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

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.

The main goal: to establish a new research unit at RSHU, the “Satellite Oceanography Laboratory” (SOL), working in the field of:

Educationthrough introduction of new courses in the field of EO from space, and advanced processing and analysis Provision of satellite data and advanced geophysical productsto 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 meteorologyto actively participate to the evolution and trends of future sensor high resolution capabilities

Dedicated Research towards an integrated approachto develop optimal tools to more efficiently combine model and observations, Implementation and Marketingof the research results in terms of scientific and commercial projects (e.g. to provide safety and efficiency of commercial activity in the Arctic)

Tasks:1.Implementation of satellite advanced products and models in educational and research activity at RSHU2.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 demonstrations5.Educational activity and attractivity.

Task 1.2 Synthetic Aperture Radar (SAR) high resolution wind, wave, current products: Wind field product

Left: ASAR image produced on the 18th 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.

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 circlesis related to the significant wave height. Trajectories are color-coded as a function of the propagation time

(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

Wind Current Wave height

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

Meso-Scale Ocean Current from Space

Vorticity and Divergence of Surface Currents

derived from MODIS SST and SAR wind

Vorticity Field Divergence Field

SST SAR-wind

Vorticity Divergence

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

Task 2. Development of Super-Sites: scientific and applicative demonstrations over targeted areas

Task 2.1 On-line access to data and advanced products

1. Development of the Super WEB-site Informational portal

2. Mirroring of existing standard satellite data streams

Technical Tasks

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.

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

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 highwind 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:

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:

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:

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

Gulf of Finland and Neva BayArea of investigation

(Top) ASAR quicklook image (525m) over the Gulf of Finland, dated 23rd of May 2011.Sea surface roughness.

(Left) Neva Bay.Same Image zoomed.

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 resolution0.5 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.

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 …

Polar Laws

Polar Laws

2007-09-21

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.

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