TY  - JOUR
PY  - 2019//
TI  - An iceberg forecast approach based on a statistical ocean current model
JO  - Cold regions science and technology
A1  - Andersson, Leif Erik
A1  - Scibilia, Francesco
A1  - Imsland, Lars
SP  - 128
EP  - 142
VL  - 158
IS  - 
N2  - This article proposes a statistical model for short-term iceberg drift forecasts by transforming the problem of forecasting the iceberg velocity into a problem of forecasting the ocean current velocity. A Vector-autoregression model is identified using historical ocean current data as a training set. The proposed forecast scheme is tested and analysed on four real iceberg drift trajectories. Based on these results, recommendations about the forecast horizon, the filter horizon and model order are given. Moreover, it is shown that the statistical forecast approach presented in this article offers superior performance to a conventional dynamic iceberg forecast model for short-term drift forecasts.<p />  <p>Language: en</p>
LA  - en
SN  - 0165-232X
UR  - http://dx.doi.org/10.1016/j.coldregions.2018.11.016
ID  - ref1
ER  -