News
January 10, 2026
New light scattering model to help assess and predict the state of marine systems

An international research team has developed a three-stream model of light scattering in the sea. It processes satellite data on the incoming and emitted light fluxes into information on water characteristics: presence of impurities, phytoplankton concentration, pollutants, and other parameters. The system of equations for this study was written by Ilya Chernov, Senior Researcher at the Institute of Applied Mathematical Research KarRC RAS. The model has been successfully tested in the Mediterranean Sea, and researchers are interested in trying it in application to the Arctic.
Scientists from Italy, Russia, and France have developed a three-stream mathematical model of radiation intensity. Using remote sensing data, it can determine the biogeochemical properties of seawater. This is important for understanding the quality and state of the ecosystem. The results of this study were published in the high-ranking international scientific journal Scientific Reports.

Light propagation through a body of water is a complex process. Professor Paolo Lazzari of the National Institute of Oceanography and Applied Geophysics (Italy) distinguishes three light streams: direct downward component, downward light stream that is already diffused in water, and upward stream of light reflected from the bottom or from particles in water.

Scientists analyze satellite and other data to determine how much light enters the water and how much comes out. Typically, the latter signal is always weaker because many components within the water column scatter and absorb light. Special equations written for this model by Ilya Chernov, Senior Researcher at the Institute of Applied Mathematical Research KarRC RAS calculate from satellite data how much light got "lost" within water depths. The coefficients used in this mathematical system indicate which specific particles have retained the light and in what quantities.

– To put it simply, a satellite sees a dark patch. People or algorithms make an inference: this could be oil, plankton, sand, and so on. The tools we use are mathematical and physical computations. After adjusting the coefficients so that the calculated signal matches the observed one, we can state that the dark patch is generated by specific particles of a certain size at a known depth. This approach helps describe in detail what is happening in the sea, producing data based on calculations rather than mere assumptions, – explained Doctor of Technical Sciences Ilya Chernov.


Ilya Chernov, Senior Researcher, Institute of Applied Mathematical Research KarRC RAS. Photo: Victoria Shvetsova / KarRC RAS Science Communication Office

The scientists have tested the three-stream model in application to the Mediterranean Sea. They established a BOUSSOLE site, where an autonomous fixed buoy was deployed, sampling bio-optical parameters every 15 minutes. Also, monthly cruises were conducted for bio-optical parameter sampling. The components tested included the concentration of chlorophyll-a and colored dissolved organic matter in water. The model's output proved comparable to data obtained from physical sensors.

– It's impossible to have sensors covering the water areas of all seas, so satellites offer a solution. Using remote sensing data and mathematical calculations, we can obtain information on the state of the marine system over an extensive area, – noted the Karelian scientist.

Experts emphasize however that when evaluating the system's performance, it is necessary to consider the specific behaviors of bio-optical and physical parameters in different ecological regions.

"The sensitivity experiments show the impact of parameter perturbations at the BOUSSOLE site, but it would be important to further evaluate how this approach works in other areas where phytoplankton optical parameters could be very different: different pigment compositions could influence absorption, or different size distributions could influence the spectral shape of the backscattering coefficient", – states the conclusion of the scientific paper.

The authors would be interested in conducting a similar study for Arctic ecosystems, particularly in the White Sea. Mathematician Ilya Chernov from Karelia and biogeochemist Paolo Lazzari from Italy have been actively collaborating for ten years, developing the JASMINE mathematical model, which describes water and ice dynamics in the White Sea.

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January 8, 2026
Karelian scientists surveyed the Mekong River Delta within a Russia-Vietnam project

Researchers from the Institute of Biology KarRC RAS Viktor Voronin and Dmitry Bityutsky took part in an expedition to the Mekong River Delta in Vietnam, which collected biological material for assessing the ecological status and biological resources of the Mekong Delta using biochemical profiling methods within an international cooperation initiative.
January 5, 2026
Archaeologist Svetlana Kochkurkina: “I wrote this book out of gratitude to people of Kurkijoki Village”

The new book "Kurkijoki. Archaeology, History, Culture" has turned into a notable event for the academic community, as well as for enthusiasts of Karelian archaeology and history. The authors of the monograph are Svetlana Kochkurkina, Leading Researcher, Archaeology Section ILLH KarRC RAS, and Marina Petrova, Director of the Kurkijoki Local Lore Centre. The work summarizes the findings from many years of research into the archaeology, history, and culture of the Kurkijoki Village and its surroundings.
January 3, 2026
Zoologists test biological samples from reindeer for toxic content

Karelian scientists have launched a new project as part of long-term studies of the state of the reindeer population. They will test biological samples from the animals for the presence of toxic elements – environmental pollutants. Zoologists are also continuing to monitor these red-listed animals using GPS-tracking collars and camera traps. The project gets funding from Severstal company. All wild reindeer populations in European Russia are listed in the national Red Data Book.