Biblio
Four-dimensional ensemble variational data assimilation and the unstable subspace. Tellus. Series A, Dynamic meteorology and oceanography 69, (2017).
Expanding the validity of the ensemble Kalman filter without the intrinsic need for inflation. Nonlinear processes in geophysics 22, (2015). Abstract
Combining inflation-free and iterative ensemble Kalman filters for strongly nonlinear systems. Nonlinear processes in geophysics 19, (2012).
Degenerate Kalman filter error covariances and their convergence onto the unstable subspace. SIAM/ASA Journal on Uncertainty Quantification (JUQ) 5, (2017).
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization. Foundations of Data Science (FoDS) 2, (2020). Abstract
Reference upper-air observations for climate: From concept to reality. Bulletin of The American Meteorological Society - (BAMS) 97, (2016).
Reference upper-air observations for climate: From concept to reality. Bulletin of The American Meteorological Society - (BAMS) (2015).doi:10.1175/BAMS-D-14-00072.1
CoCoNet: Towards Coast to Coast Networks of Marine Protected Areas (from the shore to the high and deep sea), coupled with Sea-Based Wind Energy Potential. SCIRES-IT SCIentific RESearch and Information Technology 6, (2017).
CoCoNet: Towards Coast to Coast Networks of Marine Protected Areas (from the shore to the high and deep sea), coupled with Sea-Based Wind Energy Potential. SCIRES-IT : SCIentific RESearch and Information Technology 6, (2016).
Multisensor approach to automated classification of sea ice image data. IEEE Transactions on geoscience and remote sensing 43, 1648-1664 (2005). Abstract
Download: bog05.pdf (2.31 MB)
Automatic Classification of RADARSAT SAR Images of the Northern Sea Route. In proceedings of IGARSS'99, Hamburg Germany, 28June-2July,1999 (1999).
Sea-state contributions to sea-level variability in the European Seas. Ocean Dynamics (2020).doi:10.1007/s10236-020-01404-1
Wave Climate Change in the North Sea and Baltic Sea. Journal of Marine Science and Engineering (2019).doi:10.3390/jmse7060166
Sea-level variability in the Mediterranean Sea from altimetry and tide gauges. Climate Dynamics (2016).doi:10.1007/s00382-016-3001-2
Ocean Mesoscale Variability: A Case Study on the Mediterranean Sea From a Re-Analysis Perspective. Frontiers in Earth Science 9, (2021).
Contribution of future wide-swath altimetry missions to ocean analysis and forecasting. Ocean Science (2018).doi:10.5194/os-14-1405-2018
Studies of Ice edge eddies using Synthetic Aperture Radar. (2011). Abstract
Download: Master_thesis-ElinBondevik-2011.pdf (6.06 MB)
Power law fault length distribution exponent: a synthesis. NGF (Geological Society of Norway), annual meeting, Stavanger 6-8 Jan 1999 (1999).
Statistical analysis of two dimensional fracture patterns in Granite, from Rogaland region. Second Progress Report ENV-CT97-0456 to EC (1999).
Sea ice rheology experiment (SIREx): 1. Scaling and statistical properties of sea-ice deformation fields. Journal of Geophysical Research (JGR): Oceans 127:e2021JC017667, (2022).
Fusion of Rain Radar Images and Wind Forecasts in a Deep Learning Model Applied to Rain Nowcasting. Remote Sensing 13, (2021).
Presentation of the dynamical core of neXtSIM, a new sea ice model. Ocean Modelling 91, (2015). Abstract
Download: bouillon_rampal_2015_presentation_of_the_dynamical_core_of_nextsim_a_new_sea_ice_model.pdf (5.11 MB)
On producing sea ice deformation data sets from SAR-derived sea ice motion. The Cryosphere 9, (2015). Abstract
Download: bouillon_rampal_2014_on_producing_sea_ice_deformation_data_sets_from_sar-derived_sea_ice_motion.pdf (3.53 MB)
Sea ice modelling and forecasting. New Frontiers in Operational Oceanography (2018).
