“The impact of glacier algae on the ice sheet also inspires us to think more about the vital but not well-understood linkages between climate, cryosphere, and microbes.”
Shujie Wang joined the Department of Geography in fall 2020 as an assistant professor. Her interests include remote sensing, machine learning, numerical modeling, ice flow dynamics, snow and ice albedo, and glacier algae.
“I was so surprised to learn that life could develop in such cold and barren environments,” Wang said. “Glacier algae generate a brownish-grey purpurogallin pigment that can darken the ice surface and can now be observed and mapped using data from satellites.”
Wang and colleagues conducted the first study utilizing the advanced capability of Sentinel‐3 satellites in detecting chlorophyll‐a, a typical pigment generated by algae, during the summers of 2016 and 2017.
Glacial algae had not received much attention until recently, although the presence of this supraglacial phenomenon was first documented in 1872. “Now we know that glacier algae blooms play an important role in enhancing the surface melting of the Greenland ice sheet through their role in darkening the ice sheet surface and reducing the albedo,” Wang said. As a onetime aspiring biologist who accidently became a geographer, Wang was inspired to study ice sheets after attending a seminar related to climate change and polar ice sheets.
“My first thought as a geographer was ‘how can I map this,’” Wang said. “Because I had field sampling experience studying harmful algal blooms in lakes, I quickly theorized that satellite sensors designed for ocean color studies could also be used to map glacial algae on the ice sheet surface.”
Wang likes to employ fieldwork and remote sensing in a complementary way.
“Fieldwork is very important for us to obtain ground truth samples,” Wang said. “Ground truth is important for remote sensing in two ways: it provides us with prior knowledge to be able to derive information from remote sensing data; and it validates the retrieved information from remote sensing data.”
Wang said it is logistically difficult to map regional patterns by conducting fieldwork only, particularly when studying the ice sheets, which are remote and inaccessible.
Observations from the Sentinel-3 satellite in 2016 (center) and 2017 (right) show widespread algal blooms. Credit: Wang et al., 2018, https://doi.org/10.1029/2018GL080455; data from Copernicus Sentinel-3/ESA.
“Remote sensing provides a synoptic and efficient way to characterize geospatial phenomena across large spatial scales,” Wang said. “Besides, we can use various remote sensing techniques (gravimetry, microwave, altimetry, and multispectral) to ‘measure’ the ice sheets from different perspectives and study different processes.”
Wang said she continues to collaborate with climate modelers to parameterize the biological impact of glacier algae into climate models and with biologists and geochemists to understand the nutrient cycles of the supraglacial microbiome.
She is also working on combining satellite imagery, satellite altimetry data (particularly ICESat-2), and machine learning techniques to study the morphological changes of ice surface, such as fractures, supraglacial lakes, and river channels.
“As observational and modeling data for Earth and climate systems are increasing in both quantity and quality, the emerging data mining and machine learning methods are becoming more and more important to discover patterns and relationships of various processes and to predict future dynamics,” Wang said.
She intends to incorporate those novel methods with remote sensing and climate modeling to continue her study of the ice sheets.
“The spatiotemporal development of glacier algae is not well understood, and it is important to know how much glacier algae contributes to surface mass loss,” Wang said, “The impact of glacier algae on the ice sheet also inspires us to think more about the vital but not well-understood linkages between climate, cryosphere, and microbes.”