the ice at the poles. This renders the water underneath the ice invisible.

But ocean water also passes through cracks and openings in the permanent ice, reaching the surface. "These patches of water are however very small and the signals are highly distorted by the surrounding ice. Here standard evaluation methods like those used for measurements made on the open seas are incapable of returning reliable results," Passaro points out. Together with an international team he has now developed a data analysis method which sharpens the focus of the radar's eyes.

An algorithm for all occasions

The core of this virtual "contact lens" is the adaptive algorithm ALES+, (Adaptive Leading Edge Subwaveform). ALES+ automatically identifies the portion of the radar signal which is reflected by water and derives sea level values using this information only.

This makes it possible to precisely measure the altitude of the ocean water which reaches the surface through ice cracks and openings. By comparing several years of measurements, climate researchers and oceanographers can now draw conclusions about changes in sea level and ocean currents.

"The special thing about our method is that it is adaptive," Passaro notes. "We can use one and the same algorithm to measure sea level in both open and ice-covered ocean areas. ALES+ can also be used for coastal waters, lakes and rivers. Here the signals are highly varied, but always exhibit certain characteristic properties which the system then learns." The scientists were able to use a test scenario in the Greenland Sea to demonstrate that ALES+ returns water levels for ice-covered and open ocean regions which are significantly more precise than the results of previous evaluation methods.


Story Source:

Materials provided by Technical University of Munich (TUM). Note: Content may be edited for style and length.


Journal Reference:

  1. Marcello Passaro, Stine Kildegaard Rose, Ole B. Andersen, Eva Boergens, Francisco M. Calafat, Denise Dettmering, Jérôme Benveniste. ALES Adapting a homogenous ocean retracker for satellite altimetry to sea ice leads, coastal and inland waters. Remote Sensing of Environment, 2018; DOI: 10.1016/j.rse.2018.02.074

Cite This Page:

Technical University of Munich (TUM). "Virtual contact lenses for radar satellites." ScienceDaily. ScienceDaily, 16 April 2018. <www.sciencedaily.com/releases/2018/04/180416105811.htm>.
Technical University of Munich (TUM). (2018, April 16). Virtual contact lenses for radar satellites. ScienceDaily. Retrieved November 20, 2024 from www.sciencedaily.com/releases/2018/04/180416105811.htm
Technical University of Munich (TUM). "Virtual contact lenses for radar satellites." ScienceDaily. www.sciencedaily.com/releases/2018/04/180416105811.htm (accessed November 20, 2024).

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