Biblio
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Monitoring biodiversity from space: The ESA DIVERSITY project. IGARSS´09 (IEEE International Geoscience & Remote Sensing Symposium) (2009).
Web-GIS portal for multi-source oceanographic data of Nordic Seas. 82 (2013). Download: WEB-GIS_protal_Oceanographic_data_Phalguni.pdf (2.25 MB)
Lyapunov vectors and assimilation in the unstable subspace: theory and applications. Journal of Physics A: Mathematical and Theoretical 46, 254020 (2013).
Earth system mass transport mission (e.motion): a concept for future earth gravity field measurements from space. Surveys in geophysics 34, (2013).
Factors affecting extreme rainfall events in the South Pacific. Weather and Climate Extremes (2020).doi:10.1016/j.wace.2020.100262
Efficient Thermal Noise Removal for Sentinel-1 TOPSAR Cross-Polarization Channel. IEEE Transactions on Geoscience and Remote Sensing 56, (2018).
Classification of sea ice types in Sentinel-1 synthetic aperture radar images. The Cryosphere 14, (2020).
Feasibility Study on Estimation of Sea Ice Drift from KOMPSAT-5 and COSMO-SkyMed SAR Images. Remote Sensing 13, (2021).
Numerical solution of regularised long ocean waves using periodised scaling functions. Pramana (Bangalore) 92, (2019).
Current and turbulence measurements at the FINO1 offshore wind energy site: analysis using 5-beam ADCPs. Ocean Dynamics 68, (2017).
Skilful decadal-scale prediction of fish habitat and distribution shifts. Nature Communications 13, (2022).
Data-Assimilation by delay-coordinate nudging. Quarterly Journal of the Royal Meteorological Society 142, (2016).
Stormflo vil lamme sentrum. bt.no (2007).
Sea Ice Observations. Sea Ice Analysis and Forecasting - Towards an Increased Reliance on Automated Prediction Systems (2017).at <https://www.cambridge.org/core/books/sea-ice-analysis-and-forecasting/B74BD33160B03EE1FA77CC9BB80E7DA7>
Sea ice concentration as an essential climate variable. Earth Observation and Cryosphere Science (2012).
Implementation of a new parameterisation of the surface turbulent fluxes for the stable stratification in NWP model HIRLAM. Abstracts: 27th EGS General Assembly, Nice, France, 21-26 April 2002 (2002).
Process identification by principal component analysis of river-quality data. Ecological Modeling 138, 193-213 (2001). Download: pet01.pdf (1.2 MB)
