Biblio
Multisensor approach to automated classification of sea ice image data. IEEE Transactions on geoscience and remote sensing 43, 1648-1664 (2005). Abstract
Sea-state contributions to sea-level variability in the European Seas. Ocean Dynamics (2020).doi:10.1007/s10236-020-01404-1
Statistical analysis of two dimensional fracture patterns in Granite, from Rogaland region. Second Progress Report ENV-CT97-0456 to EC (1999).
Power law fault length distribution exponent: a synthesis. NGF (Geological Society of Norway), annual meeting, Stavanger 6-8 Jan 1999 (1999).
An elastic–viscous–plastic sea ice model formulated on Arakawa B and C grids. Ocean Modelling 27, 174 - 184 (2009).
Presentation of the dynamical core of neXtSIM, a new sea ice model. Ocean Modelling 91, (2015). Abstract
Sea ice modelling and forecasting. (2018).
On producing sea ice deformation data sets from SAR-derived sea ice motion. The Cryosphere 9, (2015). Abstract
Classification of sea ice types in sentinel-1 SAR data using convolutional neural networks. Remote Sensing 12, (2020).
Annual cycles of sea level and sea surface temperature in the western Mediterranean Sea. Journal of Geophysical Research Oceans 108, 4-1-4-20 (2003). Abstract
Key indicators of Arctic climate change: 1971–2017. Environmental Research Letters 14, (2019). Abstract
Global sea-level contribution from Arctic land ice: 1971-2017. Environmental Research Letters 13:125012, (2018).
Quantifying the Impact of Wind‐Current Feedback on Mesoscale Variability in Forced Simulation Experiments of the Agulhas Current Using an Eddy‐Tracking Algorithm. Journal of Geophysical Research (JGR): Oceans 125, (2020).
Connections between data assimilation and machine learning to emulate a numerical model. (2019).doi:10.5065/y82j-f154
Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model. Journal of Computational Science 44, (2020).
Data assimilation for marine monitoring and prediction: The MERCATOR operational assimilation systems and the MERSEA developments. Q. J. R. Meteorol. Soc. 131, 3561-3582 (2006).
The plankton community in Norwegian coastal waters - abundance, composition, spatial distribution and diel variation. Continental Shelf Research 31, 14 (2011).
Observed sea-level changes along the Norwegian coast. Journal of Marine Science and Engineering 5, (2017).
An assessment of HF radar current measurements in Norwegian waters. Met.no report no 2009/08 (2009).
Real time assimilation of HF radar currents into a coastal ocean model. Journal of Marine Systems 161-182 (2001).
MyOcean SIW TAC, Sea Ice products and service. ESA Living Planet Symposium (2010).at <http://www.esa.int/SPECIALS/Living_Planet_Symposium_2010/index.html>
