scholarly journals Detecting the deformation of fast ice by InSAR technology with Sentinel-1A descending and ascending orbits data

2020 ◽  
Vol 206 ◽  
pp. 03028
Author(s):  
LIU Jian ◽  
WANG Jinning ◽  
WANG Zhiyong
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Rheological Behavior ◽  
Line Of Sight ◽  
The Baltic Sea ◽  
Amplitude Image ◽  
Fast Ice ◽  
Ice Edge ◽  
The Baltic ◽  
Ice Model

Accurate mapping of fast ice deformation can effectively characterize the rheological behavior of fast ice and subsequently improve sea ice model. This study used the Sentinel-1A descending and ascending orbits data to detect the deformations of fast ice in the Baltic Sea. A method for automatically obtaining fast ice edge line by combining interferometric coherence image and SAR amplitude image was proposed. Then, the deformations of fast ice were detected from different incidence angles with the descending and ascending orbits data. The results showed that the deformations in radar line of sight obtained from the descending and ascending orbits data were 38cm and 37cm respectively within the fast ice region of 960km2 in the study area. The continuous strong southwest wind was the principal reason for the deformation, and the deformation direction was dominated by east to west. Moreover, the inner fast ice kept stable and its deformation was smaller due to the protection of outer consolidated ice. The experimental results in this paper showed that the deformation trend and characteristics of fast ice can be better understood by InSAR technology with multi-orbits SAR data.

Succession of sea-ice bacterial communities in the Baltic Sea fast ice

Polar Biology ◽  
2008 ◽  
Vol 31 (7) ◽  
pp. 783-793 ◽  
Author(s):  
Hermanni Kaartokallio ◽  
Jaana Tuomainen ◽  
Harri Kuosa ◽  
Jorma Kuparinen ◽  
Pertti J. Martikainen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Bacterial Communities ◽  
The Baltic Sea ◽  
Fast Ice ◽  
The Baltic

Comparisons Between SAR Backscattering Coefficient and Results of a Thermodynamic Snow/Ice Model for the Baltic Sea Land-Fast Sea Ice

2007 ◽  
Vol 45 (5) ◽  
pp. 1131-1141 ◽  
Author(s):  
Marko P. Makynen ◽  
Bin Cheng ◽  
Markku H. Simila ◽  
Timo Vihma ◽  
Martti T. Hallikainen
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Backscattering Coefficient ◽  
The Baltic Sea ◽  
The Baltic ◽  
Ice Model

scholarly journals Operational SAR-based sea ice drift monitoring over the Baltic Sea

Ocean Science ◽  
2012 ◽  
Vol 8 (4) ◽  
pp. 473-483 ◽  
Author(s):  
J. Karvonen
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Vector Fields ◽  
Phase Correlation ◽  
The Baltic Sea ◽  
Sar Images ◽  
Envisat Asar ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
The Baltic

Abstract. An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR) images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine) with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

scholarly journals An Evaluation and Implementation of the Regional Coupled Ice-Ocean Model of the Baltic Sea

2017 ◽  
Author(s):  
Jaromir Jakacki ◽  
Sebastian Meler
Keyword(s):  
Baltic Sea ◽  
Three Dimensional ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Ocean Model ◽  
System Model ◽  
The Baltic Sea ◽  
Community Earth System Model ◽  
The Baltic ◽  
Ice Model

Abstract. A three dimensional, regional coupled ice-ocean model based on the open-source Community Earth System Model has been developed and implemented for the Baltic Sea. The model consists of 66 vertical levels and has a horizontal resolution of approx. 2.3 km. The paper focuses on sea ice component results but the main changes have been introduced in the ocean part of the coupled model. The hydrodynamic part, being one of the most important components, has been also presented and validated. The ice model results were validated against the radar and satellite data, and the method of validation based on probability was introduced. In the last two decades satellite and model results show an increase in the ice extent over the whole Baltic Sea, which is an evidence of a negative trend in air temperature in recent decades and increasing of winter discharge from the catchment area.

scholarly journals Sea Ice Concentration Analyses for the Baltic Sea and Their Impact on Numerical Weather Prediction

2006 ◽  
Vol 45 (7) ◽  
pp. 982-994 ◽  
Author(s):  
Matthias Drusch
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Baltic Sea ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
The Baltic Sea ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Ice Concentration ◽  
The Baltic

Abstract Sea ice concentration plays a fundamental role in the exchange of water and energy between the ocean and the atmosphere. Global real-time datasets of sea ice concentration are based on satellite observations, which do not necessarily resolve small-scale patterns or coastal features. In this study, the global National Centers for Environmental Prediction (NCEP) 0.5° sea ice concentration dataset is compared with a regional high-resolution analysis for the Baltic Sea produced 2 times per week by the Swedish Meteorological and Hydrological Institute (SMHI). In general, the NCEP dataset exhibits less spatial and temporal variability during the winter of 2003/04. Because of the coarse resolution of the NCEP dataset, ice extent is generally larger than in the SMHI analysis. Mean sea ice concentrations derived from both datasets are in reasonable agreement during the ice-growing and ice-melting periods in January and April, respectively. For February and March, during which the sea ice extent is largest, mean sea ice concentrations are lower in the NCEP dataset relative to the SMHI product. Ten-day weather forecasts based on the NCEP sea ice concentrations and the SMHI dataset have been performed, and they were compared on the local, regional, and continental scales. Turbulent surface fluxes have been analyzed based on 24-h forecasts. The differences in sea ice extent during the ice-growing period in January cause mean differences of up to 30 W m−2 for sensible heat flux and 20 W m−2 for latent heat flux in parts of the Gulf of Bothnia and the Gulf of Finland. The comparison between spatially aggregated fluxes yields differences of up to 36 and 20 W m−2 for sensible and latent heat flux, respectively. The differences in turbulent fluxes result in different planetary boundary height and structure. Even the forecast cloud cover changes by up to 40% locally.

scholarly journals TanDEM-X multiparametric data features in sea ice classification over the Baltic sea

2020 ◽  
pp. 1-20
Author(s):  
Marjan Marbouti ◽  
Oleg Antropov ◽  
Jaan Praks ◽  
Patrick B. Eriksson ◽  
Vahid Arabzadeh ◽  
...  
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
The Baltic Sea ◽  
The Baltic
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