1. The Satellite Oceanography Laboratory: Education, Research and Transfer to the Society and Economy World” Russian State Hydrometeorological University, St. Petersburg, Russia Bertrand Chapron, IFREMER, France

2. Motivation : to accelerate development at RSHU a modern scientific direction named “Satellite Oceanography” and to establish research laboratory working in this field. The necessity of such a laboratory at RSHU is justified by fast development of the Russian satellite EO system and, therefore, the strong need in engineers and researchers working in the field of satellite data processing, analysis and applications.

3. The main goal : to establish a new research unit at RSHU, the “Satellite Oceanography Laboratory” (SOL), working in the field of:  Education through introduction of new courses in the field of EO from space, and advanced processing and analysis  Provision of satellite data and advanced geophysical products to the research and commercial activity at RSHU, with development and operative support of the RSHU web-site to ensure the distribution of the satellite data products.  Dedicated Research in the field of physical and satellite oceanography and meteorology to actively participate to the evolution and trends of future sensor high resolution capabilities  Dedicated Research towards an integrated approach to develop optimal tools to more efficiently combine model and observations,  Implementation and Marketing of the research results in terms of scientific and commercial projects (e.g. to provide safety and efficiency of commercial activity in the Arctic)

4. Tasks: 1.Implementation of satellite advanced products and models in educational and research activity at RSHU 2.Development of Super-Sites and a dedicated toolbox for scientific and applicative demonstrations of satellite products over targeted areas; 3.Research and development of new approaches and methods for satellite data processing, analysis and modeling; 4.Implementation of research results: advanced and practical demonstrations 5.Educational activity and attractivity.

5. Task 1.2 Synthetic Aperture Radar (SAR) high resolution wind, wave, current products: Wind field product Left: ASAR image produced on the 18 th of March 2011 over the Baltic Sea. Dark and bright patterns of the ASAR signal results from the wind field variability. Right: Wind velocity field derived from ASAR image using CMOD5.

6. Task 1.2 Synthetic Aperture Radar (SAR) high resolution wind, wave, current products: Wave product Great-circle trajectories of swell systems in the Pacific Ocean with periods between 10 s and 17 s. from ENVISAT SAR. Size of circles is related to the significant wave height. Trajectories are color-coded as a function of the propagation time

7. (a)Weekly mean surface geostrophic current map at 25 km resolution derived from radar altimetry from 15–22 September 2007. (b) ASAR WSM Doppler velocity map from 19 September. Task 1.2 Synthetic Aperture Radar (SAR) high resolution wind, wave, current products: c) Current product

8. WindCurrent Wave height Task 1.2 Synthetic Aperture Radar (SAR) high resolution wind, wave, current products: Example of hurricane Katrine

9. Meso-Scale Ocean Current from Space Vorticity and Divergence of Surface Currents derived from MODIS SST and SAR wind Vorticity FieldDivergence Field SST SAR-wind Vorticity Divergence

10. An example of 3-day ice drift map for the Arctic for the period 30.04-03.05.2011, composed by IFREMER from QSCAT and SSM/I data An example of monthly mean ice concentration map for the period 01.04-30.04.2011, composed from SSM/I data by IFREMER Sea Ice product

11. Task 2. Development of Super-Sites: scientific and applicative demonstrations over targeted areas Task 2.1 On-line access to data and advanced products

12. 1.Development of the Super WEB-site Informational portal 2.Mirroring of existing standard satellite data streams Technical Tasks

13. Task 2.2 A toolbox for synergetic analysis of satellite data Goal to distribute high level scientific developments with powerful tools. Powerful tools must be sufficiently intuitive for non-experts to avoid that high resolution EO data remain under-exploited. SARTool was developed to consistently assemble advanced algorithms, driven by end-user needs to exploit the wide capabilities of SAR imagery over marine scenes. The proposed effort is to go beyond the present capabilities, to design an efficient and intuitive toolbox to perform high level synergetic analysis between different sources of information. As envisaged, the SYNTool will directly help educational purposes, as well as to foster demonstrations and commercialization of advanced RSHU SOL scientific results.

14. Task 3. Research and development of new approaches for satellite data processing, analysis and modeling

15. Task 3.1 Physics of the air-sea interface and electromagnetic waves scattering a) Non-linear dynamics of wind waves, statistical properties and wave breaking b) Coupled dynamic of atmospheric boundary layer over waves, impact of wind waves on MABL including conditions of high wind speeds and limited fetches (coastal zone) c) Development of the active and passive microwave, and optical imaging model of various ocean phenomena: meso-scale currents, fronts, slicks, surface and internal waves d) Experimental study of wind waves, radar scattering and air-sea interaction:

16. Task 3.2: Reconstruction of 3D structure of meso-scale ocean circulation a)Sensor synergy and methodologies for high resolution 2D ocean surface field reconstruction: b) Consistent dynamical transformation from 2D surface features to 3D ocean structure: c) Inter-comparison and validation with independent in situ observations:

17. Task 3.3: Satellite diagnosis and 3D improved reconstruction of extreme weather events (tropical cyclones polar lows) and coastal environment a)Development of the Satellite database. b) Retrieval of the surface fields (wind, waves, stress, near surface atmospheric turbulence, etc) c) An integrated model approach:

19. Task 4 Implementation of research results: advanced and practical demonstrations Task 4.1 Satellite observations and integrated modeling for environmental applications a) Coastal areas: synergy of data and HIRLAM/WRF models b) Interactions for coastal large cities: HIRLAM plus satellite data c) Wind energy mapping: synergy of SAR and WRF model d) Benefit for SPb administration

20. Gulf of Finland and Neva Bay Area of investigation (Top) ASAR quicklook image (525m) over the Gulf of Finland, dated 23 rd of May 2011. Sea surface roughness. (Left) Neva Bay. Same Image zoomed.

21. SAR Wind Retrieval SAR Wind Product ─ Derived from the calibrated normalized radar cross section of a SAR image using information on wind directions with CMOD4 ─ Horizontal resolution 0.5 km ─ ~2 m/s accuracy (bias) for wind speeds of 2-20 m/s ─ less accurate for stronger and weaker wind speeds ─ ~1 m/s accuracy (bias) for average wind speeds of 5-9 m/s It has the advantage of providing wind right up to the coast and in bays and straits.

22. Task 4.2 "Storm-Ice-Oil Watch System": an integrated approach for the Arctic shelf region As a prototype of such a system, operational “StormWatch” system already developed at IFREMER is chosen. a)Data aggregation: Following Task 2 to provide on-line access to multiple sources of observations and ancillary information, including model outputs and in situ measurements. Parameters: Wind field with focus on storm winds and polar law events, wind waves, sea level, oil spills, ice (- type, edge, drift), etc… b) Advanced integrated modeling: Assimilation of satellite data product in the atmospheric model (WRF), coupled ocean/ice circulation model (?), wind wave model …

23. Polar Laws

25. 2007-09-21

27. Task 5 Educational activity and attractivity Development of high level expertise among student and PhD students is a major outcome of the Project. Goal is to attract and educate coming generations to more easily use and interpret the various remote sensing techniques, combined with in situ observations and numerical simulations. As proposed in Task 2, advanced tools and on-line data access easiness will be key ingredients to raise the motivation of the younger generation to contribute to the discoveries needed to better understand the Earth system and its impact on society.

28. Collaboration As stated in the Proposal, in addition to IFREMER and RSHU, the project’s team could include the well-recognized foreign and Russian experts who agreed to join the proposal to strengthen the objectives toward building improved interpretation tools and more consistent data-model Integrations. In particular list of potential partners includes: Prof. Søren Ejling Larsen (RISOE National Lab. Technical University of Copenhagen, Denmark), Prof. Alexander Baklanov ( Danish Meteorological Institute, also Prof. at RSHU), Dr. Vladimir Makin (KNMI, Netherlands), Dr. Nicolas Reul, Dr. Fabrice Ardhuin (IFREMER, France), Dr. Fabrice Collard (CLS, France), Prof. Johnny Johannessen (NERSC, Norway), Dr. Sergei Stanichnyi and Vladimir Dulov (MHI, Sebastopol, Ukraine). Prof. Oleg Kopelevich (Shirshov Institute of Oceanology RAS, Moscow), Dr. Stanislav Ermakov and Prof. Yuliya Troitskaya (IAP RAS, N. Novgorod), Dr. Irina Repina (Obukhov Institute of Atmospheric Physics RAS, Moscow). Dr. Leonid Bobylev (Nansen Center, St.Petersburg) ……. You are welcome