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Contract number
Time span of the project

As of 01.11.2022

Number of staff members
scientific publications
Objects of intellectual property
General information

Name of the project: Satellite oceanology, physical oceanology, interaction of the ocean and the atmosphere, atmospheric boundary layers, remote probing, data processing, web technologies

Goals and objectives

Research directions: Satellite oceanology, physical oceanology, interaction of the ocean and the atmosphere, atmospheric boundary layers, remote probing, data processing, web technologies

Project objective: Scientific research in the field of development of new methods and technologies for processing, analysis and proliferation of satellite data, implementation of results of this work into social and economical domains by commercialization of developed products and technologies

The practical value of the study
Scientific results:

  • A modeling of the boundary of the ocean–atmosphere interface in moderate and strong winds.

    • Building modernized models of the spectrum of wind waves, breaking of waves and the impact of the inhomogeneity of the marine environment on the surface of the sea.
    • Developing models of the atmospheric boundary layer accounting for wind waves and their crashing on flows of impulse, heat and humidity. The model is oriented towards the creation of physically substantiated parameterizations of the laws of the resistance of the surface of the sea under extreme wind and wave conditions with subsequent implementation into atmospheric dynamics models.
    • Building physical models of the formation of satellite radiolocation images and radio-brightness temperature fields of the ocean at an arbitrary combination of polarizations and frequencies and their application to modeling wave and wind fields during extreme weather phenomena, identifying various dynamic processes, surface contamination and bathymetric features in the Arctic.
    • Improving the geophysical model functions for determining the key parameters of the ocean (wind, ocean surface temperature, wave height) under winds of moderate extreme speeds on the basis of the synergetics of passive and active microwave  satellite measurements.

  • Developing enhanced satellite methods.
    •  Recovering the thickness of marine ice and determining cracks from data obtained by radio-altimeters and laser altimeters.
    • Classifying the types of marine ice and identifying the edge of the ice cover from synthetic-aperture radars (SAR) and altimeters.
    • Assessing the general and special closeness of ice by SARs and optical scanners.
    • Detecting dangerous ice formations, including icebergs by SARs and optical scanners.
    • Classifying the types of marine ice from data acquired by satellite microwave radiometers.
  • Researching the «marine ice – ocean – atmosphere» system.
    •  Studying the features and trends in the «marine ice–ocean–atmosphere» system in extreme phenomena on the basis of satellite measurements.
    • Creating a simplified (applied research-oriented) physical model of the «response» of the ocean to extratropical and polar cyclones.
    • Studying the impact of feedback in  the «marine ice–ocean–atmosphere» system (occurring due to the generation of temperature «footprint» and waves) on the generation and evolution of cyclones; evaluating the effect of cyclones on the thermodynamic state of the Arctic seas.
    • Investigating the mechanisms of the formation of extreme ice conditions.
  • Creating the Arctic satellite data portal.
  • Developing methods and means for the satellite monitoring and forecasting of marine ice in the Arctic.
    • Developing a method for the automatic classification of marine ice by type (age) on the basis of data from a Sentinel-1 synthetic-aperture radar and marine ice closeness fields recovered from measurement data acquired by satellite microwave radiometers (AMSR2 and MTVZA–GYa) using the algorithms created within the Project 2019.
    • Verifying algorithms for recovering closeness of marine ice from data of measurements by AMSR2 and MTV3A-GYa satellite microwave radiometers and ASCAT satellite spectrometers under conditions of summer thaw. Comparing the results of the use of the developed algorithms and already existing satellite products.
    • Studying the spatio-temporal variability of microwave radiation and marine ice dispersion on the basis of fields of measurements by a AMSR2 radiometer and an ASCAT scatterometer with increased spatial resolution to recover the parameters of the ice cover of the Arctic.
    • Analyzing the spatio-temporal correlations between the parameters of the ice cover and the hydrometeorological parameters on the basis of satellite measurements and modeling. This will allow to create statistical models for forecasting the evolution of the ice cover of the Arctic.
  • Developing methods for remote probing, comprehensive research of the variability of the «marine ice–ocean–atmosphere» system in the Arctic in a wide range of spatio-temporal scales and implementing the results of our research in the Arctic geoinformation portal http://siows.solab.rshu.ru/ to create a system to monitor the state of the atmosphere, the ocean and the marine ice of the Arctic and to forecast its evolution. 

Implemented results of research:

The creation of the Arctic satellite data portal, a web-based GIS designed for displaying
satellite, contact and model data.

Education and career development:

As part of the «mega-grant» project, the Laboratory has developed a pilot lecture course on the remote probing of the Earth from the space.
This course is oriented towards undergraduate and postgraduate students  majoring in hydrometeorology, as well as all the employees of Russian State Hydrometeorological University willing to use satellite data on the ocean for academic and practical purposes.
The lectures were taught by leading Russian and foreign researchers during the 2012/13 academic year. The developed course includes an introduction as well as topical sections on determining the temperature of the sea surface on the basis of data from satellite IR radiometers, marine optics, passive microwave methods, introduction to satellite radiolocation, satellite altimetry, satellite scatterometry, synthetic-aperture radars (SAR), synergy of various sensors. 

Organizational and structural changes:

To support the work of the Laboratory, we have created and are continuously upgrading the material infrastructure, the core of which is comprised by a high-performance computation cluster based on IBM BladeCenterH.
The equipment’s capabilities allow to automatically process high-spatial-resolution satellite data  – both at the stage of algorithm tuning and at the stage of their application in the real-time monitoring mode. 

Other results:

Schools for young scientists were held by the Laboratory every year from 2017 to 2020 as part of the project «The marine ice–ocean–atmosphere system in the Arctic from data of satellite observations and modeling» financed by the Russian Science Foundation within the Presidential program of research projects «Conducting research in world-class laboratories».


Northern (Arctic) Federal University named after M. V. Lomonosov, Murmansk Arctic State University, Institute of Applied Physics of the Russian Academy of Sciences, P. P. Shirshov Institute of Oceanology of the Russian Academy of Sciences, A. M. Obukhov Institute of Atmospheric Physics of the Russian Academy of Sciences, International Research Center for the Research of the Environment named after Nansen (Nansen-Center), Marine Hydrophysical Institute of the Russian Academy of Sciences (Russia), Nansen Environmental and Remote Sensing Center (Norway), Danish Meteorological Institute, Risø National Laboratory of the Technical University of Denmark (Denmark), Collecte Localisation Satellites (CLS), IFREMER (France), Nanjing University of Information Science & Technology (China PR), University of Maryland, Department of Atmospheric and Oceanic Science (USA), Royal Netherlands Meteorological Institute (Netherlands).

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Yurovskaya, M.; Kudryavtsev, V.; Mironov, A.; Mouche, A.; Collard, F.; Chapron, B.
(2022). SurfaceWave Developments under Tropical Cyclone Goni (2020): Multi-Satellite Observations and Parametric Model Comparisons. Remote Sens.,14, 2032. doi.org/10.3390/rs14092032
Vladimir Kudryavtsev, Maria Yurovskaya and Bertrand Chapron
(2021). 2D parametric model for surface wave development in wind field varying in space and time. Journal of Geophysical Research: Oceans, 126(4), doi: 10.1029/⁠2020JC016915;
Vladimir Kudryavtsev, Maria Yurovskaya and Bertrand Chapron
(2021). Self-Similarity of Surface Wave Developments under Tropical Cyclones. Journal of Geophysical Research: Oceans, 126(4), doi: 10.1029/⁠2020JC016916;
Pivaev, P.D., Kudryavtsev, V.N., Korinenko, A.E., Malinovsky, V.V
(2021). Field Observations of Breaking of Dominant Surface Waves.Remote Sensing,⁠ 13⁠, 3321, doi.org/10.3390/rs13163321
Zabolotskikh E.V., K.S. Khvorostovsky, E.A. Balashova, A.I. Kostylev, V.N. Kudryavtsev
(2020). On the possibility of identifying large-scale areas of disturbed ice in the Arctic according to the ASCAT scatterometer. Modern problems of remote sensing of the Earth from space. V.17, №3, pp. 165 – 177. doi: 10.21046/2070-7401-2020-17-3-165-177
Kudryavtsev V., A. Monzikova, C. Combot, B. Chapron, N. Reul and Y. Quilfen
(2019). On ocean response to TC. Part 2: Model and Simulations. Journal of Geophysical Research: Oceans. Vol. 124, Issue 5, pp. 3462–3485. https://doi.org/10.1029/2018JC014747
Kudryavtsev V.N., E.V. Zabolotskikh, B. Chapron
(2019). Abnormal Wind Waves in the Arctic: Probability of Occurrence and Spatial Distribution. Russian Meteorology and Hydrology. Vol. 44, issue 4, pp. 268–275.
Zabolotskikh E.V., Khvorostovsky K.S., Chapron B.
(2019). An Advanced Algorithm to Retrieve ‎Total Atmospheric Water Vapor Content from the ‎Advanced Microwave Sounding ‎Radiometer Data over Sea Ice and Sea Water Surfaces in ‎the Arctic. IEEE Transactions ‎on Geoscience and Remote Sensing, pp. 1-13, doi: 10.1109/TGRS.2019.2948289.
Zabolotskikh E.V., B. Chapron
(2018). New geophysical model function for ocean ‎emissivity at 89GHz over cold Arctic waters. IEEE Geoscience and Remote Sensing ‎Letters , vol. 16 , issue 4, pp. 573 — 577, doi: 10.1109/LGRS.2018.2876731‎.
Yurovsky Yu. Yu., V. N. Kudryavtsev, B. Chapron, and S. A. Grodsky
(2018). Modulation of Ka-band Doppler Radar Signals Backscattered from Sea Surface. IEEE Transactions on Geoscience and Remote Sensing. Volume 56, Issue 5, pp. 2931-2948, DOI: 10.1109/TGRS.2017.2787459.
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