���Ҵ�ý�ƽ������

���Ҵ�ý�ƽ������ researchers develop a tool that can model phytoplankton biomass extremes in the ocean in ways that conventional satellites often can’t

Phytoplankton, the tiny, single-celled organisms that live in oceans, are more important than some realize. They are the base of the marine food web and help countless other species in the oceans thrive and survive.��

Satellite technology and its continuous advancements have given the world a better understanding of the oceans and the life within them, specifically phytoplankton. But gaps still remain in what satellites can show about the activity of phytoplankton.��

Unfortunately, phytoplankton and the oceans they call home are suffering, says Nicole Lovenduski, a University of Colorado Boulder professor of atmospheric and oceanic sciences (ATOC) and director of the Institute of Arctic and Alpine Research (INSTAAR). “You can think of (phytoplankton) as the grasses of the terrestrial biosphere,” she says. “They’re the things that build the foundation that everything else eats.”

In a conducted in partnership between ���Ҵ�ý�ƽ������ and the National Center for Atmospheric Research (NCAR), Lovenduski and her research colleagues found that despite what can be seen through satellite imagery, a lot of phytoplankton is obscured—often by clouds or low sunlight.��

��

A mixed phytoplankton community. (Image: Stephanie Anderson/University of Rhode Island/NASA)

The researchers set out to discover what the observational limitations were in detecting phytoplankton biomass extremes in the oceans, building a satellite emulator that mimics the same blind spots a real satellite would encounter: sea ice, clouds, low sun angles. This allowed them to compare what the model predicted to what the satellite actually saw, ultimately revealing the gaps between the two. By combining interdisciplinary expertise, they were able to find the holes in detecting these phytoplankton biomass extremes.��

"Statistically, by definition, there have to be extremes in everything—you think about a normal distribution (referencing phytoplankton bloom events), the extremes are on the tail of that bell curve, so mathematically they must exist,” Lovenduski explains. “And I found maybe four papers on this, and that was it. Why isn’t anyone writing about this?... And then I had the a-ha moment: It's because no one can see them in the satellite data."��

As Lovenduski explains, extremes are important for the ecosystem: “If there's a huge phytoplankton bloom, that's going to have ramifications for the whole ocean ecosystem in that region. Similarly, if blooms fail to occur, that's going to be devastating for the ecosystem.”

These high extremes refer to a higher-than-normal concentration of phytoplankton in one specific region or area. On the other hand, if a bloom is supposed to happen and it doesn’t—a low extreme—marine life in that region that rely on phytoplankton for their diet can be severely affected, which in turn causes a ripple effect across other species in the ocean.��

Combining clouds, ocean and ice��

To study these issues, Lovenduski worked with ATOC PhD graduates Genevieve Clow and Samuel Mogen, an INSTAAR postdoctoral scholar, as well as ATOC Professor Jennifer Kay and Michael Levy and Keith Lindsay of the NCAR Climate and Global Dynamics Laboratory. The researchers aimed to find a better way to visualize these mysterious single-celled organisms that do so much for our marine ecosystem.��

To solve the problem of limited visualization of phytoplankton, the team built what they call a satellite emulator within an Earth system model—a tool that allows them to “see” the modeled ocean the same way a satellite does.��

"It is an approach that they've used in atmospheric science before to simulate satellite observations of clouds, and we apply that approach to a completely different thing, which is the pigment chlorophyll in the ocean,” Lovenduski says. “Our ability to detect that from space turns out to be a really important limit on our ability to detect extremes.”��

Chlorophyll, a green pigment that phytoplankton and plants use to absorb sunlight, plays a similar role in phytoplankton as it does in plants. It is why large phytoplankton clusters and algae appear green. Chlorophyll helps phytoplankton turn sunlight, water and carbon dioxide into energy while releasing oxygen.

However, because of the limitations caused by cloud coverage blocking satellite imaging of chlorophyll, Kay emphasizes that using field samples as well as satellite imagery is vital to a model: “You can learn so much from the assets that we have in space, and sometimes those assets, while providing an incomplete picture of things, can also provide the space-time perspective that's super important for understanding this change in variability.”��

Kay also mentions that a combination of field sampling and the use of satellites are critical to understanding what's going on in the oceans, noting how her group often partners with Boulder-based NCAR scientists to validate Earth system models with data.��

As a key part of the research, Clow developed a tool that ran model simulations on a computer. Clow flew a virtual satellite inside the model, sampling the modeled ocean similar to how a real satellite would see the ocean.��

Conventional atmospheric satellites wait for reflected light to bounce off the ocean and come back up but, Lovenduski notes, so “if there's a cloud in the way and if the sun angle is really low, there's not enough radiation to come back to the satellite, so we made sure that we included that effect in the model. And if there's sea ice growing on the surface of the ocean, (the satellite) can't see the chlorophyll underneath, but the model still predicts what the chlorophyll is.”��

A phytoplankton bloom off the coast of Iceland. (Image: NASA)

By being able to account for these discrepancies in the model, Clow says that the main takeaway from this research is that “our observations of phytoplankton are limited, and that we need to combine observations and models in order to gain a complete picture of what's happening with phytoplankton in the ocean."��

One of the most significant findings in this research included the fact that globally, satellites can only detect about 10% of daily low extremes and 19% of daily high extremes. Kay explains that clouds “obscure what you can view in the ocean. It's hard to penetrate into it, and from space you're not going to get that kind of information.”��

Clow’s idea for an Earth system model study arose from that issue: “Satellites can only see the surface of the ocean, but in some regions, phytoplankton tend to grow much deeper, and so what satellites can see at the surface isn't representative of what's happening throughout the water column,” Clow explains, adding that this is the main issue with being able to visualize the amount of phytoplankton in a given area.

The stressed oceans

Despite the technical advances represented in the model, the researchers express concerns about the state and health of Earth’s oceans.��

“There are so many environmental stressors that are hitting the ocean all at once, so it's getting warmer, and that is in turn is causing the ocean to lose oxygen with time,” Lovenduski says. “That also is making it more difficult for nutrients that are below the surface to get up to the surface and fuel this biological productivity that's so important for the marine food web.

“In addition, the ocean is taking up carbon dioxide from the atmosphere, which is great for mitigating global warming but actually causing the ocean to become acidic. So, the ecosystems of the ocean are experiencing simultaneous difficult stressors all at once. It doesn't paint a very nice picture."��

Phytoplankton observability matters as a sign of what’s happening in our climate, the researchers say. Kay points out that fisheries and other marine-based industries rely on knowledge of extreme events happening in the world. “If we have a heat wave in the atmosphere, we’re kind of miserable,” she says. “So, it can affect life in the ocean as well.”��

Kay notes that though Colorado is far from the ocean, residents here still experience similar effects: “I think we can start to expect warmer days and more heat waves and more demand on water resources. I think we all felt that pretty acutely in Colorado this past winter, having 80-degree days in March when we're supposed to have the peak snowpack.”��

“Make the model look like reality”��

The recently published paper is an important step in continuing research. Clow is beginning a post-doctoral��research position at the Scripps Institute of Oceanography, where she’ll model the impact of fish on the carbon cycle.

Lovenduski’s group is applying the “make the model look like reality” idea to a fleet of ocean floats that “live forever, they don't ever run out of battery like the real world floats, but they also can do a profile every four hours instead of every 10 days.”��

This, she says, will allow the team to, “improve the frequency of sampling, and then we can look at what an ideal float configuration in the real world looks like for the thing that you're interested in sampling.”��

Kay is working with a newly launched satellite, called EarthCARE, to better understand the water cycle and how the energy budget and resources will be affected by measuring precipitation near the surface.��

The researchers note that the experience of developing a tool to model the detectability of phytoplankton biomass extremes in the ocean, as especially the interdisciplinary approach to this work, is informing their further research.��

Did you enjoy this article?����Passionate about atmospheric and oceanic sciences?��Show your support.

��