Previous Seminars

On the statistical properties of sea ice lead fraction and heat fluxes in Arctic

Speaker: 
Sea Ice Modelling (Einar Olason)
Seminar Date: 
17. October 2017 - 11:15 - 11:45

Heat flux through leads and polynyas is an order of magnitude larger than that through unbroken ice. In this presentation we explore some statistical properties observed in Arctic sea ice lead fraction, showing that our model (neXtSIM) does a good job at reproducing the observed statistics. Given the importance of heat flux through leads we then use the model to explore the statistical properties of the modelled heat fluxes. We show that the model reproduces well the probability density function (PDF) and the mono-fractal spatial scaling of observed lead fluxes in the Central Arctic.

Two new PhD students at NERSC presents themselve and their projects.

Speaker: 
Artem Moiseev and Fabio Mangini
Seminar Date: 
12. October 2017 - 12:30 - 13:00

Bergen Teknologioverføring

Speaker: 
Steffen Boga
Affiliation: 
Bergen Teknologioverføring
Seminar Date: 
28. September 2017 - 12:30 - 13:00

As the Technology Transfer Office in Bergen, BTO supports research institutions in the region, from guiding good ideas towards commercialization of research and societal benefits. Innovation is one of the four social responsibilities in the Norwegian Act relating to universities, together with research, education and dissemination. BTO supports researchers developing innovative research ideas.

A robust solver for viscous plastic sea ice models in a finite element framework

Speaker: 
Carolin Mehlmann
Affiliation: 
"Numerical Mathematics with Applications" group at the Otto-von-Guericke university, Magdeburg, Germany
Seminar Date: 
27. September 2017 - 15:00 - 16:00

Subject of this talk are the mathematical challenges and the numerical treatment of large scale sea ice problems. The model under consideration goes back to Hibler ("A dynamic thermodynamic sea ice model", J. Phys. Oceanogr., Hibler 1979) and is based on a viscous-plastic description of the ice as a two-dimensional thin layer on the ocean surface.

Geo-Scientific Platform-as-a-Service - tools and solutions for effective access and analysis of oceanographic data

Speaker: 
Ocean and Sea Ice Remote Sensing (Morten Hansen)
Seminar Date: 
12. September 2017 - 11:15 - 11:45

Existing roadmap projects for infrastructure under the Norwegian Research Council, i.e., NorDataNet, NMDC and NORMAP, provide open data access through the OPeNDAP protocol following the conventions for CF (Climate and Forecast) metadata, designed to promote the processing and sharing of files created with the NetCDF application programming interface (API). This approach is now also being implemented in the Norwegian Sentinel Data Hub (satellittdata.no) to provide satellite EO data to the user community.

A fully probabilistic data assimilation approach for range-limited observations

Speaker: 
Abhishek Shah
Seminar Date: 
7. September 2017 - 12:30 - 13:00

Many of the measurements available in the atmospheric or oceanographic systems are only available within a limited interval of actual variation of the quantity due to the limitation of gauge or data retrieval techniques i.e, observations with detection limit. For e.g., SMOS retrieved sea-ice thickness. These observations with detection limits contains hard data (quantitative) and soft data (qualitative). The current work focuses on the development and application of the data assimilation scheme for the observations with detection limit.

Presentation on The Framework for Aquatic Biogeochemical Models (FABM): a Fortran 2003 programming framework for biogeochemical models of marine and freshwater systems.

Speaker: 
Karsten Bolding
Affiliation: 
Bolding & Bruggeman ApS
Seminar Date: 
23. August 2017 - 13:00 - 13:30

Efficient coupling of ocean models (physics) and bio-geochemistry has traditionally been a resource demanding endeavor. Typically the ocean model exists and the bio-geochemistry must be implemented as an add-on without a clear defined application programming interface (API). The result being that each implementation of a new bio-geochemical model in a given physical model lead to ad-hoc solutions only working for the specific models in question.

Geometric tools for the analysis of the stability of traveling waves

Speaker: 
Armand Vic
Affiliation: 
École Normale Supérieure (ENS) of Rennes, France
Seminar Date: 
17. August 2017 - 12:30 - 13:00

Travelling waves appear naturally in many various domains in physics such as fluid mechanics,
electromagnetic theory, etc. Intuitively, a travelling wave is a recognizable shape (of energy for
instance) which is transferred from one part of the medium to another part with a constant
speed of propagation. A broad question tackled in
geophysics is whether small errors in initial conditions can bring huge errors when

Investigation of the impact of correlated observation errors on data assimilation

Speaker: 
Rémy Dubois
Affiliation: 
Ecole des Mines ParisTech
Seminar Date: 
15. August 2017 - 12:30 - 13:10

Data assimilation (DA) are still facing various challenges and one of these challenges is the lack of knowledge on the observation error covariance matrix. Focusing on the observation error correlation, this seminar will begin by presenting Python3's DAPPER environment, followed by the presentation of various DA experiments performed with the EnKF in the Lorenz95 model (e.g. inflation of diagonal R matrices and thinning correlated structures) and the LETKF on the Quasi-Geostrophic model (innovative way to track the observations).

Hydrological modelling & Data Assimilation (at catchment scale)

Speaker: 
Marc Etienne Ridler
Affiliation: 
DHI Group, Copenhagen, Dk
Seminar Date: 
29. June 2017 - 12:30 - 13:00

Hydrological models are used extensively to monitor and manage water resources, and provide flood forecasts. These complex, physically based models are inherently uncertain due to imperfect parameterization, meteorological forcing data, initial conditions, and model discretization. Data assimilation offers a means to incorporate information from measurements to both correct model forecasts and, importantly, provides quantitative uncertainty estimates useful for decision makers.