The Michigan Engineer News Center

A new, low-cost way to monitor snow and ice thickness to evaluate environmental change

Mohammad has developed a new way to remotely measure the thickness of ice and snow with a technology he calls wideband autocorrelation radiometry (WiBAR). | Short Read
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Mohammad Mousavi, PhD student in ECE, earned a Weisnet Medal at the Eastern Snow Conference for his paper “Elevation Angular Dependence of Wideband Autocorrelation Radiometric (WiBAR) Remote Sensing of Dry Snowpack and Lake Icepack,” co-authored by co-advisor Dr. Roger De Roo (Associate Research Scientist in the Department of Climate and Space Sciences and Engineering), Prof. Kamal Sarabandi, and Prof. Anthony England. The Weisnet Medal is presented to the best student paper at the conference. Mohammad has developed a new way to remotely measure the thickness of ice and snow with a technology he calls wideband autocorrelation radiometry (WiBAR), offering lower cost, lower power, and more flexibility than competing methods.

As human activity continues to effect the climate, demand grows for accurate remote sensing instruments and techniques for monitoring environmental change. In particular, understanding the changing behavior of ice and snow in different regions is vital to effective water supply management.

NASA is working with a variety of researchers as part of their SnowEx project to push different remote sensing techniques to the limit and find the best way to gather this data. Mohammad’s contribution uses microwave radiometer systems that are low in both cost and power consumption, and can operate in all weather conditions.

Existing techniques that use these systems are inflexible – researchers need to calibrate their algorithms to each new terrain they measure. These calibrations become complicated and unworkable for terrains more complex than the Great Plains. Mohammad’s WiBAR system solves this issue by sensing the time it takes microwaves to propagate through the snow and ice and comparing it with expected time from manual measuring.

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IMAGE:  Mohammad's system measures the lake icepack using a wideband autocorrelation radiometer, or WiBAR. He compares this measurement with ground truth measurements of the icepack and the snowpack on top, seen on the right.

In lab and field tests, WiBAR works at a variety of angles. Mousavi took the technology to the U-M Biological Station at Douglas Lake to test it on lake icepacks throughout winter 2016, and will deploy the whole system in a truck to measure snowpacks nearby for the duration of the coming winter.

Currently, this and other remote ice and snow measurements don’t work on snow that is too wet – water easily absorbs the microwaves and interrupts the signal. The future of this project is to find a way to work with wet snow, and also to test the current technology in moving airplanes.

Mohammad will continue exploring this technology in his PhD dissertation, and hopes to continue related research in industry after he graduates. Prof. Sarabandi is the Rufus S. Teesdale Professor of Engineering and Director of U-M’s Radiation Laboratory, and has shaped the field of radar remote sensing for more than twenty years. Prof. England, Dean of the College of Engineering and Computer Science at U-M Dearborn, was influential in the field of climate studies as one of the first researchers to note the link between the climate and the water cycle. Roger De Roo is an associate research scientist in U-M’s department of Climate and Space Sciences and Engineering.

system to measure climate change through snow
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Catharine June
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The electrons absorb laser light and set up “momentum combs” (the hills) spanning the energy valleys within the material (the red line). When the electrons have an energy allowed by the quantum mechanical structure of the material—and also touch the edge of the valley—they emit light. This is why some teeth of the combs are bright and some are dark. By measuring the emitted light and precisely locating its source, the research mapped out the energy valleys in a 2D crystal of tungsten diselenide. Credit: Markus Borsch, Quantum Science Theory Lab, University of Michigan.

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