TY - JOUR
T1 - Enhanced iceberg drift modelling in the Barents Sea with estimates of the release rates and size characteristics at the major glacial sources using Sentinel-1 and Sentinel-2
AU - Monteban, Dennis
AU - Lubbad, Raed
AU - Samardzija, Ilija
AU - Løset, Sveinung
PY - 2020
Y1 - 2020
N2 - Glaciers with termini at sea level may calve glacial ice features that can pose threats to offshore installations in the Barents Sea, especially in the central and northern part of this sea. It is therefore of great importance to estimate the annual iceberg encounter frequencies to select robust concepts for offshore field development, to design offshore structures and possibly to plan ice management operations. These encounter frequencies are often estimated using numerical models. Regardless of the model, considerable uncertainties often exist in the input data of icebergs at the sources, i.e., the annual number of icebergs released at the source and their size characteristics. The aim of this work is to reduce these uncertainties by utilizing state-of-the-art satellite remote sensing data and a complementary numerical model of iceberg drift and deterioration. Iceberg length and width distributions derived using Sentinel-2 optical imagery are presented at the major iceberg sources in the Barents Sea, which are Franz Josef Land, the eastern side of Svalbard and Novaya Zemlya. Over 22,000 icebergs were manually identified, with the largest observed iceberg being approximately 1 km long, originating from Franz Josef Land. Furthermore, a methodology is proposed to estimate the annual number of icebergs released into the Barents Sea by comparing the model results against Copernicus iceberg density data derived from the satellite synthetic aperture radar system onboard Sentinel-1. The importance of satellite remote sensing data cannot be understated because it is undoubtedly the best way to calibrate and validate the results of numerical iceberg drift models. Finally, with the calibrated model and the derived iceberg size, a map of the Barents Sea with updated annual iceberg encounter frequencies is presented.
AB - Glaciers with termini at sea level may calve glacial ice features that can pose threats to offshore installations in the Barents Sea, especially in the central and northern part of this sea. It is therefore of great importance to estimate the annual iceberg encounter frequencies to select robust concepts for offshore field development, to design offshore structures and possibly to plan ice management operations. These encounter frequencies are often estimated using numerical models. Regardless of the model, considerable uncertainties often exist in the input data of icebergs at the sources, i.e., the annual number of icebergs released at the source and their size characteristics. The aim of this work is to reduce these uncertainties by utilizing state-of-the-art satellite remote sensing data and a complementary numerical model of iceberg drift and deterioration. Iceberg length and width distributions derived using Sentinel-2 optical imagery are presented at the major iceberg sources in the Barents Sea, which are Franz Josef Land, the eastern side of Svalbard and Novaya Zemlya. Over 22,000 icebergs were manually identified, with the largest observed iceberg being approximately 1 km long, originating from Franz Josef Land. Furthermore, a methodology is proposed to estimate the annual number of icebergs released into the Barents Sea by comparing the model results against Copernicus iceberg density data derived from the satellite synthetic aperture radar system onboard Sentinel-1. The importance of satellite remote sensing data cannot be understated because it is undoubtedly the best way to calibrate and validate the results of numerical iceberg drift models. Finally, with the calibrated model and the derived iceberg size, a map of the Barents Sea with updated annual iceberg encounter frequencies is presented.
KW - Iceberg drift model
KW - Barents Sea
KW - Iceberg production
KW - Iceberg size characteristics
KW - Sentinel satellites
U2 - 10.1016/j.coldregions.2020.103084
DO - 10.1016/j.coldregions.2020.103084
M3 - Journal article
SN - 0165-232X
VL - 175
JO - Cold Regions Science and Technology
JF - Cold Regions Science and Technology
M1 - 103084
ER -