Biblio
Filtre: Forfatter er Laurent Bertino [Slett Alle Filtre]
3D current modelling of the South China Sea. NERSC Technical report no. 286 (2007).
Advanced data assimilation in oceanography. META 5, 8-12 (2012). Last ned: META_Bertino.pdf (2.77 MB)
Alleviating the bias induced by the linear analysis update with an isopycnal ocean model. Quarterly Journal of the Royal Meteorological Society 142, (2016). Abstract
Analysis of the northern South China Sea counter-wind current in winter using a data assimilation model. Ocean Dynamics (2015).doi:10.1007/s10236-015-0817-y
The Arctic marine forecasting center in the first Copernicus period. Proceedings of the 9th EuroGoos International Conference "Advances in Operational Oceanography": Expanding Europe's Observing and Forecasting Capacity (2021).doi:10.13155/83160
Argo profiling floats in the Nordic Seas: Deep-water circulation, hydrography and comparisons to the TOPAZ model. Master Thesis No. 53 (2006).
Assessment and propagation of uncertainties in input terms through an ocean-color-based model of primary productivity. Remote Sensing of Environment 115, (2011). Abstract
Last ned: 9f1bdea581d2a051ca64e22b0b0add4d.pdf (1.03 MB)
Assessment and Propagation of Uncertainties in Input Terms through the Vertically Generalized Productivity Model. COCOS Workshop on Combining Water Column Data with Sediment Trap and Satellite Observations for Improved Marine Carbon Export Estimates (2010). Last ned: COCOS_WSHOP_poster_v3.pdf (9.95 MB)
An assessment of the added value from data assimilation on modelled Nordic Seas hydrography and ocean transports. Ocean Modelling 99, (2016).
Assimilating altimetry data into a HYCOM model of the Pacific: Ensemble Optimal Interpolation versus Ensemble Kalman Filter. Journal of Atmospheric and Oceanic Technology 27, 753-765 (2010). Abstract
Last ned: wan10.pdf (3.84 MB)
Assimilation of semi-qualitative observations with a stochasticensemble Kalman filter. Quarterly Journal of the Royal Meteorological Society 144, (2018). Abstract
Assimilation of semi-qualitative sea ice thickness data with the EnKF-SQ: a twin experiment. Tellus A: Dynamic Meteorology and Oceanography 72, (2019). Abstract
Asynchronous data assimilation with the EnKF. Tellus A 62A, (2010). Abstract
Last ned: Asynchronous data assimilation with the EnKF.pdf (107.25 KB)
Automated Sea Ice Prediction Systems. Sea Ice Analysis and Forecasting - Towards an Increased Reliance on Automated Prediction Systems (2017).doi:10.1017/9781108417426
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization. Foundations of Data Science (FoDS) 2, (2020). Abstract
Benefits of assimilating thin sea ice thickness from SMOS into the TOPAZ system. The Cryosphere 10, (2016).
Biogeochemical Modelling. ETOOFS Expert team on Operational Ocean Forecasting System - Implementing operational ocean monitoring and forecasting systems. (2022).
Bresberg Workshop, Mohn-Sverdrup/NERSC Collaboration with IFREMER. NERSC Technical Report No. 278 (2007).
Building the capacity for forecasting marine biogeochemistry and ecosystems: recent advances and future developments. Journal of operational oceanography. Publisher: The Institute of Marine Engineering, Science & Technology 8, (2015).
