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Mikko Lensu
Finnish Meteorological Institute
GeologySea iceSea ice thicknessArctic ice packDrift ice
52Publications
9H-index
301Citations
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Publications 51
Newest
#1M. MakynenH-Index: 8
#2Jari HaapalaH-Index: 20
Last. Larysa IstominaH-Index: 9
view all 25 authors...
The detection, monitoring, and forecasting of sea-ice conditions, including their extremes, is very important for ship navigation and offshore activities, and for monitoring of sea-ice processes and trends. We summarize here recent advances in the monitoring of sea-ice conditions and their extremes from satellite data as well as the development of sea-ice seasonal forecasting capabilities. Our results are the outcome of the three-year (2015–2018) SPICES (Space-borne Observations for Detecting an...
Source
#1Fang Li (Aalto University)H-Index: 3
#2Floris Goerlandt (Dal: Dalhousie University)H-Index: 22
Last. Mikko Lensu (Finnish Meteorological Institute)H-Index: 9
view all 5 authors...
Source
#1Ville V. Lehtola (UT: University of Twente)H-Index: 1
#2Jakub Montewka (National Land Survey of Finland)H-Index: 21
Last. Mikko Lensu (Finnish Meteorological Institute)H-Index: 9
view all 5 authors...
Abstract Safety for conventional and autonomous navigation in ice-covered waters is a topic of rising importance. Here, we propose a generic extendable framework to provide the optimal route from multiple route planning objectives. These objectives are attained by an evaluation of multi-source input data, including state-of-the-art model data for ice conditions, for bathymetric knowledge, and for ship-ice interaction. Additionally, we model the ship-ship interactions statistically using a mean-f...
1 CitationsSource
#1Mikko Lensu (Finnish Meteorological Institute)H-Index: 9
#2Floris Goerlandt (Aalto University)H-Index: 22
Abstract The automatic identification system (AIS) has become a key element in maritime domains of inquiry and the number of related articles has increased rapidly. The systematic integration of AIS data with other datatypes has received less attention and has mostly resulted in application-specific datasets that are small relative to the available AIS data. This work presents an accumulating multi-purpose database for the northern Baltic Sea that combines nine years of AIS data with marine envi...
2 CitationsSource
#1Jakub Montewka (Aalto University)H-Index: 21
#2Floris Goerlandt (Aalto University)H-Index: 22
Last. Robert GuinnessH-Index: 9
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Practical knowledge about the performance of a ship while navigating in ice is crucial for the selection of safe and efficient route for a ship. Existing route finding tools estimate ship performance in ice adopting numerous approaches, ranging from model tests and engineering models to experts-based guidelines. Therein ship performance is usually understood as attainable ship speed or the average speed in given ice conditions; rarely the probability of besetting in ice is taken into account. Th...
3 CitationsSource
#1Iina Ronkainen (Finnish Meteorological Institute)H-Index: 1
#2Jonni Lehtiranta (Finnish Meteorological Institute)H-Index: 4
Last. Christian HaasH-Index: 37
view all 6 authors...
Abstract. While variations of Baltic Sea ice extent and thickness have been extensively studied, there is little information about drift ice thickness, distribution, and its variability. In our study, we quantify the interannual variability of sea ice thickness in the Bay of Bothnia during the years 2003–2016. We use various different data sets: official ice charts, drilling data from the regular monitoring stations in the coastal fast ice zone, and helicopter and shipborne electromagnetic sound...
1 CitationsSource
2 CitationsSource
#1Fang Li (Aalto University)H-Index: 3
#2Floris Goerlandt (Aalto University)H-Index: 22
Last. Mikko Lensu (Finnish Meteorological Institute)H-Index: 9
view all 5 authors...
Abstract For the design and transit simulation of ice-going ships, a number of methods have been proposed for the prediction of ship resistance and transit speed in various ice conditions. In this paper, selected methods for ship performance in level ice, ridged ice and channel ice are evaluated based on full-scale measurement data of two ships. Uncertainties are identified and evaluated for a better understanding of the deviations in the results. Ice thickness in full-scale data was measured us...
10 CitationsSource
#2R. Berglund (VTT Technical Research Centre of Finland)
Last. Pentti KujalaH-Index: 27
view all 7 authors...
#1Lars Arneborg (SMHI: Swedish Meteorological and Hydrological Institute)H-Index: 2
#2Anders Höglund (SMHI: Swedish Meteorological and Hydrological Institute)H-Index: 11
Last. Johan MattssonH-Index: 1
view all 6 authors...
Abstract An improved oil-in-ice parameterization has been implemented in the Seatrack Web oil spill model, tested using data from the Runner 4 oil spill accident, which occurred in high ice concentrations in the Gulf of Finland on 5 March 2006. The model is able to describe the observed transport and spreading of oil reasonably well. The sensitivity of the results towards oil-in-ice parameters and hydrodynamic forcing models has been investigated. Both the mean oil trajectory and the oil spreadi...
2 CitationsSource
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